Cancer-associated fibroblast subtypes for diagnosis, prognosis, and treatment

Abstract

This disclosure is directed to two cancer-associated fibroblast (CAP) subtypes, namely permissive (permCAF) and restraining (restCAF), in pancreatic ductal adenocarcinoma (PDAC), mesothelioma, urothelial carcinoma, or renal cell carcinoma. Methods are disclosed that describe how to identify a tumor sample as a perCAF or a restCAF subtypes. Methods are also disclosed that use the subtypes for diagnosis, prognosis, differential treatment, and treatment.

Description

Patent Atty. Dkt. No.150-35-PCT CANCER-ASSOCIATED FIBROBLAST SUBTYPES FOR DIAGNOSIS, PROGNOSIS, AND TREATMENT FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT

[0001] This invention was made with government support under Grant Number CA199064 CA274298, CA257911, CA211000, and CA106209 awarded by the National Institutes of Health; and Grant Number DGE-204-435 awarded by the National Science Foundation. The government has certain rights in the invention. REFERENCE TO A “SEQUENCE LISTING,” A TABLE, OR A COMPUTER PROGRAM LISTING APPENDIX SUBMITTED AS AN ASCII TEXT FILE

[0002] This application contains a ST.26 sequence listing appendix. It has been submitted electronically via EFS-Web as an XML file entitled “150-35-PCT.XML”. The ST.26 sequence listing is 149,152 bytes in size and was created on 06 MAY 2025. It is hereby incorporated by reference in its entirety. 1. BACKGROUND OF THE INVENTION 1.1. Introduction

[0003] The “background” description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description which may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.

[0004] It is widely recognized that the PDAC tumor microenvironment (TME) plays an important role, and can be both tumor restraining and tumor permissive1–4. PDAC is characterized by an extremely dense desmoplasia, represented as a complex mixture of extracellular matrix (ECM), blood vessels, immune cells, as well as cancer-associated fibroblasts (CAF)5–10. CAFs are key regulators in the TME. Clinical trials attempting to target the PDAC TME have been disappointing11–14. These results may be partially explained by the loss of tumor restraint with genetic depletion of CAFs in genetically engineered mouse models2,3,15.

[0005] We previously reported two PDAC stroma groups, “activated” and “normal”, where patients with “activated stroma” had decreased survival relative to normal stroma16. Maurer et al. used microdissected patient samples to derive two TME groups called “ECM-rich” and “immune- rich” stroma, with “ECM-rich” showing shorter survival17. With recent advances in single cell RNA sequencing (scRNAseq) technology, studies on the PDAC stroma have rapidly shifted to the 1Patent Atty. Dkt. No.150-35-PCT study of individual CAF and immune cell populations. In a landmark study, Elyada et. al identified “myCAF” and “iCAF” cell clusters from scRNAseq dataset (Elyada-sc) that enriched for CAF cells using fluorescence-activated cell sorting (FACS), and demonstrated gene expression signatures in the two phenotypically distinct “myCAF” and “iCAF” cell populations described in their corresponding preclinical studies18,19. More recently, additional CAF subpopulations (e.g. “csCAF”, “meCAF”, etc.) have been described20–22, as well as CAF subtypes with differential histology features23,24, and CAF related gene programs25. However, a large-scale integrative and systematic evaluation of the clinical significance of these proposed CAF subtypes or subpopulations remains lacking. 2. SUMMARY OF THE INVENTION

[0006] The present disclosure provides a method for determining a permissive cancer- associated fibroblast (permCAF) subtype or a restraining cancer-associated fibroblast (restCAF) subtype of a tumor in a biological sample, the method comprising: (a) obtaining gene expression levels for each of the following genes in the biological sample, ABCA8, ANK2, BICD1, CHRDL1, CNIH3, COL11A1, ETV1, FBLN5, IGFL2, ITGA11, KIAA1217, NOX4, NPR3, OGN, PI16, SCARA5, TGFBR3, and VSNL1; (b) performing a pair-wise comparison of the gene expression levels for each permCAF and restCAF pair in a row as follows: permCAF restCAF Coefficient(c) calculating a Top Scoring Pair (TSP) Score for the biological sample, wherein the calculating comprises: (i) assigning a value of 1 for each pair for which a permCAF gene of the pair has a higher expression level than a restCAF gene of the pair, and a value of 0 for each pair for which the permCAF gene of the pair has a lower expression level than the restCAF gene of each pair; 2Patent Atty. Dkt. No.150-35-PCT (ii) multiplying each assigned value by the coefficient listed above corresponding to each pair to calculate nine individual pair scores; and (iii) summing the nine individual pair scores together along with a baseline effect (intercept = -8.4) to calculate the TSP Score for the biological sample; and (d) converting the TSP Score to a subtype probability using the inverse-logit transformation subtype probability = expTSP Score / (1 + expTSP Score), wherein if the subtype probability is greater than or equal to 0.5, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.5, the tumor subtype is determined to be a restCAF subtype.

[0007] In the method above, we also define 0.5^ subtype probability < 0.6 as the “lean permCAF” subtype, 0.6 ^ subtype probability < 0.9 as the “likely permCAF”, and 0.9 ^ subtype probability ^ 1.0 as the “strong permCAF”, to refer to different levels of confidence of the permCAF call, in increasing order. Similarly, we define 0.4 ^ subtype probability < 0.5 as the “lean restCAF” subtype, 0.1 ^ subtype probability < 0.4 as the “likely restCAF”, and 0 ^ subtype probability ^ 0.1 as the “strong restCAF”, to refer to different levels of confidence of the restCAF call, in increasing order.

[0008] The disclosure also provides a method of determining a prognosis for a subject with a cancer, the method comprising: (a) determining if a tumor in a biological sample from the subject with cancer is a permissive cancer-associated fibroblast (permCAF) subtype or a restraining cancer-associated fibroblast (restCAF) subtype by obtaining gene expression levels for each of the following genes in the biological sample ABCA8, ANK2, BICD1, CHRDL1, CNIH3, COL11A1, ETV1, FBLN5, IGFL2, ITGA11, KIAA1217, NOX4, NPR3, OGN, PI16, SCARA5, TGFBR3, and VSNL1; (b) performing a pair-wise comparison of the gene expression levels for each permCAF and restCAF pair in a row as follows: permCAF restCAF CoefficientPatent Atty. Dkt. No.150-35-PCT (c) calculating a Top Scoring Pair (TSP) Score for the biological sample, wherein the calculating comprises: (i) assigning a value of 1 for each pair for which a permCAF gene of the pair has a higher expression level than a restCAF gene of the pair, and a value of 0 for each pair for which the permCAF gene of the pair has a lower expression level than the restCAF gene of each pair; (ii) multiplying each assigned value by the coefficient listed above corresponding to each pair to calculate nine individual pair scores; and (iii) summing the nine individual pair scores together along with a baseline effect (intercept = -8.4) to calculate the TSP Score for the biological sample; (d) converting the TSP Score to a subtype probability using the inverse-logit transformation subtype probability = expTSP Score / (1 + expTSP Score), wherein if the subtype probability is greater than or equal to 0.5, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.5, the tumor subtype is determined to be a restCAF subtype; and (e) if the tumor subtype is found to be a permCAF subtype, determining the prognosis for the subject to be poor, i.e., having a shorter overall survival rate, low change of recovery from the disease. Patients with a poor prognosis may benefit from more aggressive treatments such as high-dose chemotherapy. On the other hand, patients with a good prognosis will have a higher overall survival rate and are less likely to benefit of aggressive or experimental treatments.

[0009] In the method above, we also define 0.5^ subtype probability < 0.6 as the “lean permCAF” subtype, 0.6 ^ subtype probability < 0.9 as the “likely permCAF”, and 0.9 ^ subtype probability ^ 1.0 as the “strong permCAF”, to refer to different levels of confidence of the permCAF call, in increasing order. Similarly we define 0.4 ^ subtype probability < 0.5 as the “lean restCAF” subtype, 0.1 ^ subtype probability < 0.4 as the “likely restCAF”, and 0 ^ subtype probability ^ 0.1 as the “strong restCAF”, to refer to different levels of confidence of the restCAF call, in increasing order.

[0010] In addition, the disclosure provides a method for identifying a differential treatment strategy for a subject diagnosed with cancer, the method comprising: (a) determining if a tumor in a biological sample from the subject with cancer is a permissive cancer-associated fibroblast (permCAF) subtype or a restraining cancer-associated fibroblast (restCAF) subtype by obtaining gene expression levels for each of the following genes in the biological sample ABCA8, ANK2 , BICD1, CHRDL1, CNIH3, COL11A1, ETV1, FBLN5, IGFL2, ITGA11, KIAA1217, NOX4, NPR3, OGN, PI16, SCARA5, TGFBR3, and VSNL1; (b) performing a pair-wise comparison of the gene expression levels for each permCAF and restCAF pair in a row as follows: 4Patent Atty. Dkt. No.150-35-PCT permCAF restCAF Coefficient IGFL2 CHRDL1 1.94e biological sample, wherein the calculating comprises: (i) assigning a value of 1 for each pair for which a permCAF gene of the pair has a higher expression level than a restCAF gene of the pair, and a value of 0 for each pair for which the permCAF gene of the pair has a lower expression level than the restCAF gene of each pair; (ii) multiplying each assigned value by the coefficient listed above corresponding to each pair to calculate nine individual pair scores; and (iii) summing the nine individual pair scores together along with a baseline effect (intercept = -8.4) to calculate the TSP Score for the biological sample; and (d) converting the TSP Score to a subtype probability using the inverse-logit transformation subtype probability = expTSP Score / (1 + expTSP Score), wherein if the subtype probability is greater than or equal to 0.5, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.5, the tumor subtype is determined to be a restCAF subtype; and (e) identifying a differential treatment strategy for the subject based on the subtype assignment.

[0011] In the method above, we also define 0.5^ subtype probability < 0.6 as the “lean permCAF” subtype, 0.6 ^ subtype probability < 0.9 as the “likely permCAF”, and 0.9 ^ subtype probability ^ 1.0 as the “strong permCAF”, to refer to different levels of confidence of the permCAF call, in increasing order. Similarly we define 0.4 ^ subtype probability < 0.5 as the “lean restCAF” subtype, 0.1 ^ subtype probability < 0.4 as the “likely restCAF”, and 0 ^ subtype probability ^ 0.1 as the “strong restCAF”, to refer to different levels of confidence of the restCAF call, in increasing order.

[0012] In yet another embodiment, the disclosure provides a method for treating a subject diagnosed with cancer, the method comprising: (a) determining if a tumor in a biological sample 5Patent Atty. Dkt. No.150-35-PCT from the subject with cancer is a permissive cancer associate fibroblast (permCAF) subtype or a restraining cancer associate fibroblast (restCAF) subtype by obtaining gene expression levels for each of the following genes in the biological sample ABCA8, ANK2 , BICD1, CHRDL1, CNIH3, COL11A1, ETV1, FBLN5, IGFL2, ITGA11, KIAA1217, NOX4, NPR3, OGN, PI16, SCARA5, TGFBR3, and VSNL1; (b) performing a pair-wise comparison of the gene expression levels for each permCAF and restCAF pair as follows: permCAF restCAF Coefficient IGFL2 CHRDL1 1.94(c) ca cuat ng a op cor ng a r ( ) core or t e biological sample, wherein the calculating comprises: (i) assigning a value of 1 for each pair for which a permCAF gene of the pair has a higher expression level than a restCAF gene of the pair, and a value of 0 for each pair for which the permCAF gene of the pair has a lower expression level than the restCAF gene of each pair; (ii) multiplying each assigned value by the coefficient listed above corresponding to each pair to calculate nine individual pair scores; and (iii) summing the nine individual pair scores together along with a baseline effect (intercept = -8.4) to calculate the TSP Score for the biological sample; (d) converting the TSP Score to a subtype probability using the inverse-logit transformation subtype probability = expTSP Score / (1 + expTSP Score), wherein if the subtype probability is greater than or equal to 0.5, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.5, the tumor subtype is determined to be a restCAF subtype; and (e) treating the subject based on the subtype assignment.

[0013] In the method above, we also define 0.5^ subtype probability < 0.6 as the “lean permCAF” subtype, 0.6 ^ subtype probability < 0.9 as the “likely permCAF”, and 0.9 ^ subtype probability ^ 1.0 as the “strong permCAF”, to refer to different levels of confidence of the permCAF call, in increasing order. Similarly we define 0.4 ^ subtype probability < 0.5 as the 6Patent Atty. Dkt. No.150-35-PCT “lean restCAF” subtype, 0.1 ^ subtype probability < 0.4 as the “likely restCAF”, and 0 ^ subtype probability ^ 0.1 as the “strong restCAF”, to refer to different levels of confidence of the restCAF call, in increasing order.

[0014] In one alternative embodiment of the methods above, in step (d) if the subtype probability is greater than or equal to 0.2, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.2, the tumor subtype is determined to be a restCAF subtype. In a second alternative embodiment of the methods above, in step (d) if the subtype probability is greater than or equal to 0.4, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.4, the tumor subtype is determined to be a restCAF subtype. In a third alternative embodiment of the methods above, in step (d) if the subtype probability is greater than or equal to 0.6, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.6, the tumor subtype is determined to be a restCAF subtype. In a fourth alternative embodiment of the methods above, in step (d) if the subtype probability is greater than or equal to 0.8, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.8, the tumor subtype is determined to be a restCAF subtype.

[0015] In the methods above, the cancer may be a pancreatic ductal adenocarcinoma (PDAC), a mesothelioma, a urothelial carcinoma, or a renal cell carcinoma. In those cancers and the methods above, the biological sample may comprise a fresh sample, a frozen sample, or a formalin fixed paraffin-embedded (FFPE) sample. A variety of techniques may be used to obtain gene expression levels for these cancers and the methods above. Preferably, the gene expression levels are obtained by microarray analysis, RNAseq, quantitative RT-PCR, next-gen sequencing, multiplexed direct digital counting, such as NanoString’s nCounter® system, or a combination thereof.

[0016] For these cancers and in the methods of identifying differential treatment strategies or methods of treatment above, if the tumor is identified as the restCAF subtype, the differential treatment may be a treatment targeting a cancer expressing the restCAF subtype which may comprise an anti-PD-L1 immunotherapy in combination with chemotherapy. In some embodiments, the chemotherapy may be a VEGF signaling pathway blocker. In the treatment strategies or methods of treatment above, if the tumor is identified as the permCAF subtype, the treatment may be a treatment targeting a cancer expressing the permCAF subtype which may CCR2 immunotherapy in combination with chemotherapy. In these embodiments, the chemotherapy may be FOLFIRINOX. Alternatively, the strategy or treatment targeting the 7Patent Atty. Dkt. No.150-35-PCT permCAF subtype may comprise an extracellular matrix (ECM) modulating agent such as a pegylated human hyaluronidase, e.g., pegvorhyaluronidase alfa (PEGPH20). 3. BRIEF DESCRIPTION OF DRAWINGS

[0017] Fig. 1A-Fig. 1J. Refinement of CAF cell subpopulations and identification of marker genes. Fig. 1A, Refinement CAF cell clusters and identification of marker genes using SCISSORS in the Elyada-sc dataset. Fig. 1B, Fig. 1C, Gene set enrichment VAM score, for the Elyada and SCISSORS marker genes in each cell shown on the UMAP of Elyada-sc data. Fig. 1D, ORA showing enriched GO terms and KEGG pathways of SCISSORS myCAF-like and iCAF-like marker gene sets. Fig. 1E, VAM heatmap showing gene set enrichment of 10 schemas in the SCISSORS clusters myCAF-like, iCAF-like, apCAF-like and PSC, derived from the Elyada-sc dataset. Fig. 1F, First round of clustering on an independent scRNAseq dataset UNC- sc, using SCISSORS. Fig. 1G, Second round of clustering on CAF cells in UNC-sc using SCISSORS. Fig.1H, Fig. 1I, Violin plots and UMAP showing gene set enrichment VAM scores, of SCISSORS marker genes in UNC-sc CAF-related cells. Fig. 1J, VAM heatmap showing gene set enrichment of 10 schemas in the SCISSORS myCAF-like, iCAF-like, apCAF-like and PSC clusters in the UNC-sc dataset.

[0018] Fig. 2. The number of overlapped genes between PDAC CAF-related gene sets in 10 schemas. The intensity of the color on the heatmap showing the absolute number of gene overlaps, with greater redness indicating a larger number.

[0019] Fig. 3A-Fig. 3D. Permissive and restraining CAFs in bulk RNAseq. Fig. 3A-Fig. 3D Kaplan-Meier plots showing patient OS of CAF subtypes by CC-based schemas in pooled public datasets. Stratified log-rank test.

[0020] Fig. 4A-Fig. 4I. Development and external validation of DeCAF. Fig. 4A, Framework of DeCAF, using 9 pairs of TSP genes to derive a DeCAF permCAF probability which is then converted to the final permCAF vs restCAF call for a single sample. Fig. 4B, ROC curve for the evaluation of DeCAF calls against SCISSORS-CC labels as gold standard. Fig. 4C, Inter-study variability for the evaluation of DeCAF calls. Fig. 4D, Summary statistics of the evaluation of DeCAF subtype calls in each validation dataset. Fig. 4E, Heatmap showing SCISSORS-CC calls and DeCAF subtype calls in the pooled samples. Fig. 4F, Relationship between DeCAF score (permCAF probability) and training labels determined by SCISSORS-CC. Fig. 4G, Intersection of DeCAF with PurIST subtypes (p < 0.001, Fisher’s exact test). Fig. 4H, Proportion of patients in PurIST basal-like and classical tumor subtypes with permCAF or 8Patent Atty. Dkt. No.150-35-PCT restCAF subtypes (p<0.001, Fisher’s Exact test). Fig. 4I, Comparison of permCAF probability with PurIST tumor subtypes (p < 0.001, Wilcoxon rank-sum test).

[0021] Fig. 5A-Fig. 5L. Survival and pathology differences of DeCAF subtypes. Fig. 5A, Kaplan-Meier plot showing OS of patients with permCAF vs restCAF subtypes and Fig. 5B, patients with combination of DeCAF and PurIST tumor subtypes in pooled public datasets (p < 0.001, log-rank test, stratified datasets). Fig.5C, Multivariable Cox proportional hazards model in the pooled public datasets stratified by datasets. Fig. 5D, Kaplan-Meier plot showing OS of patients with permCAF vs restCAF subtypes and Fig. 5E, of patients in the context of combined DeCAF and PurIST tumor subtypes in the UNC-bulk dataset (p < 0.001, log-rank test). Fig. 5F, Multivariable Cox proportional hazards model in the UNC-bulk dataset. Fig. 5G, Representative hematoxylin and eosin stained slides showing a permCAF subtype sample with myxoid stroma and a restCAF subtype sample with fibrous stroma. Fig.5H, Fig.5I, Boxplots comparing DeCAF probability in samples described as having a predominant myxoid vs fibrous stroma (p = 0.007, Wilcoxon rank-sum test); or having a myxoid, fibromyxoid and fibrous stroma (p = 0.002, Kruskal-Wallis test). Fig. 5J, Fig. 5K, Kaplan-Meier plot showing OS of patients with the different stroma histologies in the UNC-bulk dataset using a predominant classification of myxoid and fibrous stroma (p = 0.004, log-rank test), or including a fibromyxoid classification (p < 0.001, log-rank test). Fig. 5L, Proportion of patients in Grünwald reactive / intermediate and deserted tumors in TCGA_PAAD with permCAF and restCAF subtypes (p < 0.001, Fisher’s Exact test).

[0022] Fig. 6A-Fig. 6B. Kaplan-Meier plots showing similar OS differences for permCAF and restCAF patients in neoadjuvant treated (FOLFIRINOX) (A) and untreated patients (B).

[0023] Fig. 7A-Fig. 7P. DeCAF subtypes in other tumor types. Fig. 7A-Fig. 7C, Kaplan- Meier plot showing OS in patients with permCAF vs restCAF subtypes in TCGA MESO, KIRC and BLCA datasets. Log-rank test. Fig. 7D, Representative hematoxylin and eosin slides showing a permCAF subtype sample with myxoid stroma and a restCAF subtype sample with fibrous stroma in TCGA MESO. Fig. 7E, Proportion of patients in each TCGA MESO histological subtype with permCAF and restCAF subtypes (p < 0.001, Fisher’s exact test). Fig. 7F, Comparison of permCAF probability between different stroma features (p = 0.001, Wilcoxon rank-sum test). Fig. 7G, Boxplot comparing permCAF probability in different TCGA BLCA consensus subtypes (p < 0.001, Kruskal-Wallis test). Fig. 7H, Proportion of patients with permCAF and restCAF subtypes within each bladder cancer consensus subtype in TCGA BLCA subtypes (p < 0.001, Fisher’s exact test). Fig.7I, Kaplan-Meier plot showing OS in patients in the context of combined tumor (basal vs luminal) and DeCAF subtypes (p = 0.011, log-rank test) Fig. 7J, Kaplan-Meier plot showing progression free survival of patients before developing MIBC 9Patent Atty. Dkt. No.150-35-PCT with permCAF and restCAF subtypes in the UROMOL dataset. Fig. 7K, Fig. 7M, Fig. 7O Proportion of patients with permCAF and restCAF subtypes in the UROMOL dataset using the bladder consensus subtype schema (K), grade (LG: low grade, HG: high grade, CIS: carcinoma in situ) (M), and class (O), Fisher’s exact test. Fig. 7L, Fig. 7N, Fig. 7P, Boxplots comparing DeCAF probability using the bladder consensus subtype schema (L), using grade (N), and class (P) in the UROMOL dataset, Kruskal-Wallis test.

[0024] Fig. 8A-Fig. 8H. Immune landscape of permCAF and restCAF subtype PDAC tumors. Fig. 8A, Comparison of immune cell fractions deconvolved using CIBERSORT and LM22 as the reference across 12 datasets. The color of the dots represents the log2 fold change (FC) of the fractions between permCAF and restCAF subtype tumors. The size of the dots represents the p-value tested by Wilcoxon rank-sum test. Fig.8B, Violin plots comparing the log2 FC of the ratio between the CD8 T cell and Treg fractions in permCAF vs restCAF subtype tumors. Wilcoxon rank-sum test. Fig. 8C, Correlation of DeCAF score (permCAF probability) in pre-treatment samples with the tumor size change in permCAF subtype (rho = -0.581, p = 0.048), and restCAF subtype (rho = -0.796, p = 0.002) tumors, Spearman correlation. Fig. 8D, Fig. 8E, Correlation of the change in neutrophil fraction (rho = 0.487, p = 0.016), and M2 macrophages fraction (rho = -0.479, p = 0.018) between pre- and post-treatment tumor samples with the percent change in tumor size, Pearson correlation. Fig. 8F, Fig. 8G, Boxplot showing the neutrophil and M2 macrophage fractions in pre- and post-treatment samples of permCAF and restCAF subtype tumors, Wilcoxon rank-sum test. Fig. 8H, Correlation of DeCAF score (permCAF probability) between pre- and posttreatment samples (p < 0.001, Spearman correlation).

[0025] Fig. 9A-Fig. 9E. DeCAF subtypes and immunotherapy response in BLCA and RCC. Fig. 9A, Fig. 9B, Boxplot comparing permCAF probability in the patients stratified by ORR in the IMmotion150 (Fig. 9A) and IMvigor 210 trials (Fig. 9B), t-test (CR: complete response, PR: partial response, SD: stable disease, PD: progressive disease). Fig. 9C, Kaplan- Meier plot showing OS of patients by DeCAF subtypes in the IMvigor210 trial. Fig. 9D, Proportion of patients with permCAF and restCAF subtype tumors within each bladder consensus subtype in IMvigor210, Fisher’s exact test (p <0.001). Fig. 9E, Boxplots comparing permCAF probability in patients with different bladder consensus subtype tumors in IMvigor210, Fisher’s exact test (p <0.001, Kruskal-Wallis test).

[0026] Fig.10A-Fig.10D. Distinct ECM regulation revealed by multi-omics analysis. Fig. 10A. Heatmap showing unsupervised clustering of matrisome proteins, which revealed association of DeCAF subtypes with matrisome clusters. Fig. 10B. Boxplot showing the Spearman correlation between RNA and protein expression levels in permCAF and restCAF 10Patent Atty. Dkt. No.150-35-PCT patients. Fig. 10C. Boxplot showing the RNA expressions of the proteins that are up-regulated in permCAF vs restCAF patients. Fig. 10D. Boxplot showing the methylation beta value of the proteins that are up-regulated in permCAF vs restCAF patients. Wilcoxon rank-sum test used for comparing the mean between two groups. 4. DETAILED DESCRIPTION OF THE INVENTION

[0027] Cancer-associated fibroblast (CAF) subpopulations in pancreatic ductal adenocarcinoma (PDAC) have been identified using single-cell RNA sequencing (scRNAseq) with divergent physical and biological characteristics. Using SCISSORS, a method that we previously developed to sensitively cluster rare cells and identify highly cell-subpopulation- specific marker genes in scRNAseq, we identify uniquely expressed marker genes for CAF clusters that robustly translate to bulk RNAseq. We show that these marker genes define subtypes with prognostic and therapeutic significance, which we define as permissive (perm) and restraining (rest) CAFs. We develop a single-sample classifier (SSC), DeCAF, to facilitate the robust and replicable classification of PDAC CAF subtypes and validate it in 12 independent bulk transcriptomic datasets. We find that DeCAF subtypes are independently prognostic, have distinct histology features, different immune landscapes, and are associated with response to immunotherapy. Furthermore, DeCAF subtypes are relevant in other cancer types, including mesothelioma. In bladder and renal cell cancers, DeCAF subtypes are prognostic and associated with anti-PD-L1 response. Here we demonstrate that DeCAF is a clinically usable and robust method to evaluate the impact of CAF subtypes in patients with mesothelioma, renal cell, bladder and pancreatic cancers. Significance

[0028] We have developed a replicable and robust classifier, DeCAF, that delineates the biological and clinical significance of the role of CAF subtypes in patients. Our results will advance the translation of preclinical CAF research, laying the groundwork for the development of CAF subtype specific therapies as well as introducing a clinically tractable CAF based subtype classifier, which may be both predictive and prognostic. 4.1. DEFINITIONS PART 1: GENES IN THE CLASSIFIER 11Patent Atty. Dkt. No.150-35-PCT

[0029] As used herein, the term “ABCA8” refers to the ATP binding cassette subfamily A member 8 gene and its transcription and translation products. Examples of the ABCA8 nucleic acid and protein sequences include NCBI Reference Sequence: NM_001288985.2 (SEQ ID NO.: 1) and NP_001275914.1 (SEQ ID NO.: 2), respectively.

[0030] As used herein, the term “ANK2” refers to the ankyrin 2 gene and its transcription and translation products. Examples of the ANK2 nucleic acid and protein sequences include NCBI Reference Sequence: NM_001148.6 (SEQ ID NO.: 3) and NP_001139.3 (SEQ ID NO.: 4), respectively.

[0031] As used herein, the term “BICD1” refers to gene encoding an adaptor protein that belongs to the bicaudal D family of dynein cargo adaptors and its transcription and translation products. Examples of the BICD1 nucleic acid and protein sequences include NCBI Reference Sequence: NM_001714.4 (SEQ ID NO.: 5) and NP_001705.2 (SEQ ID NO.: 6), respectively.

[0032] As used herein, the term “CHRDL1” refers to the chordin like gene and its transcription and translation products. Examples of the CHRDL1 nucleic acid and protein sequences include NCBI Reference Sequence: NM_001143981.2 (SEQ ID NO.: 7) and NP_001137453.1 (SEQ ID NO.: 8), respectively.

[0033] As used herein, the term “CNIH3” refers to the cornichon family AMPA receptor auxiliary protein 3 gene and its transcription and translation products. Examples of the CNIH3 nucleic acid and protein sequences include NCBI Reference Sequence: NM_152495.2 (SEQ ID NO.: 9) and NP_689708.1 (SEQ ID NO.: 10), respectively.

[0034] As used herein, the term “COL11A1” refers to the collagen type XI alpha 1 chain gene and its transcription and translation products. Examples of the COL11A1 nucleic acid and protein sequences include NCBI Reference Sequence: NM_001854.4 (SEQ ID NO.: 11) and NP_001845.3 (SEQ ID NO.: 12), respectively.

[0035] As used herein, the term “ETV1” refers to a gene encoding a protein in the E twenty- six (ETS) family of transcription factors and its transcription and translation products. Examples of the ETV1 nucleic acid and protein sequences include NCBI Reference Sequence: NM_004956.5 (SEQ ID NO.: 13) and NP_004947.2 (SEQ ID NO.: 14), respectively.

[0036] As used herein, the term “FBLN5” refers to the fibulin 5 gene and its transcription and translation products. Examples of the FBLN5 nucleic acid and protein sequences include NCBI Reference Sequence: NM_006329.4 (SEQ ID NO.: 15) and NP_006320.2 (SEQ ID NO.: 16), respectively.

[0037] As used herein, the term “IGFL2” refers to the insulin growth factor (IGF) like family member 2 gene and its transcription and translation products. Examples of the IGFL2 nucleic acid 12Patent Atty. Dkt. No.150-35-PCT and protein sequences include NCBI Reference Sequence: NM_001002915.3 (SEQ ID NO.: 17) and NP_001002915.2 (SEQ ID NO.: 18), respectively.

[0038] As used herein, the term “ITGA11” refers to integrin subunit alpha 11 gene and its transcription and translation products. Examples of the ITGA11 nucleic acid and protein sequences include NCBI Reference Sequence: NM_001004439.2 (SEQ ID NO.: 19) and NP_001004439.1 (SEQ ID NO.: 20), respectively.

[0039] As used herein, the term “KIAA1217” refers to the KIAA1217 (sickle tail protein homolog) gene and its transcription and translation products. Examples of the KIAA1217 nucleic acid and protein sequences include NCBI Reference Sequence: NM_019590.5 (SEQ ID NO.: 21) and NP_062536.2 (SEQ ID NO.: 22), respectively.

[0040] As used herein, the term “NOX4” refers to the NADPH oxidase 4 gene and its transcription and translation products. Examples of the NOX4 nucleic acid and protein sequences include NCBI Reference Sequence: NM_016931.5 (SEQ ID NO.: 23) and NP_058627.2 (SEQ ID NO.: 24), respectively.

[0041] As used herein, the term “NPR3” refers to the natriuretic peptide receptor 3 gene and its transcription and translation products. Examples of the NPR3 nucleic acid and protein sequences include NCBI Reference Sequence: NM_001204375.2 (SEQ ID NO.: 25) and NP_001191304.1 (SEQ ID NO.: 26), respectively.

[0042] As used herein, the term “OGN” refers to the osteoglycan gene and its transcription and translation products. Examples of the OGN nucleic acid and protein sequences include NCBI Reference Sequence: NM_033014.4 (SEQ ID NO.: 27) and NP_148935.1 (SEQ ID NO.: 28), respectively.

[0043] As used herein, the term “PI16” refers to the peptidase inhibitor 16 gene and its transcription and translation products. Examples of the PI16 nucleic acid and protein sequences include NCBI Reference Sequence: NM_153370.3 (SEQ ID NO.: 29) and NP_699201.2 (SEQ ID NO.: 30), respectively.

[0044] As used herein, the term “SCARA5” refers to the scavenger receptor class A member 5 gene and its transcription and translation products. Examples of the SCARA5 nucleic acid and protein sequences include NCBI Reference Sequence: NM_173833.6 (SEQ ID NO.: 31) and NP_776194.2 (SEQ ID NO.: 32), respectively.

[0045] As used herein, the term “TGFBR3” refers to the transforming growth factor beta receptor 3 gene and its transcription and translation products. Examples of the TGFBR3 nucleic acid and protein sequences include NCBI Reference Sequence: NM_003243.5 (SEQ ID NO.: 33) and NP_003234.2 (SEQ ID NO.: 34), respectively. 3Patent Atty. Dkt. No.150-35-PCT

[0046] As used herein, the term “VSNL1” refers to the visinin like 1 gene and its transcription and translation products. Examples of the VSNL1 nucleic acid and protein sequences include NCBI Reference Sequence: NM_003385.5 (SEQ ID NO.: 35) and NP_003376.2 (SEQ ID NO.: 36), respectively. 4.2. DEFINITIONS PART 2

[0047] While the following terms are believed to be well understood by one of ordinary skill in the art, the following definitions are set forth to facilitate explanation of the presently disclosed subject matter.

[0048] Throughout the present specification, the terms “about” and / or “approximately” may be used in conjunction with numerical values and / or ranges. The term “about” is understood to mean those values near to a recited value. For example, “about 40 [units]” may mean within ± 25% of 40 (e.g., from 30 to 50), within ± 20%, ± 15%, ± 10%, ± 9%, ± 8%, ± 7%, ± 6%, ± 5%, ± 4%, ± 3%, ± 2%, ± 1%, less than ± 1%, or any other value or range of values therein or there below. Alternatively, depending on the context, the term “about” may mean ± one half a standard deviation, ± one standard deviation, or ± two standard deviations. Furthermore, the phrases “less than about [a value]” or “greater than about [a value]” should be understood in view of the definition of the term “about” provided herein. The terms “about” and “approximately” may be used interchangeably.

[0049] Throughout the present specification, numerical ranges are provided for certain quantities. It is to be understood that these ranges comprise all subranges therein. Thus, the range “from 50 to 80” includes all possible ranges therein (e.g., 51-79, 52-78, 53-77, 54-76, 55-75, 60- 70, etc.). Furthermore, all values within a given range may be an endpoint for the range encompassed thereby (e.g., the range 50-80 includes the ranges with endpoints such as 55-80, 50- 75, etc.).

[0050] As used herein, the verb “comprise” as used in this description and in the claims and its conjugations are used in its non-limiting sense to mean that items following the word are included, but items not specifically mentioned are not excluded.

[0051] Throughout the specification the word “comprising,” or variations such as “comprises” or “comprising,” will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps. The present disclosure may suitably “comprise”, “consist of”, or “consist essentially of”, the steps, elements, and / or reagents described in the claims. 14Patent Atty. Dkt. No.150-35-PCT

[0052] As used herein, "remission" means and includes a period during which the symptoms of a cancer have been reduced or eliminated, as remission is ordinarily defined in the oncology art.

[0053] As used herein "serially monitoring" levels of a biomarker in a sample, refers to measuring levels of a biomarker in a sample more than once, e.g., quarterly, bimonthly, monthly, biweekly, weekly, every three days, daily, or several times per day. Serial monitoring of a level includes periodically measuring levels of biomarkers at regular intervals as deemed necessary by the skilled artisan.

[0054] The term "standard level" as used herein refers to a baseline level of a biomarker as determined in one or more normal subjects. For example, a baseline may be obtained from at least one subject and preferably is obtained from an average of subjects (e.g., n=2 to 100 or more), wherein the subject or subjects have no prior history of cancer. In the present invention, the measurement of biomarker levels may be carried out using the multiplexed copy number as described.

[0055] As used herein, "elevation" of a measured level of a biomarker relative to a standard level means that the amount or concentration of a biomarker in a sample is sufficiently greater in a subject relative to the standard to be detected by the methods described herein. For example, elevation of the measured level relative to a standard level may be any statistically significant elevation which is detectable. Such an elevation may include, but is not limited to, about a 1%, about a 10%, about a 20%, about a 40%, about an 80%, about a 2-fold, about a 4-fold, about an 8- fold, about a 20-fold, or about a 100-fold elevation, or more, relative to the standard. The term "about" as used herein, refers to a numerical value plus or minus 10% of the numerical value.

[0056] It is further noted that the claims may be drafted to exclude any optional element. As such, this statement is intended to serve as antecedent basis for use of such exclusive terminology as "solely", "only" and the like in connection with the recitation of claim elements, or the use of a "negative" limitation.

[0057] Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Preferred methods, devices, and materials are described, although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present disclosure. All references cited herein are incorporated by reference in their entirety. 4.3. COMPUTING DEVICES 15Patent Atty. Dkt. No.150-35-PCT

[0058] A computing device may be implemented in programmable hardware devices such as processors, digital signal processors, central processing units, field programmable gate arrays, programmable array logic, programmable logic devices, cloud processing systems, or the like. The computing devices may also be implemented in software for execution by various types of processors. An identified device may include executable code and may, for instance, comprise one or more physical or logical blocks of computer instructions, which may, for instance, be organized as an object, procedure, function, or other construct. Nevertheless, the executable of an identified device need not be physically located together but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the computing device and achieve the stated purpose of the computing device. In another example, a computing device may be a server or other computer located within a hospital or out-patient environment and communicatively connected to other computing devices (e.g., POS equipment or computers) for managing accounting, purchase transactions, and other processes within the hospital or out-patient environment. In another example, a computing device may be a mobile computing device such as, for example, but not limited to, a smart phone, a cell phone, a pager, a personal digital assistant (PDA), a mobile computer with a smart phone client, or the like. In another example, a computing device may be any type of wearable computer, such as a computer with a head- mounted display (HMD), or a smart watch or some other wearable smart device. Some of the computer sensing may be part of the fabric of the clothes the user is wearing. A computing device can also include any type of conventional computer, for example, a laptop computer or a tablet computer. A typical mobile computing device is a wireless data access-enabled device (e.g., an iPHONE® smart phone, a BLACKBERRY® smart phone, a NEXUS ONE™ smart phone, an iPAD® device, smart watch, or the like) that is capable of sending and receiving data in a wireless manner using protocols like the Internet Protocol, or IP, and the wireless application protocol, or WAP. This allows users to access information via wireless devices, such as smart watches, smart phones, mobile phones, pagers, two-way radios, communicators, and the like. Wireless data access is supported by many wireless networks, including, but not limited to, Bluetooth, Near Field Communication, CDPD, CDMA, GSM, PDC, PHS, TDMA, FLEX, ReFLEX, iDEN, TETRA, DECT, DataTAC, Mobitex, EDGE and other 2G, 3G, 4G, 5G, and LTE technologies, and it operates with many handheld device operating systems, such as PalmOS, EPOC, Windows CE, FLEXOS, OS / 9, JavaOS, iOS and Android. Typically, these devices use graphical displays and can access the Internet (or other communications network) on so-called mini- or micro- browsers, which are web browsers with small file sizes that can accommodate the reduced memory constraints of wireless networks. In a representative embodiment, the mobile device is a 16Patent Atty. Dkt. No.150-35-PCT cellular telephone or smart phone or smart watch that operates over GPRS (General Packet Radio Services), which is a data technology for GSM networks or operates over Near Field Communication e.g. Bluetooth. In addition to a conventional voice communication, a given mobile device can communicate with another such device via many different types of message transfer techniques, including Bluetooth, Near Field Communication, SMS (short message service), enhanced SMS (EMS), multi-media message (MMS), email WAP, paging, or other known or later-developed wireless data formats. Although many of the examples provided herein are implemented on smart phones, the examples may similarly be implemented on any suitable computing device, such as a computer.

[0059] An executable code of a computing device may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different applications, and across several memory devices. Similarly, operational data may be identified and illustrated herein within the computing device, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, as electronic signals on a system or network.

[0060] The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided, to provide a thorough understanding of embodiments of the disclosed subject matter. One skilled in the relevant art will recognize, however, that the disclosed subject matter can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosed subject matter.

[0061] As used herein, the term “memory” is generally a storage device of a computing device. Examples include, but are not limited to, read-only memory (ROM) and random access memory (RAM).

[0062] The device or system for performing one or more operations on a memory of a computing device may be a software, hardware, firmware, or combination of these. The device or the system is further intended to include or otherwise cover all software or computer programs capable of performing the various heretofore-disclosed determinations, calculations, or the like for the disclosed purposes. For example, exemplary embodiments are intended to cover all software or computer programs capable of enabling processors to implement the disclosed processes. Exemplary embodiments are also intended to cover any and all currently known, related art or later developed non-transitory recording or storage mediums (such as a CD-ROM, DVD-ROM, 17Patent Atty. Dkt. No.150-35-PCT hard drive, RAM, ROM, floppy disc, magnetic tape cassette, etc.) that record or store such software or computer programs. Exemplary embodiments are further intended to cover such software, computer programs, systems and / or processes provided through any other currently known, related art, or later developed medium (such as transitory mediums, carrier waves, etc.), usable for implementing the exemplary operations disclosed below.

[0063] In accordance with the exemplary embodiments, the disclosed computer programs can be executed in many exemplary ways, such as an application that is resident in the memory of a device or as a hosted application that is being executed on a server and communicating with the device application or browser via a number of standard protocols, such as TCP / IP, HTTP, XML, SOAP, REST, JSON and other sufficient protocols. The disclosed computer programs can be written in exemplary programming languages that execute from memory on the device or from a hosted server, such as BASIC, COBOL, C, C++, Java, Pascal, or scripting languages such as JavaScript, Python, Ruby, PHP, Perl, or other suitable programming languages.

[0064] As referred to herein, the terms “computing device” and “entities” should be broadly construed and should be understood to be interchangeable. They may include any type of computing device, for example, a server, a desktop computer, a laptop computer, a smart phone, a cell phone, a pager, a personal digital assistant (PDA, e.g., with GPRS NIC), a mobile computer with a smartphone client, or the like.

[0065] As referred to herein, a user interface is generally a system by which users interact with a computing device. A user interface can include an input for allowing users to manipulate a computing device, and can include an output for allowing the system to present information and / or data, indicate the effects of the user’s manipulation, etc. An example of a user interface on a computing device (e.g., a mobile device) includes a graphical user interface (GUI) that allows users to interact with programs in more ways than typing. A GUI typically can offer display objects, and visual indicators, as opposed to text-based interfaces, typed command labels or text navigation to represent information and actions available to a user. For example, an interface can be a display window or display object, which is selectable by a user of a mobile device for interaction. A user interface can include an input for allowing users to manipulate a computing device, and can include an output for allowing the computing device to present information and / or data, indicate the effects of the user’s manipulation, etc. An example of a user interface on a computing device includes a graphical user interface (GUI) that allows users to interact with programs or applications in more ways than typing. A GUI typically can offer display objects, and visual indicators, as opposed to text-based interfaces, typed command labels or text navigation to represent information and actions available to a user. For example, a user interface 18Patent Atty. Dkt. No.150-35-PCT can be a display window or display object, which is selectable by a user of a computing device for interaction. The display object can be displayed on a display screen of a computing device and can be selected by and interacted with by a user using the user interface. In an example, the display of the computing device can be a touch screen, which can display the display icon. The user can depress the area of the display screen where the display icon is displayed for selecting the display icon. In another example, the user can use any other suitable user interface of a computing device, such as a keypad, to select the display icon or display object. For example, the user can use a track ball or arrow keys for moving a cursor to highlight and select the display object.

[0066] The display object can be displayed on a display screen of a mobile device and can be selected by and interacted with by a user using the interface. In an example, the display of the mobile device can be a touch screen, which can display the display icon. The user can depress the area of the display screen at which the display icon is displayed for selecting the display icon. In another example, the user can use any other suitable interface of a mobile device, such as a keypad, to select the display icon or display object. For example, the user can use a track ball or times program instructions thereon for causing a processor to carry out aspects of the present disclosure.

[0067] As referred to herein, a computer network may be any group of computing systems, devices, or equipment that are linked together. Examples include, but are not limited to, local area networks (LANs) and wide area networks (WANs). A network may be categorized based on its design model, topology, or architecture. In an example, a network may be characterized as having a hierarchical internetworking model, which divides the network into three layers: access layer, distribution layer, and core layer. The access layer focuses on connecting client nodes, such as workstations to the network. The distribution layer manages routing, filtering, and quality-of- server (QoS) policies. The core layer can provide high-speed, highly-redundant forwarding services to move packets between distribution layer devices in different regions of the network. The core layer typically includes multiple routers and switches.

[0068] The present subject matter may be a system, a method, and / or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present subject matter.

[0069] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic 19Patent Atty. Dkt. No.150-35-PCT storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0070] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network, or Near Field Communication. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0071] Computer readable program instructions for carrying out operations of the present subject matter may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state- setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++, Javascript or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer 20Patent Atty. Dkt. No.150-35-PCT (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present subject matter.

[0072] Aspects of the present subject matter are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the subject matter. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer readable program instructions.

[0073] These computer readable program instructions may be provided to a processor of a computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function / act specified in the flowchart and / or block diagram block or blocks.

[0074] The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0075] The description illustrates the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present subject matter. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the herein. For example, two blocks shown in succession may, in fact, be executed substantially 21Patent Atty. Dkt. No.150-35-PCT concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustration, and combinations of blocks in the block diagrams and / or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 4.4. SAMPLES

[0076] The sample may be from a subject suspected of having a particular cancer or from a patient diagnosed with cancer, e.g., for confirmation of diagnosis or establishing a clear margin or for the detection of cancer cells in other tissues such as lymph nodes or circulating tumor cells. The biological sample may also be from a subject with an ambiguous diagnosis in order to clarify the diagnosis. The sample may be obtained for the purpose of differential diagnosis, e.g., a subject with a histopathologically benign lesion to confirm the diagnosis. The sample may also be obtained for the purpose of prognosis, i.e., determining the course of the disease and selecting primary treatment options. Tumor staging and grading are examples of prognosis. The sample may also be evaluated to select or monitor therapy, selecting likely responders in advance from non-responders or monitoring response in the course of therapy. In addition, the sample may be evaluated as part of post-treatment ongoing surveillance of patients who have had cancer.

[0077] Samples may be obtained using any of a number of methods in the art. Examples of biological samples comprising potential cancer cells include those obtained from excised biopsies, such as punch biopsies, shave biopsies, core needle biopsies, fine needle aspirates (FNA), or surgical excisions; or biopsy from tissues such as lymph node tissue, mucosa, etc. In addition, the sample may be from a distant metastatic site, a soft tissue, e.g., lung, liver, bone, skin, or brain. Representative biopsy techniques include, but are not limited to, excisional biopsy, incisional biopsy, pinch biopsy, forceps biopsy, needle biopsy, or surgical biopsy. An "excisional biopsy" refers to the removal of an entire tumor mass with a small margin of normal tissue surrounding it. An "incisional biopsy" refers to the removal of a wedge of tissue that includes a cross-sectional diameter of the tumor. A diagnosis or prognosis made by endoscopy or fluoroscopy may require a "core-needle biopsy" of the tumor mass, or a "fine-needle aspiration biopsy" which generally contains a suspension of cells from within the tumor mass. The biological sample may be a microdissected sample, such as a PALM-laser (Carl Zeiss MicroImaging GmbH, Germany) capture microdissected sample. 22Patent Atty. Dkt. No.150-35-PCT

[0078] A sample may also be a sample of an organ, a mucosal surface, blood and blood fractions or products (e.g., serum, plasma, platelets, red blood cells, white blood cells, circulating tumor cells isolated from blood, free DNA isolated from blood, and the like), sputum, saliva, lymph and tongue tissue, cultured cells, e.g., primary cultures, explants, and transformed cells, stool, urine, etc. The sample may also be vascular tissue or cells from blood vessels such as microdissected blood vessel cells of endothelial origin. A sample is typically obtained from a eukaryotic organism, most preferably a mammal such as a primate e.g., chimpanzee or human, cow, dog, cat; or a rodent, e.g., guinea pig, rat, mouse, rabbit.

[0079] A sample may be one that was treated with a fixative such as formaldehyde and embedded in paraffin (FFPE) and sectioned for use in the methods of the invention. The sample may be an archival FFPE sample. Alternatively, fresh or frozen tissue may be used. These cells may be fixed, e.g., in alcoholic solutions such as 100% ethanol or 3:1 methanol:acetic acid. Nuclei can also be extracted from thick sections of paraffin-embedded specimens to reduce truncation artifacts and eliminate extraneous embedded material. Typically, biological samples, once obtained, are harvested and processed prior to nucleic acid analysis using standard methods known in the art. Such processing typically includes protease treatment and additional fixation in an aldehyde solution such as formaldehyde. 4.5. POLYNUCLEOTIDE SEQUENCE AMPLIFICATION AND DETERMINATION

[0080] In many instances, it is desirable to amplify a nucleic acid sequence using any of several nucleic acid amplification procedures which are well known in the art. Specifically, nucleic acid amplification is the chemical or enzymatic synthesis of nucleic acid copies which contain a sequence that is complementary to a nucleic acid sequence being amplified (template). The methods and kits of the invention may use any nucleic acid amplification or detection methods known to one skilled in the art, such as those described in U.S. Pat. Nos. 5,525,462 (Takarada et al.); 6,114,117 (Hepp et al.); 6,127,120 (Graham et al.); 6,344,317 (Urnovitz); 6,448,001 (Oku); 6,528,632 (Catanzariti et al.); and PCT Pub. No. WO 2005 / 111209 (Nakajima et al.); all of which are incorporated herein by reference in their entirety.

[0081] In some embodiments, the nucleic acids may be amplified by PCR amplification using methodologies known to one skilled in the art. One skilled in the art will recognize, however, that amplification can be accomplished by other known methods, such as ligase chain reaction (LCR), Qβ-replicase amplification, rolling circle amplification, transcription amplification, self-sustained sequence replication, nucleic acid sequence-based amplification (NASBA), each of which provides sufficient amplification. Branched-DNA technology may also be used to qualitatively 23Patent Atty. Dkt. No.150-35-PCT demonstrate the presence of a sequence of the technology which may quantitatively determine the amount of this particular genomic sequence in a sample. Nolte reviews branched-DNA signal amplification for direct quantitation of nucleic acid sequences in clinical samples (Nolte, 1998, Adv. Clin. Chem.33:201-235).

[0082] The PCR process is well known in the art and is thus not described in detail herein. Multiple sequences may be analyzed simultaneously by PCT using a technique known as multiplex PCR. For a review of PCR methods and protocols, see, e.g., Innis et al., eds., PCR Protocols, A Guide to Methods and Application, Academic Press, Inc., San Diego, Calif. 1990; U.S. Pat. No. 4,683,202 (Mullis); for multiplex-PCR, see, e.g., Henegariu et al., 1997, BioTechniques, 23(3) 504-11; Markoulatos et al., 2002, J. Clin. Lab. Anal., 16(1) 47-51; and Miglietta et al., 2023, Comm. Biol. doi.org / 10.1038 / s42003-023-05235-w., which are incorporated herein by reference in their entirety. PCR reagents and protocols are also available from commercial vendors, such as Roche Molecular Systems. PCR may be carried out as an automated process with a thermostable enzyme. In this process, the temperature of the reaction mixture is cycled through a denaturing region, a primer annealing region, and an extension reaction region automatically. Machines specifically adapted for this purpose are commercially available. 4.6. HIGH THROUGHPUT AND SINGLE MOLECULE SEQUENCING TECHNOLOGY

[0083] Suitable next generation sequencing technologies are widely available. Examples include the 454 Life Sciences platform (Roche, Branford, CT) (Margulies et al.2005 Nature, 437, 376-380); lllumina’s Genome Analyzer, Illumina’s MiSeq System, Illumina’s NextSeq Systems (e.g., NextSeq 500, NextSeq 500 / 550), Illumina’s MiniSeq System, (Illumina, San Diego, CA); Bibkova et al., 2006, Genome Res. 16, 383-393; U.S. Pat. Nos. 6,306,597 and 7,598,035 (Macevicz); 7,232,656 (Balasubramanian et al.)); or DNA Sequencing by Ligation, SOLiD System (Applied Biosystems / Life Technologies; U.S. Pat. Nos. 6,797,470, 7,083,917, 7,166,434, 7,320,865, 7,332,285, 7,364,858, and 7,429,453 (Barany et al.); or the Helicos True Single Molecule DNA sequencing technology (Harris et al., 2008 Science, 320, 106-109; U.S. Pat. Nos. 7,037,687 and 7,645,596 (Williams et al.); 7,169,560 (Lapidus et al.); 7,769,400 (Harris)), the single molecule, real-time (SMRTTM) technology of Pacific Biosciences, and sequencing (Soni and Meller, 2007, Clin. Chem.53, 1996-2001) which are incorporated herein by reference in their entirety. These systems allow the sequencing of many nucleic acid molecules isolated from a specimen at high orders of multiplexing in a parallel fashion (Dear, 2003, Brief Funct. Genomic 24Patent Atty. Dkt. No.150-35-PCT Proteomic, 1(4), 397-416 and McCaughan and Dear, 2010, J. Pathol., 220, 297-306). Each of these platforms allow sequencing of clonally expanded or non-amplified single molecules of nucleic acid fragments. Certain platforms involve, for example, (i) sequencing by ligation of dye- modified probes (including cyclic ligation and cleavage), (ii) pyrosequencing, (iii) targeted next- generation sequencing from bisulfite treated DNA, and / or (iv) single-molecule sequencing.

[0084] Pyrosequencing is a nucleic acid sequencing method based on sequencing by synthesis, which relies on detection of a pyrophosphate released on nucleotide incorporation. Generally, sequencing by synthesis involves synthesizing, one nucleotide at a time, a DNA strand complementary to the strand whose sequence is being sought. Study nucleic acids may be immobilized to a solid support, hybridized with a sequencing primer, incubated with DNA polymerase, ATP sulfurylase, luciferase, apyrase, adenosine 5' phosphsulfate and luciferin. Nucleotide solutions are sequentially added and removed. Correct incorporation of a nucleotide releases a pyrophosphate, which interacts with ATP sulfurylase and produces ATP in the presence of adenosine 5' phosphosulfate, fueling the luciferin reaction, which produces a chemiluminescent signal allowing sequence determination. Machines for pyrosequencing are available from Qiagen, Inc. (Valencia, CA). An example of a system that can be used by a person of ordinary skill based on pyrosequencing generally involves the following steps: ligating an adaptor nucleic acid to a study nucleic acid and hybridizing the study nucleic acid to a bead; amplifying a nucleotide sequence in the study nucleic acid in an emulsion; sorting beads using a picoliter multiwell solid support; and sequencing the amplified nucleotide sequences by pyrosequencing methodology (e.g., Nakano et al., 2003, J. Biotech. 102, 117-124). Such a system can be used to exponentially amplify amplification products.

[0085] Next-generation sequencing (NGS) is a nucleic acid sequencing method based on sequencing by synthesis, where fluorescently labeled deoxyribonucleotide triphosphates (dNTPs) catalyzed by DNA polymerase are incorporated into a DNA temple through cycles of DNA synthesis and nucleotides are identified by fluorophore excitation at each incorporation step. NGS allows this process to take place in a multiplex reaction across millions of DNA fragments in parallel. Generally, sequencing by synthesis involves synthesizing, one nucleotide at a time, a DNA strand complimentary to the strand whose sequence is being sought. Study nucleic acids may be immobilized to a solid support, hybridized with a sequencing primer, and incubated with DNA polymerase in the presence of fluorescently labeled dNTPS. After each cycle, the image is scanned and the emission wavelength and intensity are recorded and used to identify the base incorporated. This process is repeated multiple times to create a specific read length of bases. 25Patent Atty. Dkt. No.150-35-PCT

[0086] Certain single-molecule sequencing embodiments are based on the principal of sequencing by synthesis, and some utilize single-pair Fluorescence Resonance Energy Transfer (single pair FRET) as a mechanism by which photons are emitted as a result of successful nucleotide incorporation. The emitted photons often are detected using intensified or high sensitivity cooled charge-couple-devices in conjunction with total internal reflection microscopy (TIRM). Photons are only emitted when the introduced reaction solution contains the correct nucleotide for incorporation into the growing nucleic acid chain that is synthesized as a result of the sequencing process. In FRET based single-molecule sequencing or detection, energy is transferred between two fluorescent dyes, sometimes polymethine cyanine dyes Cy3 and Cy5, through long-range dipole interactions.

[0087] An example of a system that can be used based on single-molecule sequencing generally involves hybridizing a primer to a study nucleic acid to generate a complex; associating the complex with a solid phase; iteratively extending the primer by a nucleotide tagged with a fluorescent molecule; and capturing an image of FRET signals after each iteration (e.g., Braslavsky et al., PNAS 100(7): 3960-3964 (2003); U.S. Pat. No. 7,297,518 (Quake et al.) which are incorporated herein by reference in their entirety). Such a system can be used to directly sequence amplification products generated by processes described herein. In some embodiments, the released linear amplification product can be hybridized to a primer that contains sequences complementary to immobilized capture sequences present on a solid support, a bead or glass slide for example. Hybridization of the primer-released linear amplification product complexes with the immobilized capture sequences, immobilizes released linear amplification products to solid supports for single pair FRET based sequencing by synthesis. The primer often is fluorescent, so that an initial reference image of the surface of the slide with immobilized nucleic acids can be generated. The initial reference image is useful for determining locations at which true nucleotide incorporation is occurring. Fluorescence signals detected in array locations not initially identified in the "primer only" reference image are discarded as non-specific fluorescence. Following immobilization of the primer-released linear amplification product complexes, the bound nucleic acids often are sequenced in parallel by the iterative steps of, a) polymerase extension in the presence of one fluorescently labeled nucleotide, b) detection of fluorescence using appropriate microscopy, TIRM for example, c) removal of fluorescent nucleotide, and d) return to step a with a different fluorescently labeled nucleotide.

[0088] The technology described herein may be practiced with digital PCR. Digital PCR was developed by Kalinina and colleagues (Kalinina et al., 1997, Nucleic Acids Res. 25; 1999-2004) and further developed by Vogelstein and Kinzler (1999, Proc. Natl. Acad. Sci. U.S.A. 96; 9236- 26Patent Atty. Dkt. No.150-35-PCT 9241). The application of digital PCR is described by Cantor et al. (PCT Pub. Nos. WO 2005 / 023091A2 (Cantor et al.); WO 2007 / 092473 A2, (Quake et al.)), which are hereby incorporated by reference in their entirety. Digital PCR takes advantage of nucleic acid (DNA, cDNA or RNA) amplification on a single molecule level and offers a highly sensitive method for quantifying low copy number nucleic acids. Fluidigm® Corporation offers systems for the digital analysis of nucleic acids. Digital PCR has been extended to digital droplet PCR (ddPCR) to detect rare mRNA transcripts. See Hindson et al., 2011, Anal. Chem.83(22) 8604-8610.

[0089] In some embodiments, nucleotide sequencing may be by solid phase single nucleotide sequencing methods and processes. Solid phase single nucleotide sequencing methods involve contacting sample nucleic acid and solid support under conditions in which a single molecule of a sample nucleic acid hybridizes to a single molecule of a solid support. Such conditions can include providing the solid support molecules and a single molecule of sample nucleic acid in a "microreactor." Such conditions also can include providing a mixture in which the sample nucleic acid molecule can hybridize to solid phase nucleic acid on the solid support. Single nucleotide sequencing methods useful in the embodiments described herein are described in PCT Pub. No. WO 2009 / 091934 (Cantor).

[0090] Next generation sequencing techniques may be applied to measure expression levels or count numbers of transcripts using RNA-seq or whole transcriptome shotgun sequencing. See, e.g., Mortazavi et al., 2008 Nat. Meth. 5(7) 621-627 or Wang et al., 2009 Nat. Rev. Genet. 10(1) 57-63.

[0091] Nucleic acids in the invention also may be counted using methods known in the art. In one embodiment, multiplexed direct digital counting of RNA expression is performed using NanoString’s nCounter® system (Seattle, WA). The system is amplification-free and attaches fluorescent barcodes to nucleic acid probes, incubates the labeled probes with an mRNA sample to form hybrid sequences, plates the probe target hybrids, and directly counts the barcodes for the hybrids. See Veldman-Jones et al., 2015, Cancer Res. 75(13) 2587-2594; Kulkarni, M. M., 2011, Current protocols in molecular biology, 94(1), 25B-10; Geiss et al., 2008 Nat. Biotech 26(3) 317- 325; U.S. Pat. No. 7,473,767 (Dimitrov). Spatial resolution to transcript identification may be added in a high-throughput manner with NanoString’s Digital Spatial Profiling (DSP) platform for nucleic acids or proteins. See Blank et al., 2018 Nature Medicine 241655–1661; Amaria et al., 2018 Nature Medicine 24 1649–1654; Wang et al., 2020 Front Oncol. 10 447 doi: 10.3389 / fonc.2020.00447. Alternatively, Fluidigm’s Dynamic Array system may be used (South San Francisco, CA). Byrne et al., 2009 PLoS ONE 4 e7118; Helzer et al., 2009 Can Res 697860- 7866. For reviews, see Zhao et al., 2011 Sci. China Chem. 54(8) 1185-1201; Ozsolak and Milos, 27Patent Atty. Dkt. No.150-35-PCT 2011 Nat. Rev. Genet. 12 87-98; for cancer transcription methods, see Cieslik and Chinnaiyan, 2018, Nat. Rev. Genet. 19 93-109. Technologies such as single molecule recognition through equilibrium Poisson sampling (SiMREPS) also may be used for sequencing samples. See Mandel et al., 2022, Methods 19763-73.

[0092] Samples may be sequenced using RNAseq to bulk sequence the sample. Alternatively, samples may be laser-captured microdissected samples. In other embodiments, the single cell RNA (scRNA) sequencing technology may be used. Methods for scRNA expression profiling in nanoliter droplets a technique called Drop-seq or inDrops. For Drop-seq, see Macosko et al., 2015, Cell 1611202-1214; for inDrops, see Klein et al., 2015, Cell 1611187-1201.

[0093] In certain embodiments, nanopore sequencing detection methods include (a) contacting a nucleic acid for sequencing ("base nucleic acid," e.g., linked probe molecule) with sequence-specific detectors, under conditions in which the detectors specifically hybridize to substantially complementary subsequences of the base nucleic acid; (b) detecting signals from the detectors, and (c) determining the sequence of the base nucleic acid according to the signals detected. In certain embodiments, the detectors hybridized to the base nucleic acid are disassociated from the base nucleic acid (e.g., sequentially dissociated) when the detectors interfere with a nanopore structure as the base nucleic acid passes through a pore, and the detectors disassociated from the base sequence are detected.

[0094] A detector also may include one or more regions of nucleotides that do not hybridize to the base nucleic acid. In some embodiments, a detector may be a molecular beacon. A detector often comprises one or more detectable labels independently selected from those described herein. Each detectable label can be detected by any convenient detection process capable of detecting a signal generated by each label (e.g., magnetic, electric, chemical, optical and the like). For example, a CD camera can be used to detect signals from one or more distinguishable quantum dots linked to a detector.

[0095] The invention encompasses methods known in the art for enhancing the sensitivity of the detectable signal in such assays, including, but not limited to, the use of cyclic probe technology (Bakkaoui et al., 1996, BioTechniques 20: 240-8, which is incorporated herein by reference in its entirety); and the use of branched probes (Urdea et al., 1993, Clin. Chem.39, 725- 6; which is incorporated herein by reference in its entirety). The hybridization complexes are detected according to well-known techniques in the art.

[0096] Reverse transcribed or amplified nucleic acids may be modified nucleic acids. Modified nucleic acids can include nucleotide analogs, and in certain embodiments include a detectable label and / or a capture agent. Examples of detectable labels include, without limitation, 28Patent Atty. Dkt. No.150-35-PCT fluorophores, radioisotopes, colorimetric agents, light emitting agents, chemiluminescent agents, light scattering agents, enzymes and the like. Examples of capture agents include, without limitation, an agent from a binding pair selected from antibody / antigen, antibody / antibody, antibody / antibody fragment, antibody / antibody receptor, antibody / protein A or protein G, hapten / anti-hapten, biotin / avidin, biotin / streptavidin, folic acid / folate binding protein, vitamin B12 / intrinsic factor, chemical reactive group / complementary chemical reactive group (e.g., sulfhydryl / maleimide, sulfhydryl / haloacetyl derivative, amine / isotriocyanate, amine / succinimidyl ester, and amine / sulfonyl halides) pairs, and the like. Modified nucleic acids having a capture agent can be immobilized to a solid support in certain embodiments. 4.7. COMPOSITIONS AND KITS

[0097] The invention provides compositions and kits detecting the biomarkers described herein using antibodies or other reagents specific for the nucleic acids specific for the polynucleotides described herein. Kits for carrying out the diagnostic assays of the invention typically include, in a suitable container means, (i) a probe that comprises an antibody or nucleic acid sequence that specifically binds to the marker polynucleotides of the invention, (ii) a label for detecting the presence of the probe, and (iii) instructions for how to measure the level the polynucleotide. The kits may include several antibodies or polynucleotide sequences encoding biomarkers disclosed herein, e.g., a first antibody and / or second and / or third and / or additional antibodies that recognize the biomarkers or specific nucleic acids. In one embodiment the nucleic acids in the kit are the forward and reverse PCR primers for the biomarkers disclosed herein. The container means of the kits will generally include at least one vial, test tube, flask, bottle, syringe and / or other container into which a first antibody specific for one of the polypeptides or a first nucleic acid specific for one of the polynucleotides of the present invention may be placed and / or suitably aliquoted. Where a second and / or third and / or additional component is provided, the kit will also generally contain a second, third and / or other additional container into which this component may be placed. Alternatively, a container may contain a mixture of more than one antibody or nucleic acid reagent, each reagent specifically binding a different marker in accordance with the present invention. The kits of the present invention will also typically include means for containing the antibody or nucleic acid probes in close confinement for commercial sale. Such containers may include injection and / or blow-molded plastic containers into which the desired vials are retained. 29Patent Atty. Dkt. No.150-35-PCT

[0098] The kits may further comprise positive and negative controls, as well as instructions for the use of kit components contained therein, in accordance with the methods of the present invention. 4.8. METHODS OF TREATMENT

[0099] Current treatments for pancreatic cancer include FOLFIRNOX (fluorouracil (5-FU), leucovorin, irinotecan, and oxaliplatin) or gemcitabine and albumin-bound paclitaxel for neoadjuvant or adjuvant therapy for resectable disease, borderline resectable disease, first line therapy for locally advanced disease, or first line therapy for metastatic disease. If specific mutations are present, there are FDA-approved treatments available. Specifically for tumors with the BRAF V600E mutation, guidelines recommend one treat with kinase inhibitors, dabrafenib (targeting BRAF) and trametinib (targeting MEK1 / 2). For tumors that have the NTRK gene fusion, guidelines recommend one treat with entrectinib (targeting TRK, ROS, ALK) or larotrectinib (targeting TRKA, TRKB, TRKC). If the tumor is RET gene fusion positive, guidelines recommend one treat with selpercatinib (targeting RET). If the tumor mutation burden (TMB) is great than 10 mutations per megabase or is MSI-H or dMMR, guidelines recommend one treat with pembrolizumab. See, NCCN Guidelines Pancreatic Adenocarcinoma Ver. 1.2024. Many cancers are responsive to kinase inhibitors. There are many approved kinase inhibitors which may be small molecule drugs, monoclonal antibodies, monoclonal antibody drug conjugates, etc. Table 1 lists a number of approved kinase inhibitors, relevant biomarkers for companion diagnostics, their intended target(s), and indicated uses.

[0100] KRAS mutations are common in PDAC and other cancers. KRAS mutations are associated with shortened survival for malignant pleural mesothelioma (MPM). See, Vannuchi et al., 2023, Cancers, 15, 2027 doi.org / 10.3390 / cancers15072072. Smal et al. reported a prevalence of RAS mutations in 11.2% of bladder cancers, of which HRAS accounted for 64.3%, KRAS, for 28.6%, and NRAS, for 7.1%. Smal et al., 2016, The opposite association of HRAS and KRAS mutations with clinical variables of bladder cancer. Russ J Genet Appl Res 6, 613–621. A subset of renal cell carcinomas, specifically, papillary renal neoplasm with reverse polarity (PRNRP), one study reported that 28 / 30 samples had recurrent KRAS mutations.

[0101] Several KRAS specific drugs are now approved or in advanced clinical trials. Specifically, KRASG12Cinhibitors, LUMAKRAS® (Sotorasib, AMG 510); KRASATITM(Adagrasib, MRTX849), BI1823911, LY3537982, JNJ-74699157 (ARS3248), JDQ443, Glecirasib (JAB-21822), Garsorasib (D-1553), Divarasib (GDC-6036, RG6330). Unfortunately, while the G12C mutation is common in many cancers, G12C mutation is only present 1-2% of 30Patent Atty. Dkt. No.150-35-PCT pancreatic cancers. See Elhariri et al., 2023, World J. Clin. Oncol. 14(8) 285-296. Another mutation, G12D, is also common. KRASG12Dinhibitors in development MRTX1133 and degrader ASP3082. Other approaches include pan-RAS inhibitors such as RMC-6236. Another compound in clinical trials is BI 1701963, a KRAS inhibitor that acts on the KRAS / SOS1 (son of sevenless 1) complex. Indirect inhibition of the RAS pathway can be accomplished by SHP2 inhibitors such as BBP-398 (formerly IACS-15509), ERAS-601, ET0038, GDC-1971(RLY-1971), HBI-2376, HS-10381, JAB-3068, or JAB-3312, RMC-4630, or TNO155. See Stalnecker and Der, 2020, Science Signaling, 13, eaay6013; Hu et al., 2024, Nat. Rev. Gastro. Hepatol., 21 (1) 7-24.

[0102] Perez et al. reported a number of clinical trials targeting the extracellular matrix (ECM) for pancreatic ductal adenocarcinoma (PDAC). Perez et al., 2021, Front. Oncol. 11:751311. The targets include hyaluronic acid (HA) using PEGylated human hyaluronidase (PEGPH20) and chemotherapy. The hedgehog pathway is targeted by sonic hedgehog (Shh) inhibitors such as vismodegib or IPI-926 in conjunction with chemotherapy. Other studies target the vitamin D receptor, a regulator of transcription in CAFs and PSCs, using vitamin D mimic, calcipotrol. Lastly, several studies are underway looking to block TGFβ signaling. Table 2 lists a number of clinical studies targeting the ECM and lists the particular treatment, the intended targets, and the study populations.

[0103] The following Examples further illustrate the disclosure and are not intended to limit the scope. In particular, it is to be understood that this disclosure is not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be limited only by the appended claims. 5. EXAMPLES

[0104] Using SCISSORS, a method that we previously developed to sensitively cluster rare cells and identify highly cell-subpopulation-specific marker genes in scRNAseq, we identify uniquely expressed marker genes for CAF clusters that robustly translate to bulk RNAseq26. We show that these marker genes define subtypes with prognostic and therapeutic significance, which we define as permissive (perm) and restraining (rest) CAFs. We then train and validate a single- sample classifier (SSC) DeCAF, to facilitate robust and replicable classification of PDAC CAF subtypes in 12 independent bulk transcriptomic datasets of patient PDAC samples. We find that DeCAF subtypes are independently prognostic and associated with distinct histologic features. DeCAF subtype tumors have different immune landscapes and are associated with treatment 31Patent Atty. Dkt. No.150-35-PCT response in a phase Ib trial of FOLFIRINOX and CCR2 inhibition27. We show that DeCAF subtypes are relevant in other cancer types, including mesothelioma, urothelial carcinoma and clear cell renal cell carcinoma. In urothelial and clear cell renal cell carcinoma, DeCAF subtypes are prognostic and associated with response to anti-PD-L1 therapy. Here we demonstrate that DeCAF is a clinically usable and robust method to evaluate the impact of CAF subtypes in patients with mesothelioma, renal cell, bladder and pancreatic cancers. RESULTS Refinement of CAF cell subpopulations and marker genes

[0105] Using SCISSORS26, a method that we showed can find rare cell clusters (e.g. 0.1% of cells in a dataset), and the the Elyada-sc dataset18which is enriched for fibroblasts, we refined the identification of fibroblast subpopulations to identify distinct marker genes (Fig. 1A, Table 3). We annotated our clusters as myCAF-like, iCAF-like, and apCAF-like, based on the enrichment of previously defined Elyada panCAF, consisting of myCAF, iCAF and apCAF (murine) genes18(Fig. 1B). After marker gene identification, we demonstrate that the newly determined SCISSORS marker genes show higher specificity in marking the respective clusters (Fig. 1C). Only 1 gene overlapped between SCISSORS myCAF-like (n = 116) and Elyada myCAF genes (n = 16), and 10 genes overlapped between SCISSORS iCAF-like (n = 209) and Elyada iCAF genes (n = 35). To determine gene ontology differences between SCISSORS myCAF-like and iCAF- like genes, we performed over-representation analysis28(ORA) (Table 4). In contrast to the prior findings in Elyada et al. where only myCAF genes were enriched for ECM organization and collagen formation18,19, we found that both SCISSORS myCAF-like and iCAF-like genes were enriched in ECM and collagen regulation related terms, albeit with different genes (Fig. 1D, Table 4). This may suggest potential distinct mechanisms of ECM regulation in the two CAF subpopulations. In addition to JAK-STAT signaling (hsa04630) that has been previously described to be enriched for Elyada iCAF genes18, we also found genes defining our iCAF-like subgroup to be enriched in Ras signaling pathway (hsa04014) and PI3K-Akt signaling pathway (hsa0415)29–31, not previously reported (Fig. 1D). Our results support that SCISSORS CAF marker genes are distinct from the originally defined Elyada myCAF and iCAF genes, in terms of the actual genes identified, the corresponding cells and pathway function.

[0106] We then compared SCISSORS marker genes to other previously described CAF subpopulations using 8 additional PDAC CAF cell-subpopulation schemas16,17,20–25. We found that the overlap between SCISSORS genes and the other gene sets was limited (Fig. 2). To better compare how gene sets from different schemas may be associated with the same cell populations, 32Patent Atty. Dkt. No.150-35-PCT we computed VAM scores32for each gene set in the Elyada-sc fibroblast cell populations (Fig. 1E, Methods). This allows us to compare enrichment of gene sets across schemas rather than individual genes for each cell and their clusters. The myCAF-like cluster called by SCISSORS in the Elyada-sc dataset showed enrichment of gene sets of Elyada myCAF, Ogawa F-stroma and A- stroma, Chen cCAF, Hwang myofibroblastic, Oh IL11-CAF and myCAF, and Wang myCAF (Fig. 1D). The iCAF-like cell cluster showed enrichment of gene sets from Elyada iCAF, Ogawa C-stroma, Chen csCAF, Grünwald deserted, Hwang neurotropic and adhesive, Oh csCAF and iCAF, and Wang non-typicalCAF and iCAF (Fig. 1E). For bulk RNAseq derived signatures, we find that Moffitt activated stroma and Maurer ECM-rich genes are more enriched in myCAF-like than iCAF-like cell clusters, and that Moffitt normal stroma and Maurer immune-rich genes are enriched in both iCAF-like and apCAF-like cell clusters, with Moffitt normal stroma also showing enrichment in a pancreatic stellate cell (PSC) cluster (Fig.1D).

[0107] Next, we further validated the above SCISSORS-defined cell-level gene sets using an independent scRNAseq dataset of 6 primary PDAC samples (UNC-sc, Table 5). In the UNC-sc data, we similarly identified one pancreatic stellate cell (PSC) cluster, one apCAF-like cluster, two myCAF-like clusters and three iCAF-like clusters (Fig. 1F-Fig. 1I, Methods). In this independent UNC-sc dataset, we found that the SCISSORS-derived marker genes best discriminated between the cell clusters (Fig.1J). For example, while the SCISSORS myCAF-like genes were found to be uniquely enriched in the two annotated myCAF-like clusters, the Elyada myCAF genes, as well as myCAF associated gene markers in other schemas were found to be enriched in multiple cell clusters such as PSC and iCAF-like clusters (Fig. 1J). By leveraging the refined methodology for clustering and marker gene identification by SCISSORS26, we identify marker genes that are uniquely expressed in and most discriminatory between the CAF cell subpopulations. Permissive and restraining CAFs in bulk RNAseq

[0108] One challenge in evaluating the clinical relevance of CAF subpopulations derived from scRNAseq is the paucity of samples with both scRNAseq and clinical outcome information. Therefore, we set out to translate the marker genes derived from scRNAseq for use in bulk transcriptomics data. We previously showed that the basal-like and classical marker genes derived from scRNAseq using SCISSORS may also be used to cluster bulk RNAseq of PDAC samples, and highly recapitulated the clinically validated PDAC tumor subtypes26. Therefore, we hypothesized that the SCISSORS CAF marker genes derived from scRNAseq may also be used to cluster bulk RNAseq data for the classification of CAF subtypes in these patient samples. 33Patent Atty. Dkt. No.150-35-PCT

[0109] To investigate this, we evaluated 11 publicly available bulk RNAseq and microarray datasets containing 1,432 primary PDAC patients using consensus clustering (CC) (Methods, Table 6). In all datasets, the SCISSORS top 25 myCAF-like and iCAF-like genes separate patient samples into two clusters . In a meta-analysis of the 11 datasets, patients with tumors that have higher expression of myCAF-like genes showed a significantly shorter median OS (mOS) of 20.33 months (mos), while patients with tumors that have higher expression of iCAF-like genes had a longer mOS of 30.19 mos (p < 0.001, HR = 1.40 [95% CI 1.317-1.725], Fig.3A). In light of the clinical implications of our results and avoid conflict with the existing nomenclature, we rename and hereafter refer to the subpopulation expressing the SCISSORS iCAF-like genes as tumor restraining CAF (restCAF) and the subpopulation expressing SCISSORS myCAF-like genes as tumor permissive CAF (permCAF).

[0110] Next, we performed a systematic comparison between the previously published CAF subtyping schemas using the gene signatures from Elyada et al.18, Moffitt et al.16, and Maurer et al.17to call subtypes in each of the 11 datasets using CC . In contrast to SCISSORS, we found that the Elyada myCAF and iCAF gene sets resulted in consensus clusters that showed no difference in OS (mOS: 21.32 vs 25.20 mos, p = 0.339, HR = 1.203 [95% CI 1.532-0.945], Fig. 3B). The Moffitt stroma schema demonstrated shorter survival for patients with tumors with activated stroma relative to normal stroma but did not reach significance in our pooled datasets (mOS: 21.45 vs 30.0 mos, p = 0.082, HR = 1.279 [95% CI 0.991-1.651], Fig. 3C). We also found that Maurer ECM-rich and Immune-rich gene signatures are associated with differences in survival (mOS: 20.53 vs 30.03 mos, p = 0.005, HR = 1.33 [95% CI 1.047-1.69], Fig. 3D). Using the Bayesian information criterion (BIC)33where the model with the lowest BIC in a series of competing candidate models is preferred in statistical applications, and is agnostic to the magnitude of the difference34, we found that SCISSORS was the preferred model with the lowest BIC, (SCISSORS BIC = 4553 vs Maurer BIC = 4558). Development and external validation of DeCAF

[0111] Clustering techniques have many limitations, such as their inability to assign subtypes to individual patients and the lack of robustness in existing subtype assignments due to the re- clustering required for the addition of new samples to existing data. Thus, we developed a robust SSC, DeCAF (Fig. 4A, Table 7), to predict permCAF and restCAF subtypes in individual patients, using CC based training labels derived in four large bulk gene expression datasets (Training datasets: CPTAC, Dijk, Moffitt GSE71729, TCGA PAAD, Table 6, Methods). A key element of our method includes the utilization of our CAF marker genes derived by SCISSORS to avoid the possible confounding of the expression of these genes in tumor and other tissue types. 34Patent Atty. Dkt. No.150-35-PCT The final DeCAF classifier uses rank-derived predictors through the k Top Scoring Pair (kTSP) (https: / / github.com / jjyeh-unc / decaf) (Fig. 4A, Methods); the same approach that we employed for the PurIST PDAC tumor classifier35. This approach avoids using raw expression values which reduced its dependence on between sample / study normalization, simplifying data integration over different studies35–38 and during prediction on new samples.

[0112] To assess the quality of our prediction model, we first evaluate the cross-validation error of the final model in our Training Group samples. We find that the internal leave-one-out cross validation error for DeCAF in the Training Group is low (4.0%). To evaluate the overall classification performance of DeCAF across additional studies, we compare the DeCAF subtype calls to the SCISSORS subtype calls in an independent validation dataset of 7 patient cohorts (Table 6). First, we applied a nonparametric meta-analysis approach to obtain a consensus ROC curve based on the individual ROC curves from each validation study. We found that the overall consensus Area Under the Curve (AUC) is high, with a value of 0.961 (Fig. 4B). The estimated interstudy variability of these ROC curves with respect to predicted permCAF score threshold t is very low at our standard threshold of t=0.5 or greater (Fig. 4C). Furthermore, sensitivities and specificities were often high at this threshold, and AUC values were similarly strong ( > 0.8) (Fig. 4D). Across validation datasets, we find that the pooled samples strongly segregate by CC subtype when sorted by their DeCAF score (i.e. permCAF probability), despite diverse studies of origin (Fig. 4E). This suggests that our methodology avoids potential study-level effects. As expected, the relative expression of classifier genes within each classifier TSP (paired rows) strongly discriminates between subtypes in each sample, forming the basis of our robust TSP- oriented approach for subtype prediction (Fig. 4E). We also find that, predicted permCAF probability scores have strong correspondence with CC subtype labels, illustrating the relative extent of each subtype as a continuum (Fig. 4F). For example, permCAF probability scores in the in between 0.25-0.75 are associated with mixed gene expression on CC.

[0113] Next, we compared the association of DeCAF subtypes with basal-like and classical tumor-intrinsic subtypes as defined by PurIST. We found that 64.5% (N=167) of basal-like tumors had a permCAF subtype, but only 35.5% of basal-like tumors had a restCAF subtype (N=92). No difference was seen in CAF subtypes within classical tumors: 49.7% permCAF (N=529) vs 50.3% restCAF (N = 536), suggesting an affinity for basal-like tumors to be a permCAF subtype (p < 0.001, Fisher’s exact test, Fig. 4G, Fig. 4H). Similarly, we found that patients with basal-like subtype tumors showed significantly higher permCAFprobability scores than patients with classical subtype tumors (Fig.4I). DeCAF subtypes and survival outcome 35Patent Atty. Dkt. No.150-35-PCT

[0114] To evaluate the clinical impact of DeCAF subtypes on outcome, we first performed a meta-analysis of the 9 pooled datasets with OS data available (Table 8). We find that the patients with permCAF subtype tumors (mOS 17.70 mos) have significantly shorter survival than patients with restCAF subtype tumors (mOS 29.04 mos) (stratified HR = 1.634, 95% CI 1.375-1.943, p < 0.001, stratified log-rank test) (Fig. 5A). Patients with PurIST basal-like and DeCAF permCAF subtype tumors had the shortest OS, while patients with PurIST classical and DeCAF restCAF subtype tumors had the longest OS (11.01 mos vs 30.43 mos, p < 0.001, Fig. 5B).To determine the relationship between DeCAF and PDAC tumor subtypes16,35,39, we first performed a multivariable stratified cox proportional hazard model for the pooled public datasets including DeCAF and PurIST subtypes as variables. We found that both PurIST tumor subtype and the DeCAF subtype were independently associated with survival (p < 0.001 for both, stratified Cox proportional hazards model, Fig.5C).

[0115] Next, we applied DeCAF to another independent patient cohort of primary PDAC at UNC where clinical and pathology variables were available (UNC-bulk, N = 129) and find that DeCAF subtypes are again associated with OS (HR = 2.255, 95% CI 1.423-3.574, p < 0.001, log- rank test) (Fig. 5D). We saw similar additive effects of DeCAF and PurIST subtypes and their relationship to OS (p < 0.001, log-rank test, Fig.5E). In an univariable analysis, we found that the restCAF subtype was associated with chronic pancreatitis on pathology (p=0.008, Fisher’s exact test), although chronic pancreatitis had no association with OS (Table 9). There was no difference in the prevalence of DeCAF subtypes derived from samples exposed to neoadjuvant chemotherapy compared to untreated patients (Fig. 6A, Fig. 6B). In a multivariable analysis of patients who had complete (R0) resections, DeCAF and PurIST subtypes remained independently prognostic when including the variables stage, differentiation and lymphovascular invasion (LVI) (DeCAF p < 0.001 and PurIST p = 0.005, Cox proportional hazards model, Fig.5F). Pathology differences in DeCAF subtypes

[0116] Differential pathology features of PDAC CAF subtypes were previously found, where the stroma of a subgroup of patients were described as collagen-enriched23,24. To investigate the association of DeCAF subtypes with pathological features, hematoxylin and eosin stained slides (n = 106) were reviewed by a pathologist blinded to the subtype calls in the UNC-bulk dataset . Samples were annotated as either myxoid, fibrous or fibromyxoid with the fibromyxoid subtypes delineating a mixed appearance with the dominant histology noted40 (Fig.5G). We found that the restCAF subtype tumors were associated with a fibrous (51 / 74, 68.9%) compared to a myxoid stroma histology (23 / 74, 31.1%) (p = 0.018, Fisher’s exact test). Samples with myxoid dominant histology showed significantly more permCAFness (i.e. higher permCAF probability) compared 36Patent Atty. Dkt. No.150-35-PCT to fibrous histology samples (p = 0.007, Wilcoxon rank-sum test, Fig. 5H). The mixed histology type, fibromyxoid, showed intermediate permCAF probability, supporting that the DeCAF score is associated with a histologic continuum (p = 0.002, Kruskal-Wallis test, Fig. 5I). Interestingly, stroma histology alone was prognostic, with myxoid histology associated with the shortest OS, fibromyxoid with intermediate OS, and fibrous the longest (p = 0.004, log-rank test, Fig. 5J, Fig. 5K). In the TCGA_PAAD dataset, where Grünwald et al. described subTME types, we looked at the relationship between DeCAF and the subTME types. We found that 89.6% (60 / 67) of permCAF subtype tumors had a reactive / intermediate subTME, compared to 10.4% (7 / 67) of them had a deserted subTME (Fig. 5L). In contrast, 43.5% (40 / 92) of restCAF subtype tumors had a reactive / intermediate subTME compared to 56.5% (52 / 92) that had a deserted subTME (Fig.5L, p = 9.582e-10, Fisher’s exact test). DeCAF subtypes in other tumor types

[0117] Similarities in CAFs across cancer types have been studied41,42. To determine if DeCAF subtypes are clinically applicable in other cancer types, we evaluated the TCGA Pan- Cancer datasets and found that DeCAF subtypes are similarly prognostic in malignant pleural mesothelioma (MESO, HR=2.056, 95% CI 1.1, 3.84 , p = 0.021), clear cell renal cell (KIRC, HR=2.138, 95% CI 1.342, 3.407, p = 0.0011) and urothelial bladder (BLCA, HR 1.6, 95% CI 1, 2.6, p = 0.043) carcinomas (Fig.7A-Fig.7C).

[0118] Given the clinical similarities of fibrosis that characterizes both MESO43 and PDAC, we hypothesized that there may also be similar pathology findings that explain the relevance of DeCAF subtypes in MESO. We found that DeCAF subtypes were associated with histological type (p = 0.001) with 93% (53 / 57) of epithelioid type tumors having a restCAF subtype (Fig. 7D, Fig. 7E). Pathologist review of the stroma showed similar findings as PDAC, where a myxoid stroma was associated with higher permCAF probability (i.e. permCAFness) compared to a fibrous histology (Wilcoxon, p = 0.001, Fig.7F).

[0119] In bladder cancer where consensus subtypes have been described including a basal bladder subtype (Ba / Sq) with similar gene expression to basal-like PDAC, we found that similar to PDAC, the Ba / Sq bladder consensus subtype was enriched in the permCAF subtype, with 52.0% (80 / 152, p = 1.22e-13, Fisher’s exact test, Fig. 7G) of Ba / Sq subtype patients having a permCAF subtype and highest permCAF probability (Fig. 7H) in the TCGA BLCA dataset. In addition, we also see a relationship between Ba / Sq tumor subtype and DeCAF subtype (p = 0.011, log-rank test, Fig. 7I). In a dataset of non-muscle invasive bladder cancer (NMIBC), UROMOL44, we find that patients with permCAF subtype tumors have a shorter progression free survival to developing MIBC (PFS, p=0.00082, log-rank test) (Fig. 7J). Using the BLCA 37Patent Atty. Dkt. No.150-35-PCT consensus subtyping schema, 75% (3 / 4, p= 0.00166, Fisher’s exact test) of Ba / Sq tumors had a permCAF subtype and had the highest permCAF probability scores (Fig. 7K, Fig. 7L). Using standard clinical groupings of NMIBC, we found that permCAF prevalence and higher permCAF probability scores (i.e. permCAFness) was associated with higher grade (p = 8.7e-06, Kruskal- Wallis test, Fig. 7M, Fig. 7N) and most enriched in Class 2a NMIBC [18% (25 / 142), p = 0.000301, Fisher’s exact test], the most aggressive class of NMIBC (Fig.7O, Fig.7P).

[0120] Taken together, our results show that the presence of the permCAF subtype is associated with poor prognosis in multiple cancer types with similar histology and tumor subtype associations as PDAC. Immune landscape of permCAF and restCAF subtype tumors

[0121] We hypothesized that the perm / rest CAF subtype tumors may harbor different immune landscapes. Therefore, we used CIBERSORT45 with LM22 as the reference to deconvolve the fractions of 22 types of immune cells in each of our 12 datasets (Fig. 8A). We found that the immune landscape was more immunosuppressive in permCAF, enriched an average of 1.3-fold in Tregs in 6 datasets, 1.9-fold neutrophils in 5 datasets, 1.8-fold in M0 macrophages in 10 datasets, 1.1-fold in M2 macrophages in 6 datasets (Fig. 8A). In contrast, restCAF subtype tumors were more enriched an average of 1.3-fold in M0 macrophages in 4 datasets, 1.5-fold in CD8+ T cells in 7 datasets, and 1.8-fold in naïve B cells in 6 datasets (Fig. 8A). In addition, restCAF subtype tumors showed significantly higher CD8 / Treg ratios in 8 datasets (Fig. 8B), suggesting that patients with different DeCAF subtype tumors may show more favorable response to certain immunotherapies compared to patients with permCAF subtype tumors46,47.To investigate if DeCAF subtypes are predictive of immunotherapy response in PDAC patients, we examined the Phase 1b trial of FOLFIRINOX in combination with PF-04136309, a CCR2 inhibitor (FFX+PF) which has both pre- and post-treatment samples (Linehan dataset)27. Within each subtype, we found that increasing permCAF probability (i.e. increasing permCAFness) in the pre-treatment sample was correlated with a greater percent decrease in tumor size (permCAF rho = -0.581, p = 0.048; restCAF rho = -0.796, p = 0.002, Spearman correlation, Fig. 8C). We hypothesized that as CCR2 inhibition targets the recruitment of inflammatory monocytes, our findings may be explained by the enrichment of monocytes in the permCAF subtype samples (Fig. 8A). As this trial had pre- and post-treatment samples, we next looked at the change in neutrophil and M2 macrophages after treatment. We found that decreases in the neutrophil fraction (rho = 0.487, p = 0.016, Pearson correlation) and increases in the M2 macrophage fraction (rho = -0.479, p = 0.018, Pearson correlation) was correlated with tumor response (Fig. 8D, Fig. 8E). In the original trial, 38Patent Atty. Dkt. No.150-35-PCT CD14+CCR2+ tumor associated macrophages were found to be significantly decreased in FFX+PF treated tumors of 6 patients, but association with response was not avaialble27.

[0122] We next looked at the relationship between DeCAF subtypes and immune cell population changes in the FFX+PF trial. We found that the decrease in neutrophil and increase in M2 macrophage fractions were specific to permCAF subtype tumors and not found in restCAF subtype tumors (Fig. 8F, Fig. 8G). However, there was overall correlation of DeCAF score between pre- and post-treatment samples (rho = 0.675, p < 0.001, Fig. 8H), suggesting that the changes may be less in the CAF subtype, but rather the immune microenvironment associated with the DeCAF subtype. Our results suggest that the DeCAF subtype specific immune microenvironment may predict immunotherapy responsiveness. DeCAF subtypes and immunotherapy response in BLCA and RCC

[0123] Clinical trials of immunotherapy in PDAC are limited. As DeCAF subtypes were prognostic in BLCA and RCC, we evaluated the IMvigor210 trial (NCT02108652) in BLCA48 and the IMmotion150 trial (NCT01984242) in RCC49 where patients were treated with the anti- PD-L1 antibody, atezolizumab. In the IMmotion150 trial of metastatic RCC patients, in the atezolizumab only arm, lower DeCAF score or permCAF probability (i.e. increased restCAFness) was numerically, but not significantly associated with having a complete (CR) or partial response (PR) (p = 0.077, t-test, Fig. 9A). In the IMvigor210 trial for metastatic urothelial cancers, we found that patients who had either a CR or PR had significantly lower permCAF probability (i.e. increased restCAFness) (p = 0.014, t-test, Fig. 9B). In addition, patients with permCAF subtype tumors had a mOS of 6.7 months compared to 9.9 months for patients with restCAF tumors (p = 0.043, HR 1.4 [95% CI 1.01, 1.95], Fig. 9C). Finally, similar to PDAC and the TCGA BLCA dataset, in IMvigor210, we found that Ba / Sq subtype tumors were most enriched in the permCAF subtype with 33% (36 / 109) of Ba / Sq subtype harboring a permCAF subtype (p = 3.81e-05, Fisher’s exact test, Fig.9D). As expected, higher DeCAF probability was associated with a Ba / Sq tumor subtype as well (p = 5.5e-13, Kruskal-Wallis test, Fig.9E). Therefore, renal cell carcinoma and bladder cancer patients with restCAF tumors have an increased overall response rate (ORR) to immune checkpoint inhibition. Distinct ECM regulation revealed by multi-omics analysis

[0124] To gain a better understanding of the protein profiles between permCAF and restCAF patients, we analyzed the whole proteomics data from CPTAC doi: 10.1016 / j.cell.2021.08.023. 354 proteins were found to be up-regulated in permCAF patients and 358 proteins were found to be up-regulated in restCAF patients (Fig. 10A, Table 10). Gene ontology analysis showed enrichment for ECM related terms for both permCAF and restCAF proteins, where they over- 39Patent Atty. Dkt. No.150-35-PCT expressed two different lists of ECM proteins. Using a curated matrisome database, we systematically analyzed the matrisome proteins, and found that 594 ECM-related proteins were captured without missing values in this CPTAC dataset. Unsupervised clustering on these proteins revealed two robust clusters (Fig. 10A), which interestingly showed a significant association with the DeCAF subtypes. Cluster 1 was found to have a relatively even split between permCAF (31, 43.1%) and restCAF (41, 56.9%) patients, while cluster 2 was found to be enriched with permCAF (47, 74.6%) than restCAF (16, 25.4%) patients. This suggested that permCAF and restCAF patients express distinct groups of ECM proteins, which may explain the differences in pathological phenotypes of “myxoid” vs “collagenized” that we described above. We then focused on the 97 and 54 differentially expressed matrisome proteins in permCAF and restCAF respectively to understand if these proteins were regulated differently by integrating methylation, RNA and protein data. By analyzing matched RNAseq and proteomics data, we found that the RNA and protein levels were highly correlated in both permCAF and restCAF patients (Fig. 10B), compared to 0.35 as the median level for all protein-RNA pairs as previously reported [doi: 10.1016 / j.cell.2021.08.023]. The correlation in permCAF patients is even higher in restCAF patients (p < 0.0001). In addition, for proteins that were up-regulated in permCAF patients, the respective RNA levels were also up-regulated in permCAF patients, while this pattern was not seen in restCAF patients (Fig. 10C). This suggested that the upregulation and downregulation of ECM proteins were highly regulated through RNA levels in the permCAF patients, but not in restCAF patients. More intriguingly, up-regulated proteins in permCAF were more hypomethylated than down-regulated proteins in permCAF patients (Fig.10D), indicating that the RNA-protein levels of these genes were regulated through epigenetic methylation mechanisms. In contrast, this pattern was not observed for restCAF (Fig. 10D). Altogether, this may suggest that the ECM protein expressions in permCAF were subject to methylation regulation, while a different group of ECM proteins were regulated through distinct mechanisms in restCAF patients. These epigenetic, transcriptomic and proteomic differences in permCAF vs restCAF patients may be the molecular underpinnings for the differences in pathological, immunological, prognostic and response features that we illustrated above. DISCUSSION

[0125] Several CAF classifications have been described. Here we leverage the wealth of sc and bulk transcriptomic studies in PDAC to identify the most clinically relevant and robust CAF subtypes. As clustering tends to introduce problems of instability during between-sample normalization when a new sample is added, it is not an optimal option to use clustering-based 40Patent Atty. Dkt. No.150-35-PCT methods to call patient subtypes in the clinical setting. For CAF subtype classification, we developed an SSC DeCAF, which uses 9 pairs of TSP genes to call permCAF vs restCAF subtypes, instead of the raw expression values, that is robust and replicable. This considerably increases the flexibility and practicality of integrating CAF subtypes into the analysis across datasets, including clinical trials with limited sample sizes and potential utilization in future clinical trials.

[0126] A key element of our method includes the utilization of CAF-intrinsic subpopulation marker genes identified using our novel method SCISSORS26. Our identified myCAF-like and iCAF-like clusters and genes correspond to, but also more discretely call the widely accepted myCAF and iCAF subtypes18. In an independent scRNAseq dataset (UNC-sc), we show that SCISSORS CAF marker genes accurately discriminate between the respective CAF cell subpopulations compared to previously described CAF subpopulations gene sets16–18,20–25. The discriminatory ability of SCISSORS CAF marker genes was critical to successfully deriving CAF-intrinsic subtypes in bulk RNAseq data.

[0127] myCAFs were initially described and are thought to be more quiescent with iCAFs as inflammatory and tumor promoting19. However, our findings suggest that, in patients, the CAF subpopulations have opposite phenotypes compared to the majority of preclinical studies, with permCAF (myCAF-like) subtypes with worse prognosis compared to restCAF (iCAF-like) subtypes. This is in agreement with a recent study that found that myCAFs may be pro- metastatic50. Thus, to improve clarity and better describe our clinical findings, we use the terms permissive and restraining. We find that the histologic features of the stroma in PDAC and mesothelioma have direct associations with the DeCAF subtypes with permCAF subtype tumors having myxoid stroma, and restCAF subtype tumors having fibrous stroma. The DeCAF score allows us to look at mixtures where fibromyxoid (mixed) stroma have intermediate DeCAF scores. Our findings of fibrous histology are consistent with the previously described “deserted subTME” by Grünwald et al. and a “collagen-rich stroma” or “C-stroma” by Ogawa et al. In contrast to prior studies where myCAFs are thought to be enriched with ECM pathways18,19, we find the restCAF subtype to also be enriched with ECM pathways but attributable to different genes. This association of restCAF and ECM enrichment is in agreement with Grünwald et al23, where the “deserted subTME” was enriched in ECM proteins, and with Ogawa et al., where longer OS and higher collagen content was associated with C-stroma24. Our immune cell landscape analysis by CIBERSORT also suggested similar immune infiltrations found by these two studies. For example, our findings that the restCAF subtype showed higher naïve B cell fractions is in line with the finding by Grünwald et al., that the deserted subTME trended toward 41Patent Atty. Dkt. No.150-35-PCT higher B cell marker (CD20) expression in their deep-phenotyping platform for human PDAC tissues23. In addition, permCAF showing higher CD8+ T cell percentages is in agreement with the finding that FAP-stroma was characterized by restricted CD8+ cell infiltrates24.

[0128] Many studies have reported common CAF types across cancers41,42. We found that DeCAF subtypes have clinical relevance in mesothelioma, renal cell and bladder carcinomas. In bladder cancer, where the PDAC basal-like gene signature can be used to accurately recall the Ba / Sq bladder consensus subtype16, both of which have an enrichment of cytokeratins, we find that the permCAF subtype is enriched in both basal bladder Ba / Sq and PDAC basal-like subtype tumors. Furthermore, both tumor and CAF subtype affect prognosis in an additive fashion. Finally, our findings of differential immune microenvironments associated with the permCAF vs restCAF subtype has implications for immunotherapy response in renal cell, bladder and pancreatic cancers.

[0129] In summary, we find that DeCAF subtypes are histologically distinctive, prognostic and predictive of treatment response in multiple cancer types. In pancreatic, renal cell and bladder cancers, the immune microenvironment specific to the subtypes may help predict response to immunotherapy approaches. Our findings that the biology of previously described iCAF and myCAF subgroups, where iCAFs were thought to be pro-tumorigenic, in patients, is completely reversed, suggests that the interest in targeting iCAF populations may not be as beneficial as originally thought18, and may explain some of the disappointing trials to date. We present a clinically tractable CAF subtype SSC, DeCAF, that determines permCAF and restCAF subtypes in patients that may be incorporated into clinical trials, will facilitate the translation of preclinical studies to patients, and provides a framework for the understanding of CAF subtypes in patients for the development of CAF subtype specific therapies. METHODS Marker gene identification in Elyada-sc

[0130] SCISSORS includes a carefully designed function, which is a two-step method for the identification of highly cell subpopulation specific genes26. Briefly, SCISSORS first derives a candidate gene set by comparing the cell subpopulation of interest to the most related cell subpopulation; then the highly expressed genes from other unrelated cell types are removed from this candidate gene set. In this study using the Elyada-sc dataset, myCAF-like cells were compared to iCAF-like and apCAF-like cells, and the iCAF-like cells were compared myCAF- like and apCAF-like cells, to derive a candidate gene set for the cell subpopulation of myCAF- like and iCAF-like separately (Wilcoxon rank-sum test, p<0.05, log2 fold change > 0). Then, the myCAF-like and iCAF-like candidate gene sets were subjected to a filtering step, in which the 42Patent Atty. Dkt. No.150-35-PCT highly expressed genes of the non-CAF cells were removed. The highly expressed genes were defined as the top 10% expressed by averaging all the cells within each broad cell cluster. As a result, final gene sets were identified for myCAF-like and iCAF-like respectively (Table 3). Tumor dissociation and library preparation for UNC-sc

[0131] Six de-identified primary PDAC samples (UNC-sc, Table 4) were collected from the IRB-approved University of North Carolina Lineberger Comprehensive Cancer Center Tissue Procurement Core Facility after IRB exemption in accordance with the U.S. Common Rule. Fresh tissue was dissociated into single cells using Miltenyi human dissociation kits (Miltenyi, 130-095- 929) and red blood cells were removed using red blood cell lysis solution (Miltenyi, 130-094- 183). Cell counts were performed using an automated cell counter and live cell counts were determined using trypan blue staining. Up to 10,000 cells were encapsulated into droplets for droplet-based 3’ end single-cell RNAseq using Chromium 3’ v3 reagents (10X Genomics). cDNA libraries were quantified using the Qubit dsDNA Assay Kit (Thermo, Q32851) and library quality was assessed with the 4150 Tapestation System (Agilent) and D5000 screen tapes (Agilent, 5067- 5588). cDNA libraries were sequenced on a NextSeq500 (Illumina) using NextSeq 500 / 550 High Output Kit v2.5 (150 Cycles) (Illumina, 20024907) at 200M reads per sample. Sample collection and processing for UNC-bulk

[0132] 129 de-identified primary PDAC patient samples (UNC-bulk) were collected from the IRB-approved University of North Carolina Lineberger Comprehensive Cancer Center Tissue Procurement Core Facility after IRB exemption in accordance with the U.S. Common Rule and were flash frozen in liquid nitrogen. FFPE samples were prepared, hematoxylin and eosin stained. RNA expression libraries were generated for flash frozen samples or FFPE samples, with TruSeq Stranded mRNA kits or with KAPA RNA HyperPrep Kit with RiboErase (HMR) according to the manufacturer’s instructions. Sequencing was performed on the NextSeq500 and NovaSeq6000 Sequencing Systems (Illumina). UNC-sc processing

[0133] Cell Ranger 6.1.2 was used. BCL files was converted into fastq files using cellranger mkfastq based on bcl2fastq2 (v2.20.0). Fastq files for each sample was then processed by cellranger count to derive unique molecular identifier (UMI) count for each gene, using the human GRCh38 genome. Samples were then aggregated by cellranger aggr.

[0134] Aggregated data (filtered_feature_bc_matrix) were analyzed by SCISSORS, which is wrapped around Seurat (v4), for cell clustering. The Quality control steps include 1) the inclusion of genes expressed in more than 2 cells, 2) the inclusion of cells that have the number of genes captured within 200~2500 (200 < nFeatures < 2500), and 3) the inclusion of cells with 43Patent Atty. Dkt. No.150-35-PCT mitochondrial reads accounting for less than 5% (percent_MT < 5). The filtered data underwent processing through the PrepareData() function in SCISSORS to obtain the initial clusters with the following parameter settings: n.HVG = 3000, regress.mt = TRUE, n.PC = 20, random.seed = 629, with other parameters using default values. The first-round clusters were annotated using SingleR. Clusters identified as "activated_stellate" were categorized as fibroblasts. A second-round clustering analysis was performed on the fibroblast related clusters (0,4,6) using the ReclusterCells function in SCISSORS, with the following parameter settings: merge.clusters = TRUE, use.sct = TRUE, n.HVG = 3000, regress.mt = TRUE, n.PC = 20, resolution.vals = 0.2, k.vals = 57, with other parameters using default values. For a more refined identification, a third- round clustering analysis was conducted on the cluster identified as a combination of myCAF-like and iCAF-like. VAM heatmap

[0135] For the CAF-related cells (myCAF-like, iCAF-like, apCAF-like and PSC) in Elyada-sc and UNC-sc datasets, VAM32 scores were generated to assess the gene set enrichment of CAF- related gene markers of SCISSORS and 9 additional schemas. The median of the VAM scores in the same cells was derived to represent the enrichment score of each gene sets in each cell cluster. For the same cell cluster, z-score transformation was applied to derive the VAM z-score, which was visualized on a heatmap. On the heatmap, each row represents a cell cluster and each column represents a marker gene set from each schema. The intensity of the red represents the enrichment of the respective gene set in the respective cell cluster. Therefore, on the same column, the unique intensity of the redness in the respective cluster (discriminatory) shows the specific enrichment of the gene set in that cluster, instead of in other clusters. UNC-bulk processing

[0136] Raw base call (BCL) files were converted to fastq files using bcl2fastq2 (v2.19.0). RefSeq assembly (GCF_000001405.40) of the human reference genome GRCh38.p14 was used as the reference for gene quantification by Salmon 1.9.051("-- gcBias -- seqBias"). The total expected read counts per gene were normalized to transcripts per million (TPM). Public bulk datasets and sample inclusion

[0137] Eleven bulk transcriptomics datasets were obtained from public sources (Table 6). Gene expression quantifications was used ‘as-is’ with respect to the original publications when possible, i.e. data were not re-aligned or re-quantified; gene-level expression estimates were used either in the unit of TPM (transcripts per million) or FPKM (fragments per kilobase per million reads), depending on the study. When preprocessed gene expression data were not available, for training datasets, the most similar methods were used to process the data; for validation and 44Patent Atty. Dkt. No.150-35-PCT independent datasets, Salmon 1.9.051using RefSeq assembly (GCF_000001405.40) of the human reference genome GRCh38.p14 was used to derive gene expression levels (Table 6). Samples from the public datasets were filtered to include only non-metastatic primary PDAC samples. For the Grünwald and Olive datasets, which are microdissected, only stroma samples were included.

[0138] Bladder cancer subtyping calls were made on log2 transformed upper-quartile normalized expression data using the BLCA subtyping and consensusMIBC R package52. Within the UROMOL and IMvigor210 datasets, all samples with gene expression data were used in the analysis. For the TCGA_BLCA cohort, only tumors from patients with stage M0 disease were included in the analysis. Over-representation analysis (ORA)

[0139] The R package (version 4.1.3) clusterProfiler (version 3.1.8) was utilized to perform Over-Representation Analysis on marker genes derived from SCISSORS, specifically targeting myCAF and iCAF markers. For the enrichment analysis of Gene Ontology (GO) terms, the "org.Hs.eg.db" was employed for genome-wide annotation, and the p-value cutoff was set at 0.05. Regarding the KEGG terms, the organism was specified as "hsa" (Homo sapiens), and the p-value cutoff was set at 0.05. Consensus clustering (CC)

[0140] SCISSORS myCAF-like and iCAF-like genes were derived as described above and ranked by fold enrichment to generate the top25 genes for each subtype. Gene sets of the Moffitt stroma, Elyada and Maurer schemas were collected from each study respectively. For each of the subtyping schemas in each of the 11 public transcriptomics datasets, unsupervised CC was applied using the ConsensusClusterPlus (version 1.56.0) package in R for genes (rows) and samples (columns) separately. Data matrices were subjected to log2 transformation and column- wise quantile normalization. Note that the data were not normalized row-wise, as that may force the clusters to have similar sizes, instead of deriving the reflective number of patients in each cluster. For clustering of samples, a distance matrix was derived based on Pearson correlation. Then CC was applied to this distance matrix to derive two sample clusters (K = 2), which consisted of 1,000 iterations of k-means clustering using Euclidean distance, with 80% items hold-out at each iteration. The number of K was determined empirically by visual inspection to derive clusters of samples that were most representative of the CAF subtypes. For clustering of genes, a distance matrix was derived based on Pearson correlation. Then CC was applied to this distance matrix derive two gene clusters (K = 2), which consisted of 200 iterations of k-means clustering using Euclidean distance, with 80% items hold-out at each iteration. Generation of CC labels for classifier training and validation 45Patent Atty. Dkt. No.150-35-PCT

[0141] To derive confident labels for classifier training and validation, the CC method mentioned above were adapted. Specifically, the CC starts at sample-wise K=2, with Ks increasing step by step for inspection of clustering performance and sample-gene associations. The resultant clusters were then labeled as “permCAF”, “Mixed permCAF”, “Mixed”, “Mixed restCAF”, “restCAF” and “Absent” based on gene expressions. A dataset does not necessarily have every one of the 6 cluster categories. “Mixed permCAF” was then merged with ”permCAF”, and “Mixed restCAF” merged with “restCAF”. These merged “permCAF” and “restCAF” labels were used for training and validation of DeCAF. DeCAF classifier training Candidate gene ranking

[0142] SCISSORS CAF genes were ranked based on the consistency of their differential expression (DE) statistics between CC-based subtypes in each individual training dataset. A cross- study DE consistency score was obtained by summing the -log10 p-values (Wilcoxon rank-sum test) and ranking them from high to low. The top 25% of this set (consistent DE genes) were considered for model training and the genes where the direction of up-regulation or down- regulation of them were not consistent in the subtypes were removed. The remaining genes then formed our final candidate gene set for downstream steps. Rationale of using kTSP for binary classification

[0143] Let us define a gene pair (^^ௗ^^, ^^ௗ^௧), where ^^ௗ^^is the expression of gene s for subject i in study d , and ^^ௗ^௧is the expression of gene t for the same subject and study. A TSP is anindicator variable based on this gene pair, ^^^^^ௗ^^ ^ ^^ௗ^௧^ െ^ ଶ , where the value represents which gene in the pair has higher expression in subject i from study d , ((^^ ଶif ^^ௗ^^ ^ ^^ௗ^௧, and െଶ if ^^ௗ^^^ ^^ௗ^௧otherwise). The TSP method was originally proposed in thcontext of binary classification. See, Leek JT. The tspair package for finding top scoring pair classifiers in R. Bioinformatics. 2009 May 1;25(9):1203-4. In traditional applications, a single TSP (k = 1) is selected out of theset of all possible gene pairs, in which case, ^^^^^ௗ^^ ^ ^^ௗ^௧^ െ^ ଶ^ 0 implies subtype A with highprobability, otherwise subtype B is implied (Leek, 2009) \. We view such binary variables as “biological switches" indicating how pairs of genes are expressed relative to clinical outcome.

[0144] In the kTSP setting, class prediction reduces to verifying whether the sum across k selected TSPs is greater than 0: ^ 1 ^^^ ^^ ^ ^^െ^ 0Patent Atty. Dkt. No.150-35-PCT

[0145] This reduces to a majority vote across the selected k TSPs, where the contribution of each of the k TSPs are equally weighted to select subtype A if the above sum is greater than 0, and subtype B otherwise. However, some TSPs may be more informative than others, so we utilized penalized logistic regression to jointly estimate the effect of each of the k selected TSPs in predicting binary subtype, and to further remove TSPs with weak or redundant effects. See, Breheny P, Huang J. Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection. The annals of applied statistics. 2011 Jan 1;5(1):232. Predicted probabilities of permCAF subtype membership (DeCAF score) may then be obtained from the fitted logistic regression model on our training samples, where values greater than 0.5 indicate predicted membership to the permCAF subtype and restCAF otherwise. We also define 0.5^ subtype probability < 0.6 as the “lean permCAF” subtype, 0.6 ^ subtype probability < 0.9 as the “likely permCAF”, and 0.9 ^ subtype probability ^ 1.0 as the “strong permCAF”, to refer to different levels of confidence of the permCAF call, in increasing order. Similarly we define 0.4 ^ subtype probability < 0.5 as the “lean restCAF” subtype, 0.1 ^ subtype probability < 0.4 as the “likely restCAF”, and 0 ^ subtype probability ^ 0.1 as the “strong restCAF”, to refer to different levels of confidence of the restCAF call, in increasing order. Horizontal data integration and kTSP selection via switchBox

[0146] To apply the top scoring pairs transformation, we utilize the switchBox R package (version 1.28.0) to enumerate all possible gene pairs based on our final candidate gene list and training samples (function SWAP.KTSP.Train, with optimal parameters featureNo=100, krange = 50, FilterFunc = NULL). See, Afsari B, Fertig EJ, Geman D, Marchionni L. switchBox: an R package for k–Top Scoring Pairs classifier development. Bioinformatics. 2015 Jan 15;31(2):273- 4. Given the large number of potential gene pairs based on this list, in addition to the strong correlation between gene pairs sharing the same genes, the switchBox package utilizes a greedy algorithm to select from this list a subset of gene pairs that are helpful for prediction, given the set of training labels. We merge data from each training dataset without normalization prior to applying switchBox, as the method only looks at the relative gene expression ranking within each sample from each study. The method then selects a subset of k TSPs, where k is determined through a greedy optimization procedure. Model training based on selected kTSPs

[0147] To remove redundant TSPs and to jointly estimate their contribution in predicting subtype in our training samples, we utilize the ncvreg R package (version 3.13.0) to fit a penalized 47Patent Atty. Dkt. No.150-35-PCT logistic regression model based upon the selected TSPs from switchBox. Our design matrix is an N x (k+1) matrix, where the first column pertains to the intercept and the remaining k columns pertains to the k selected TSPs from switchBox. Here N is the total number of training samples (Table 6). Each TSP in the design matrix is represented as a binary vector, taking on the value of 1 if gene A’s expression is greater than gene B’s expression. Our outcome variable here is binary subtype (1 = permCAF, 0 otherwise). We utilize optional parameters alpha = 0.05 and nfolds = N. We allow for correlation between TSPs by setting the ncvreg alpha parameter to 0.05 in order to shrink the coefficients of highly correlated TSPs and also remove correlated uninformative TSPs from the model. We set nfolds = N to apply leave one out cross validation in order to choose the optimal MCP penalty tuning parameter for variable selection, where the optimal tuning parameter is the one that minimizes the cross-validation error of the fitted model. Our final model then reports the set of coefficients estimated for each of the kTSPs, where each coefficient may be interpreted as the change in log odds of a patient being part of the permCAF subtype when the lth TSP is equal to 1, given the others in the model. TSPs with coefficient of 0 are those that have been removed from the model for either weak effect or redundancy with other TSPs. Final kTSP model

[0148] As illustrated in Fig. 4A, 9 pairs of kTSP genes were evaluated for their relative ranking in a new patient. A value of 1 is assigned if the permCAF gene in a TSP has greater expression than the restCAF gene in that patient (and 0 assigned otherwise) creating ^^^,^^௪, a 1 x (k +1) TSP predictor vector. These values are then multiplied by the corresponding set ofestimated TSP model coefficients, ^^^ , obtained from the fitted penalized logistic regression model.The intercept term is included to correct for estimated baseline effects. These values are summedto get the patient “DeCAF Score” ^^^,^^௪ ^^^ . This score is then converted to a predicted probabilityof belonging to the permCAF subtype by computing its inverse logit: ^^̂^,^^௪ ൌ exp൫^^^,^^௪^^^൯ / ^1 ^ exp൫^^^,^^௪^^^൯^

[0149] Values greater than or equal to 0.5 indicated predicted permCAF subtype membership, and those less than 0.5 are predicted to be of the restCAF subtype. This is equivalent todetermining whether ^^^,^^௪^^^ >0 (permCAF subtype) vs ^^^,^^௪^^^ <0 (restCAF subtype). Thus, theDeCAF score, ^^^,^^௪^^^ , may also be utilized as a continuous score for classification. Therefore,prediction in new samples, such as from our validation datasets, reduces to simply checking the relative expression of each gene within the set of TSPs. We also define 0.5^ subtype probability < 48Patent Atty. Dkt. No.150-35-PCT 0.6 as the “lean permCAF” subtype, 0.6 ^ subtype probability < 0.9 as the “likely permCAF”, and 0.9 ^ subtype probability ^ 1.0 as the “strong permCAF”, to refer to different levels of confidence of the permCAF call, in increasing order. Similarly we define 0.4 ^ subtype probability < 0.5 as the “lean restCAF” subtype, 0.1 ^ subtype probability < 0.4 as the “likely restCAF”, and 0 ^ subtype probability ^ 0.1 as the “strong restCAF”, to refer to different levels of confidence of the restCAF call, in increasing order.

[0150] For all discussions regarding classifier performance, we obtain the predicted subtypes in the manner described above. The level of confidence in the prediction can be determined basedupon the distance of ^^^,^^௪^^^ from 0.5, where values closer to 0.5 indicate lower confidence in thepredicted subtype and higher confidence otherwise. We also define 0.5^ subtype probability < 0.6 as the “lean permCAF” subtype, 0.6 ^ subtype probability < 0.9 as the “likely permCAF”, and 0.9 ^ subtype probability ^ 1.0 as the “strong permCAF”, to refer to different levels of confidence of the permCAF call, in increasing order. Similarly we define 0.4 ^ subtype probability < 0.5 as the “lean restCAF” subtype, 0.1 ^ subtype probability < 0.4 as the “likely restCAF”, and 0 ^ subtype probability ^ 0.1 as the “strong restCAF”, to refer to different levels of confidence of the restCAF call, in increasing order. Validation of DeCAF

[0151] The performance of the final DeCAF model in the training set was measured using leave-one-out cross validation. This was implemented using the cv.ncvreg function from the ncvreg (version 3.13.0). Since the outcome is binary, the cross-validation error is measured via the leave-one-out cross-validated deviance of the logistic regression model.

[0152] Next, the performance of the DeCAF model was evaluated in the validation sets. The validation set is composed of seven separate studies. To account for the variability between studies, a fully non-parametric ROC curve was used for this meta-analysis. The ROC curve was constructed and the inter-study variability was measured using the study random-effects model53 and implemented in the metaROC function from the nsROC R package (version 1.1). All validation metrics compared the DeCAF classifier to the combined "Mixed permCAF” and “permCAF” calls and combined “Mixed restCAF” and “restCAF” clustering calls. Survival analysis

[0153] For pooled survival analysis, patients with subtype calls, OS time and event were involved. For the Linehan dataset, where patients received treatments, only pre-treatment samples were included when both pre-treatment and post-treatment samples were available. For samples 49Patent Atty. Dkt. No.150-35-PCT that are duplicated in the PACA_AU_seq and PACA_AU_array datasets, only the sample from PACA_AU_seq was used for survival analysis.

[0154] Overall survival estimates were calculated using the Kaplan-Meier method. Association between overall survival and individual covariates such as subtype were evaluated via the cox proportional hazards models using the coxph function from the ‘survival’ R package (version 3.2-13), where a given subtyping schema was considered as a multi-level categorical predictor. The log-rank test was used to evaluate overall association of a subtyping schema with overall survival and derive the p-values. In the pooled analyses, a stratified cox proportional hazards model was utilized, where dataset of origin was used as a stratification factor to account for variation in baseline hazard across studies. CIBERSORT

[0155] The analytical tool CIBERSORT was employed to estimate the percentage of cell types for each sample of 12 bulk transcriptomics data. This estimation was performed using the LM22 signature matrix, which encompasses 547 genes that distinguish 22 human hematopoietic cell phenotypes. With the percentage results obtained from CIBERSORT, we compared the results across two types of DeCAF calls for the samples in each dataset. The Wilcoxon rank-sum test was employed to assess whether there were significant differences. The log2 fold change of the median was utilized to quantify the magnitude of the observed differences. 6. REFERENCES 1. Elahi-Gedwillo, K. Y., Carlson, M., Zettervall, J. & Provenzano, P. P. Antifibrotic Therapy Disrupts Stromal Barriers and Modulates the Immune Landscape in Pancreatic Ductal Adenocarcinoma. Cancer Research 79, 372–386 (2019). 2. Lee, J. J. et al. Stromal response to Hedgehog signaling restrains pancreatic cancer progression. 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[0156] It should be understood that the above description is only representative of illustrative embodiments and examples. For the convenience of the reader, the above description has focused on a limited number of representative examples of all possible embodiments, examples that teach the principles of the disclosure. The description has not attempted to exhaustively enumerate all possible variations or even combinations of those variations described. That alternate embodiments may not have been presented for a specific portion of the disclosure, or that further undescribed alternate embodiments may be available for a portion, is not to be considered a disclaimer of those alternate embodiments. One of ordinary skill will appreciate that many of those undescribed embodiments, involve differences in technology and materials rather than differences in the application of the principles of the disclosure. Accordingly, the disclosure is not intended to be limited to less than the scope set forth in the following claims and equivalents. INCORPORATION BY REFERENCE

[0157] All references, articles, publications, patents, patent publications, and patent applications cited herein are incorporated by reference in their entireties for all purposes. However, mention of any reference, article, publication, patent, patent publication, and patent application cited herein is not, and should not be taken as an acknowledgment or any form of suggestion that they constitute valid prior art or form part of the common general knowledge in any country in the world. It is to be understood that, while the disclosure has been described in conjunction with the detailed description, thereof, the foregoing description is intended to illustrate and not limit the scope. Other aspects, advantages, and modifications are within the scope of the claims set forth below. All publications, patents, and patent applications cited in this specification are herein incorporated by reference as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. COMPUTER PROGRAM 53Patent Atty. Dkt. No.150-35-PCT DeCAF data and script DeCAF TSP genes classifier$TSPs ## [,1] [,2] ## [1,] "IGFL2" "CHRDL1" ## [2,] "NOX4" "OGN" ## [3,] "VSNL1" "PI16" ## [4,] "BICD1" "ANK2" ## [5,] "NPR3" "ABCA8" ## [6,] "ETV1" "TGFBR3" ## [7,] "ITGA11" "FBLN5" ## [8,] "CNIH3" "SCARA5" ## [9,] "COL11A1" "KIAA1217" DeCAF parameters classifier$fit$beta ## 0.1062 ## (Intercept) -8.3790291 ## indmat11.9399809 ## indmat22.2970861 ## indmat30.7868817 ## indmat41.4660046 ## indmat51.2197586 ## indmat61.6365770 ## indmat71.5563258 ## indmat81.8657202 ## indmat92.3576040 Main function to call DeCAF apply_decaf = function(data, classifier){ # "data": a dataframe with unique official gene symbols as rownames # "classifier": the DeCAF classifier containing essential objects as shown above 1 ## Extract Gene Games genes = rownames(data) ## Extract Classifier fit = classifier$fit if(is.null(fit$beta)) "Classifier Does Not Have Coefficients Assigned to beta" ## Keep only gene info for genes in classifier data1 = data[genes %in% classifier$TSPs,] rnames = rownames(data1) data1 = matrix(as.numeric(as.matrix(data1)), ncol = ncol(data1)) rownames(data1) = rnames if(nrow(data1) != length(unique(classifier$TSPs))){ print(classifier$TSPs[!classifier$TSPs %in% genes]) stop("genes missing") } ## See which of gene pair has higher expression indmat = matrix(-1, ncol(data1), nrow(classifier$TSPs)) for(i in 1:nrow(classifier$TSPs)){ p1 = which(rownames(data1) == classifier$TSPs[i,1]) p2 = which(rownames(data1) == classifier$TSPs[i,2]) indmat[,i] = (data1[p1,] > data1[p2,])ˆ2 } ## Calculate probability of permCAF X=cbind(rep(1, nrow(indmat)), indmat) trainingPrediction = exp(X%*%c(fit$beta)) / (1+exp(X%*%c(fit$beta))) 54Patent Atty. Dkt. No.150-35-PCT ## Obtain DeCAF subtype classification = c("restCAF","permCAF")[(trainingPrediction >= 0.5)ˆ2 + 1] ## Obtain Grade of DeCAF Subtype guess = rep(1, length(trainingPrediction)) guess[trainingPrediction < .1] = "Strong restCAF" guess[trainingPrediction >= .1 & trainingPrediction < .4] = "Likely restCAF" guess[trainingPrediction >= .4 & trainingPrediction < .5] = "Lean restCAF" guess[trainingPrediction >= .5 & trainingPrediction < .6] = "Lean permCAF" guess[trainingPrediction >= .6 & trainingPrediction < .9] = "Likely permCAF" guess[trainingPrediction >= .9 ] = "Strong permCAF" ## Put results together into dataframe final = data.frame(DeCAF_prob = trainingPrediction, DeCAF = classification, DeCAF_graded = guess) rownames(final) = make.names(colnames(data), unique = any(table(colnames(data)) > 1)) return(final) } TABLES TABLE 1 Approved kinase inhibitors Drug Class Biomarker Intended Target(s) Indication Abemaciclib SmallPatent Atty. Dkt. No.150-35-PCT Drug Class Biomarker Intended Target(s) Indication Axitinib Small VEGFR-1, VEGFR-2, and INLYTA® m l l VEGFR 32ndline RCCPatent Atty. Dkt. No.150-35-PCT Drug Class Biomarker Intended Target(s) Indication Erdafitinib Small FGFR2 or FGFR2 FGFR1, FGFR2, FGFR3, Adv. urothelial BAL ER A™ l l l i F FR4 i D e,57Patent Atty. Dkt. No.150-35-PCT Drug Class Biomarker Intended Target(s) Indication Melanoma, met Ni l b SLCC RCC SCC er v , , o C58Patent Atty. Dkt. No.150-35-PCT Drug Class Biomarker Intended Target(s) Indication Sirolimus (RAPAMUNE® Small mTOR Transplant , al,Table 2 Examples of clinical trials targeting the ECMp Agent Targets Study population PEGPH20 + modified FOLFIRINOX HA + chemotherapy Metastatic pancreatic cancer PEGPH20 + nab-Paclitaxel + Gemcitabine HA + chemotherapy Hyaluronan-high IV untreated PDAC Vismodegib + Gemcitabine Shh pathway + Advance pancreatic 59Patent Atty. Dkt. No.150-35-PCT chemotherapy cancer Vismodegib + Gemcitabine + nab-Paclitaxel Shh pathway + Metastatic pancreatic chemotherapy cancer Vismodegib + Gemcitabine Shh pathway + Recurrent or met. chemotherapy pancreatic cancer IPI-926 + FOLFIRINOX Shh pathway + Advance pancreatic chemotherapy cancer AT13148 muti-AGC kinases incl Advance solid tumors ROCK.-AKT Paricalcitol + Nivolumab + nab-Paclitaxel + Vitamin D Receptor + PD- Resectable pancreatic Gemcitabine L1 + chemo cancer Paricalcitol + Gemcitabine + nab-Paclitaxel Vitamin D Receptor + Advance pancreatic chemotherapy cancer Paricalcitol + Hydroxychloroquine + Vitamin D Receptor + Advance or met. Gemcitabine + nab-Paclitaxel autophagy + chemotherapy pancreatic cancer Paricalcitol + Pembrolizumab Vitamin D Receptor + PD-1 Pancreatic cancer (maintenance) Paricalcitol + Pembrolizumab + Gemcitabine Vitamin D Receptor + PD-1 Resectable pancreatic + nab-Paclitaxel + chemotherapy cancer Paricalcitol + nab-Paclitaxel + Gemcitabine Vitamin D Receptor + Resectable pancreatic chemotherapy cancer Paricalcitol + nab-Paclitaxel + Gemcitabine Vitamin D Receptor + Advance pancreatic + Cisplatin chemotherapy cancer Paricalcitol + nab-Paclitaxel + Gemcitabine Vitamin D Receptor Metastatic pancreatic + Cisplatin cancer Paricalcitol + Nivolumab + nab-Paclitaxel + Vitamin D Receptor + PD- Metastatic pancreatic Gemcitabine + Cisplatin L1 + chemotherapy cancer LY3022859 TβRII Advance solid tumors PF-03446962 TβRI Advance solid tumors Bintrafusp alfa TβRII + PD-L1 Advance solid tumors Galunisertib TβRI Advance solid tumors Galunisertib + Gemcitabine TβRI + chemotherapy Inoperable or met. pancreatic cancer Galunisertib + Gemcitabine TβRI + chemotherapy Inoperable or met. pancreatic cancer Galunisertib + Durvalumab TβRI + PD-L1 Metastatic pancreatic cancer SAR438459 + Cemiplimab TGFβ1, TGFβ2, and TGFβ Advance solid tumors + PD-L1 RAS+PD- Borderline / Locally Losartan+Nivolumab+FOLFIRINOX+SBRT L1+chemotherapy+radiation Advanced TABLE 3 SCISSORS CAF GENES p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype genePatent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 1.230E-19 0.791 0.302 0.005 1.928E-15 myCAF-like permCAF COL11A1 1 N 5Patent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 1.763E-08 0.198 0.14 0.005 2.763E-04 myCAF-like permCAF RNF152 L 2 3 L1 162Patent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 1.276E-06 0.199 0.191 0.055 1.999E-02 myCAF-like permCAF SPRYD7 1 2 2Patent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 1.077E-52 0.759 0.41 0.038 1.687E-48 iCAF-like restCAF C16orf89 L 1 1Patent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 4.025E-25 0.483 0.338 0.075 6.306E-21 iCAF-like restCAF NAF1 1 4 3Patent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 4.419E-14 0.376 0.349 0.131 6.924E-10 iCAF-like restCAF NEGR1 5 2 L LPatent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 6.423E-09 0.136 0.108 0.021 1.006E-04 iCAF-like restCAF NOP2 3 0 1 G .67Patent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 1.925E-140 1.454 0.609 0 3.016E-136 apCAF-like MYOT. .Patent Atty. Dkt. No.150-35-PCT p_val avg_log2FC pct.1 pct.2 p_val_adj cluster subtype gene 5.431E-15 0.705 0.217 0.012 8.509E-11 apCAF-like SLITRK6A. L .26Table 4 ORA_SCISSORS_CAF_GENES (Part 1 / 2) Gene t 469Patent Atty. Dkt. No.150-35-PCT Gene ID Rati oBgRatio pvalue p.adjust qvalue Ct6 9 8 0 3 6 0 6 6 8 1 7 7 9 6 9 4 7 7 7 0 8 6 8 7 5 3 4 4 7 3 5 7 7 9Patent Atty. Dkt. No.150-35-PCT Gene ID Rati oBgRatio pvalue p.adjust qvalue Ct4 9 9 6 6 6 6 6 6 0 8 4 4 6 3 7 7 3 5 4 5 3 4 7 4 4 7 5 6 5 6 3 3 7 5Patent Atty. Dkt. No.150-35-PCT Gene ID Rati oBgRatio pvalue p.adjust qvalue Ct3 5 7 4 8 3 9 3 6 6 4 5 6 5 5 3 3 3 8 4 4 4 4 5 5 7 3 3 4 6 5 5 8 3 7Patent Atty. Dkt. No.150-35-PCT Gene ID Rati oBgRatio pvalue p.adjust qvalue Ct8 5 4 8 6 2 2 2 7 5 5 4 7 4 4 4 5 3 6 4 2 2 2 2 2 2 3 4 4 3 3 4 4 4 5Patent Atty. Dkt. No.150-35-PCT Gene ID Rati oBgRatio pvalue p.adjust qvalue Ct4 4 4 2 2 2 4 6 7 6 3 3 5 4 3 2 3 7 4 8 3 3 5 8 4 8 5 4 7 3 4 5 2 2 2Patent Atty. Dkt. No.150-35-PCT Gene ID Rati oBgRatio pvalue p.adjust qvalue Ct2 2 2 2 2 4 4 3 3 3 5 8 7 2 2 2 4 4 4 4 3 5 4 5 3 3 5 2 4 3 5 3 3 4 4Patent Atty. Dkt. No.150-35-PCT Gene ID Rati oBgRatio pvalue p.adjust qvalue Ct2 2 2 2 2 2 5 6 5 4 2 2 2 4 2 2 2 3 3 3 3 4 6 3 2 2 2 3 4 6 6 4 3 2 2Patent Atty. Dkt. No.150-35-PCT Gene ID Rati oBgRatio pvalue p.adjust qvalue Ct2 2 2 2 2 5 6 4 5 4 3 3 5 2 2 2 3 8esc p o ge e COL11A1 / WNT5A / HOXB5 / RBP4 / TBX3 / HOXB6 / HAN embryonic organ D2 / MICAL2 / DLL1 / HOXB4 / RARB / BMP4 / CLUAP1 / FO GO:0048562 morphogenesis XF2 COL11A1 / PDGFC / WNT5A / HOXB5 / RBP4 / TBX3 / HOX embryonic organ B6 / HAND2 / MICAL2 / DLL1 / HOXB4 / PTCH1 / RARB / B GO:0048568 development MP4 / CLUAP1 / FOXF2 embryonic skeletal COL11A1 / WNT5A / KIAA1217 / HOXB5 / RBP4 / HOXB6 / GO:0048706 system development HAND2 / HOXB4 / BMP4 specification of GREM1 / WNT5A / TBX3 / HAND2 / MICAL2 / DLL1 / BMP GO:0009799 symmetry 4 / CLUAP1 COL11A1 / WNT5A / RBP4 / TBX3 / HAND2 / MICAL2 / DL GO:0003007 heart morphogenesis L1 / PTCH1 / BMP4 / CLUAP1 pattern specification GREM1 / WNT5A / HOXB5 / TBX3 / HOXB6 / HAND2 / MIC GO:0007389 process AL2 / DLL1 / HOXB4 / NKD1 / PTCH1 / BMP4 / CLUAP1 GO:0001947 heart looping WNT5A / TBX3 / HAND2 / MICAL2 / DLL1 / CLUAP1 sensory organ COL11A1 / COL8A1 / WNT5A / RBP4 / TBX3 / DLL1 / NKD1 GO:0090596 morphogenesis / RARB / BMP4 / FOXF2 GO:0061371determination of heartWNT5A / TBX3 / HAND2 / MICAL2 / DLL1 / CLUAP177Patent Atty. Dkt. No.150-35-PCT ID Description geneID left / right asymmetry embryonic heart tube GO:0003143 morphogenesis WNT5A / TBX3 / HAND2 / MICAL2 / DLL1 / CLUAP1 COL8A1 / WNT5A / RBP4 / DLL1 / NKD1 / RARB / BMP4 / F GO:0048592 eye morphogenesis OXF2 GREM1 / WNT5A / HOXB5 / TBX3 / HOXB6 / DLL1 / HOXB GO:0003002 regionalization 4 / NKD1 / PTCH1 / BMP4 / CLUAP1 embryonic limb GO:0030326 morphogenesis GREM1 / WNT5A / TBX3 / HAND2 / PTCH1 / RARB / BMP4 embryonic appendage GO:0035113 morphogenesis GREM1 / WNT5A / TBX3 / HAND2 / PTCH1 / RARB / BMP4 cardiac muscle tissue GREM1 / COL11A1 / WNT5A / RBP4 / TBX3 / NOX4 / DLL1 / GO:0048738 development RARB / BMP4 embryonic heart tube GO:0035050 development WNT5A / TBX3 / HAND2 / MICAL2 / DLL1 / CLUAP1 striated muscle tissue GREM1 / COL11A1 / WNT5A / RBP4 / TBX3 / NOX4 / DLL1 / GO:0014706 development RARB / BMP4 negative regulation of chondrocyte GO:0032331 differentiation GREM1 / ADAMTS12 / RARB / BMP4 determination of GREM1 / WNT5A / TBX3 / HAND2 / MICAL2 / DLL1 / CLU GO:0009855 bilateral symmetry AP1 appendage GO:0035107 morphogenesis GREM1 / WNT5A / TBX3 / HAND2 / PTCH1 / RARB / BMP4 GO:0035108 limb morphogenesis GREM1 / WNT5A / TBX3 / HAND2 / PTCH1 / RARB / BMP4 epithelial tube GREM1 / ADAMTS12 / WNT5A / TBX3 / HAND2 / MICAL2 A D1 / Patent Atty. Dkt. No.150-35-PCT ID Description geneID negative regulation of GREM1 / WNT5A / SHISA2 / NKD2 / APCDD1 / NKD1 / DA GO:0030178 Wnt signaling pathway CT1 norepinephrine GO:0042415 metabolic process MOXD1 / HAND2 / RNF180 regulation of cartilage GO:0061035 development GREM1 / ADAMTS12 / WNT5A / RARB / BMP4 appendage GO:0048736 development GREM1 / WNT5A / TBX3 / HAND2 / PTCH1 / RARB / BMP4 GO:0060173 limb development GREM1 / WNT5A / TBX3 / HAND2 / PTCH1 / RARB / BMP4 extracellular matrix COL10A1 / GREM1 / COL11A1 / ADAMTS12 / MATN3 / C / C / C L1 / A 14Patent Atty. Dkt. No.150-35-PCT ID Description geneID protein catabolic 4A process regulation of cell proliferation involved in heart GO:2000136 morphogenesis TBX3 / HAND2 / BMP4 embryonic skeletal GO:0048704 system morphogenesis COL11A1 / HOXB5 / HOXB6 / HOXB4 / BMP4 columnar / cuboidal epithelial cell GO:0002066 development WNT5A / DLL1 / RARB / BMP4 GO:0009798 axis specification WNT5A / TBX3 / DLL1 / PTCH1 / BMP4 cell proliferation involved in heart GO:0061323 morphogenesis TBX3 / HAND2 / BMP4 positive regulation of receptor-mediated GO:0048260 endocytosis GREM1 / BICD1 / WASL / HIP1 skeletal system GREM1 / COL11A1 / HOXB5 / HOXB6 / HOXB4 / RARB / B GO:0048705 morphogenesis MP4 regulation of chondrocyte GO:0032330 differentiation GREM1 / ADAMTS12 / RARB / BMP4 embryonic digit GO:0042733 morphogenesis WNT5A / TBX3 / HAND2 / BMP4 GREM1 / PDGFC / ADAMTS12 / HOXB4 / TNFSF11 / RAR GO:0060348 bone development B / BMP4 GO:0035282 segmentation WNT5A / TBX3 / DLL1 / NKD1 / BMP4 cardiac chamber GO:0003205 development COL11A1 / WNT5A / RBP4 / TBX3 / HAND2 / BMP4 response to retinoic GO:0032526 acid WNT5A / RBP4 / HAND2 / EPHA3 / PTCH1 epithelial to mesenchymal GO:0001837 transition GREM1 / WNT5A / TBX3 / EPHA3 / BMP4 / FOXF2 type B pancreatic cell GO:0003323 development WNT5A / DLL1 / BMP4 negative regulation of myoblast GO:0045662 differentiation TBX3 / DLL1 / BMP4 negative regulation of GO:0045926 growth GREM1 / WNT5A / RBP4 / NKD1 / ING4 / PTCH1 / BMP4 chondrocyte GO:0002062 differentiation GREM1 / COL11A1 / ADAMTS12 / RARB / BMP4 80Patent Atty. Dkt. No.150-35-PCT ID Description geneID regulation of non- canonical Wnt GO:2000050 signaling pathway WNT5A / NKD1 / DACT1 negative regulation of GO:0048640 developmental growth WNT5A / RBP4 / NKD1 / PTCH1 / BMP4 mesenchymal cell GREM1 / WNT5A / TBX3 / HAND2 / EPHA3 / BMP4 / FOXF GO:0048762 differentiation 2 collagen fibril GO:0030199 organization GREM1 / COL11A1 / ADAMTS12 / ADAMTS2 regulation of Wnt GREM1 / WNT5A / SHISA2 / SPIN1 / NKD2 / APCDD1 / NK GO:0030111 signaling pathway D1 / DACT1 GO:0003401 axis elongation WNT5A / NKD1 / BMP4 GREM1 / COL11A1 / ADAMTS12 / WNT5A / HAND2 / ITG GO:0001503 Ossification A11 / TNFSF11 / PTCH1 / BMP4 embryonic hindlimb GO:0035116 morphogenesis TBX3 / RARB / BMP4 regulation of MAP GO:0043405 kinase activity PDGFC / WNT5A / NOX4 / TRIB2 / TNFSF11 / BMP4 WNT5A / RBP4 / ADAMTS2 / ADAMTSL2 / NKIRAS2 / BM GO:0030324 lung development P4 mammary gland epithelium GO:0061180 development WNT5A / TBX3 / TNFSF11 / PTCH1 GO:0072089 stem cell proliferation WNT5A / TBX3 / HOXB4 / PTCH1 / RARB respiratory tube WNT5A / RBP4 / ADAMTS2 / ADAMTSL2 / NKIRAS2 / BM GO:0030323 development P4 cardiac ventricle GO:0003231 development COL11A1 / WNT5A / TBX3 / HAND2 / BMP4 embryonic epithelial GO:0001838 tube formation GREM1 / WNT5A / PTCH1 / BMP4 / CLUAP1 type B pancreatic cell GO:0003309 differentiation WNT5A / DLL1 / BMP4 mammary gland duct GO:0060603 morphogenesis WNT5A / TBX3 / PTCH1 cell surface receptor signaling pathway involved in heart GO:0061311 development WNT5A / HAND2 / BMP4 regulation of protein WNT5A / NKD2 / TRIB2 / NKD1 / DACT1 / RNF180 / FOXF2 GO:0042176 catabolic process / RNF144A glandular epithelial GO:0002067 cell differentiation WNT5A / DLL1 / RARB / BMP4 establishment of GO:0001736 planar polarity WNT5A / NKD1 / DACT1 / FOXF2 81Patent Atty. 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No.150-35-PCT ID Description geneID establishment of tissue GO:0007164 polarity WNT5A / NKD1 / DACT1 / FOXF2 embryonic pattern GO:0009880 specification WNT5A / TBX3 / DLL1 / PTCH1 mammary gland GO:0030879 development WNT5A / TBX3 / TNFSF11 / PTCH1 / BMP4 epithelial tube GO:0072175 formation GREM1 / WNT5A / PTCH1 / BMP4 / CLUAP1 GO:0046879 hormone secretion ANO1 / RBP4 / SCG5 / TBX3 / VSNL1 / IRS1 / TNFSF11 embryonic eye GO:0048048 morphogenesis WNT5A / RARB / FOXF2 GO:0060914 heart formation WNT5A / HAND2 / BMP4 outflow tract GO:0003151 morphogenesis WNT5A / TBX3 / HAND2 / BMP4 respiratory system WNT5A / RBP4 / ADAMTS2 / ADAMTSL2 / NKIRAS2 / BM GO:0060541 development P4 regulation of proteasomal ubiquitin- dependent protein GO:0032434 catabolic process NKD2 / TRIB2 / RNF180 / FOXF2 / RNF144A negative regulation of canonical Wnt GO:0090090 signaling pathway GREM1 / WNT5A / NKD2 / NKD1 / DACT1 COL8A1 / WNT5A / RBP4 / DLL1 / NKD1 / RARB / BMP4 / F GO:0001654 eye development OXF2 enteroendocrine cell GO:0035883 differentiation WNT5A / DLL1 / BMP4 GO:0009914 hormone transport ANO1 / RBP4 / SCG5 / TBX3 / VSNL1 / IRS1 / TNFSF11 visual system COL8A1 / WNT5A / RBP4 / DLL1 / NKD1 / RARB / BMP4 / F GO:0150063 development OXF2 kidney epithelium GO:0072073 development GREM1 / DLL1 / PTCH1 / RARB / BMP4 GO:0061053 somite development WNT5A / DLL1 / NKD1 / PTCH1 sensory system COL8A1 / WNT5A / RBP4 / DLL1 / NKD1 / RARB / BMP4 / F GO:0048880 development OXF2 positive regulation of ERK1 and ERK2 GO:0070374 cascade PDGFC / HAND2 / NOX4 / GPBAR1 / TNFSF11 / BMP4 GO:0003129 heart induction WNT5A / BMP4 cardiac neural crest cell migration involved in outflow GO:0003253 tract morphogenesis HAND2 / BMP4 82Patent Atty. 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No.150-35-PCT ID Description geneID GO:0060068 vagina development WNT5A / RBP4 mesenchyme GREM1 / WNT5A / TBX3 / HAND2 / EPHA3 / BMP4 / FOXF GO:0060485 development 2 morphogenesis of GO:0016331 embryonic epithelium GREM1 / WNT5A / PTCH1 / BMP4 / CLUAP1 GO:0035148 tube formation GREM1 / WNT5A / PTCH1 / BMP4 / CLUAP1 roof of mouth GO:0060021 development WNT5A / TBX3 / HAND2 / FOXF2 renal system GO:0072001 development GREM1 / WNT5A / RBP4 / DLL1 / PTCH1 / RARB / BMP4 GO:0001843 neural tube closure WNT5A / PTCH1 / BMP4 / CLUAP1 regulation of stem cell GO:0072091 proliferation WNT5A / TBX3 / PTCH1 / RARB positive regulation of peptide hormone GO:0090277 secretion ANO1 / RBP4 / VSNL1 / TNFSF11 branching morphogenesis of an GO:0048754 epithelial tube GREM1 / WNT5A / TBX3 / PTCH1 / BMP4 mesenchymal cell GO:0010463 proliferation WNT5A / HAND2 / BMP4 regulation of hormone GO:0046883 secretion ANO1 / RBP4 / SCG5 / VSNL1 / IRS1 / TNFSF11 GO:0060606 tube closure WNT5A / PTCH1 / BMP4 / CLUAP1 secondary heart field GO:0003139 specification WNT5A / BMP4 regulation of odontogenesis of dentin-containing GO:0042487 tooth APCDD1 / BMP4 GO:0060433 bronchus development ADAMTSL2 / BMP4 lateral sprouting from GO:0060601 an epithelium WNT5A / BMP4 metanephric collecting GO:0072205 duct development PTCH1 / BMP4 regulation of heart GO:2000826 morphogenesis WNT5A / BMP4 ventricular septum GO:0060412 morphogenesis WNT5A / TBX3 / BMP4 positive regulation of GO:0002793 peptide secretion ANO1 / RBP4 / VSNL1 / TNFSF11 positive regulation of GO:0032436 proteasomal ubiquitin- dependent proteinNKD2 / TRIB2 / RNF180 / RNF144A83Patent Atty. 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No.150-35-PCT ID Description geneID catabolic process embryonic axis GO:0000578 specification WNT5A / TBX3 / PTCH1 GO:0001709 cell fate determination DLL1 / PTCH1 / BMP4 morphogenesis of a GO:0001738 polarized epithelium WNT5A / NKD1 / DACT1 / FOXF2 nephron tubule GO:0072080 development GREM1 / DLL1 / PTCH1 / BMP4 ureteric bud GO:0001657 development GREM1 / PTCH1 / RARB / BMP4 neural tube GO:0021915 development WNT5A / PTCH1 / DACT1 / BMP4 / CLUAP1 primary neural tube GO:0014020 formation WNT5A / PTCH1 / BMP4 / CLUAP1 mesonephric epithelium GO:0072163 development GREM1 / PTCH1 / RARB / BMP4 mesonephric tubule GO:0072164 development GREM1 / PTCH1 / RARB / BMP4 sinoatrial node GO:0003163 development TBX3 / BMP4 mesenchymal to epithelial transition involved in metanephros GO:0003337 morphogenesis GREM1 / BMP4 cardiac neural crest cell development involved in outflow GO:0061309 tract morphogenesis HAND2 / BMP4 renal tubule GO:0061326 development GREM1 / DLL1 / PTCH1 / BMP4 GO:0042593 glucose homeostasis ANO1 / RBP4 / VSNL1 / NOX4 / IRS1 / PTCH1 regulation of cellular response to growth GREM1 / ADAMTS12 / WNT5A / SHISA2 / ADAMTSL2 / D GO:0090287 factor stimulus LL1 / BMP4 carbohydrate GO:0033500 homeostasis ANO1 / RBP4 / VSNL1 / NOX4 / IRS1 / PTCH1 endocrine pancreas GO:0031018 development WNT5A / DLL1 / BMP4 clathrin-dependent GO:0072583 endocytosis WASL / DLL1 / HIP1 regulation of ubiquitin-dependent GO:2000058protein catabolicNKD2 / TRIB2 / RNF180 / FOXF2 / RNF144A84Patent Atty. 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No.150-35-PCT ID Description geneID process mesonephros GREM1 / PTCH1 / RARB / BMP4compound GO:0046189 biosynthetic process WNT5A / MOXD1 / HAND2 regulation of thymocyte apoptotic GO:0070243 process WNT5A / BMP4 digestive tract GO:0048546 morphogenesis WNT5A / DACT1 / BMP4 muscle organ GO:0007517 development COL11A1 / WNT5A / ETV1 / ITGA11 / DLL1 / TCF12 / BMP4 GO:0001841 neural tube formation WNT5A / PTCH1 / BMP4 / CLUAP1 positive regulation of WNT5A / ANO1 / RBP4 / BICD1 / VSNL1 / NKD2 / CROCC / E GO:1903829 protein localization PHA3 prostate gland GO:0030850 development WNT5A / PTCH1 / BMP4 regulation of morphogenesis of a GO:0060688 branching structure GREM1 / WNT5A / BMP4 regulation of peptide GO:0090276 hormone secretion ANO1 / RBP4 / VSNL1 / IRS1 / TNFSF11 GREM1 / WNT5A / SHISA2 / SPIN1 / NKD2 / APCDD1 / NK GO:0016055 Wnt signaling pathway D1 / DACT1 GO:0001708 cell fate specification WNT5A / TBX3 / DLL1 / PTCH1 cell-cell signaling by GREM1 / WNT5A / SHISA2 / SPIN1 / NKD2 / APCDD1 / NK GO:0198738 wnt D1 / DACT1 regulation of peptide GO:0002791 secretion ANO1 / RBP4 / VSNL1 / IRS1 / TNFSF11 positive regulation of ubiquitin-dependent protein catabolic GO:2000060 process NKD2 / TRIB2 / RNF180 / RNF144A urogenital system GO:0001655 development GREM1 / WNT5A / RBP4 / DLL1 / PTCH1 / RARB / BMP4 Wnt signaling pathway, planar cell GO:0060071 polarity pathway WNT5A / NKD1 / DACT1 phenol-containing compound metabolic GO:0018958 process WNT5A / MOXD1 / HAND2 / RNF180 regulation of peptide GO:0090087 transport ANO1 / RBP4 / VSNL1 / IRS1 / TNFSF11 85Patent Atty. 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No.150-35-PCT ID Description geneID peripheral nervous system neuron GO:0048934 differentiation ETV1 / HAND2 peripheral nervous system neuron GO:0048935 development ETV1 / HAND2 GO:0060026 convergent extension WNT5A / NKD1 morphogenesis of an GO:0060572 epithelial bud WNT5A / BMP4 cardiac neural crest cell differentiation involved in heart GO:0061307 development HAND2 / BMP4 cardiac neural crest cell development involved in heart GO:0061308 development HAND2 / BMP4 metanephric renal GO:0072283 vesicle morphogenesis GREM1 / BMP4 positive regulation of non-canonical Wnt GO:2000052 signaling pathway WNT5A / NKD1 myoblast GO:0045445 differentiation GREM1 / TBX3 / DLL1 / BMP4 regulation of receptor- GO:0048259 mediated endocytosis GREM1 / BICD1 / WASL / HIP1 catecholamine GO:0006584 metabolic process MOXD1 / HAND2 / RNF180 catechol-containing compound metabolic GO:0009712 process MOXD1 / HAND2 / RNF180 negative regulation of osteoblast GO:0045668 differentiation GREM1 / HAND2 / PTCH1 morphogenesis of a GO:0061138 branching epithelium GREM1 / WNT5A / TBX3 / PTCH1 / BMP4 ANO1 / RBP4 / SCG5 / TBX3 / VSNL1 / IRS1 / TNFSF11 / APB GO:0023061 signal release A2 GREM1 / ADAMTS12 / COL8A1 / EDIL3 / SPOCK1 / ITGA1 GO:0031589 cell-substrate adhesion 1 / EPHA3 establishment of planar polarity of GO:0042249 embryonic epithelium WNT5A / FOXF2 collecting duct GO:0072044 development PTCH1 / BMP4 86Patent Atty. 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No.150-35-PCT ID Description geneID regulation of Wnt signaling pathway, planar cell polarity GO:2000095 pathway NKD1 / DACT1 columnar / cuboidal epithelial cell GO:0002065 differentiation WNT5A / DLL1 / RARB / BMP4 nephron epithelium GO:0072009 development GREM1 / DLL1 / PTCH1 / BMP4 amine metabolic GO:0009308 process MOXD1 / HAND2 / ALDH7A1 / RNF180 positive regulation of GO:0043406 MAP kinase activity PDGFC / WNT5A / NOX4 / TNFSF11 regulation of establishment of GO:0090175 planar polarity WNT5A / NKD1 / DACT1 GO:0048839 inner ear development COL11A1 / WNT5A / TBX3 / DLL1 / BMP4 positive regulation of proteasomal protein GO:1901800 catabolic process NKD2 / TRIB2 / RNF180 / RNF144A regulation of proteasomal protein GO:0061136 catabolic process NKD2 / TRIB2 / RNF180 / FOXF2 / RNF144A anterior / posterior axis GO:0009948 specification WNT5A / TBX3 / BMP4 cell differentiation involved in kidney GO:0061005 development GREM1 / PTCH1 / BMP4 regulation of stress- activated MAPK GO:0032872 cascade WNT5A / HAND2 / TNFSF11 / DACT1 / BMP4 regulation of GO:0042481 odontogenesis APCDD1 / BMP4 negative regulation of cellular response to GO:0090288 growth factor stimulus GREM1 / ADAMTS12 / WNT5A / SHISA2 regulation of epidermal cell GO:0045604 differentiation DLL1 / PTCH1 / BMP4 regulation of stress- activated protein kinase signaling GO:0070302 cascade WNT5A / HAND2 / TNFSF11 / DACT1 / BMP4 branching involved in ureteric bud GO:0001658 morphogenesis GREM1 / PTCH1 / BMP4 87Patent Atty. 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No.150-35-PCT ID Description geneID negative regulation of GO:0045599 fat cell differentiation WNT5A / RUNX1T1 / TRIB2 GO:0022612 gland morphogenesis WNT5A / TBX3 / PTCH1 / BMP4 positive regulation of GO:0046887 hormone secretion ANO1 / RBP4 / VSNL1 / TNFSF11 heart field GO:0003128 specification WNT5A / BMP4 morphogenesis of an GO:0003159 endothelium ADAMTS12 / BMP4 cellular biogenic amine catabolic GO:0042402 process MOXD1 / ALDH7A1 branch elongation of GO:0060602 an epithelium WNT5A / BMP4 endothelial tube GO:0061154 morphogenesis ADAMTS12 / BMP4 renal vesicle GO:0072077 morphogenesis GREM1 / BMP4 morphogenesis of a GO:0001763 branching structure GREM1 / WNT5A / TBX3 / PTCH1 / BMP4 striated muscle cell GO:0051146 differentiation GREM1 / TBX3 / NOX4 / DLL1 / RARB / BMP4 regulation of cell GO:1901888 junction assembly GREM1 / WNT5A / EPHA3 / GPBAR1 / SYNDIG1 formation of primary GO:0001704 germ layer COL11A1 / COL8A1 / WNT5A / BMP4 pericardium GO:0060039 development WNT5A / HAND2 thymocyte apoptotic GO:0070242 process WNT5A / BMP4 renal vesicle GO:0072087 development GREM1 / BMP4 positive regulation of stress-activated MAPK GO:0032874 cascade WNT5A / HAND2 / TNFSF11 / BMP4 activation of transmembrane receptor protein GO:0007171 tyrosine kinase activity GREM1 / PDGFC amine catabolic GO:0009310 process MOXD1 / ALDH7A1 mesenchymal to GO:0060231 epithelial transition GREM1 / BMP4 GO:0001756 Somitogenesis WNT5A / DLL1 / NKD1 88Patent Atty. 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No.150-35-PCT ID Description geneID regulation of epidermis GO:0045682 development DLL1 / PTCH1 / BMP4 ureteric bud GO:0060675 morphogenesis GREM1 / PTCH1 / BMP4 cellular response to GO:0071300 retinoic acid WNT5A / HAND2 / EPHA3 positive regulation of stress-activated protein kinase signaling GO:0070304 cascade WNT5A / HAND2 / TNFSF11 / BMP4 reproductive structure GO:0048608 development WNT5A / RBP4 / TBX3 / PTCH1 / BMP4 / FOXF2 mesonephric tubule GO:0072171 morphogenesis GREM1 / PTCH1 / BMP4 cell migration involved in heart GO:0060973 development HAND2 / BMP4 regulation of branching involved in ureteric bud GO:0090189 morphogenesis GREM1 / BMP4 regulation of cardiac muscle cell GO:2000725 differentiation DLL1 / BMP4 positive regulation of GO:0032024 insulin secretion ANO1 / RBP4 / VSNL1 GO:0042476 Odontogenesis HAND2 / APCDD1 / TNFSF11 / BMP4 GO:0001822 kidney development GREM1 / WNT5A / DLL1 / PTCH1 / RARB / BMP4 reproductive system GO:0061458 development WNT5A / RBP4 / TBX3 / PTCH1 / BMP4 / FOXF2 positive regulation of proteolysis involved in protein catabolic GO:1903052 process NKD2 / TRIB2 / RNF180 / RNF144A animal organ GO:0048645 formation WNT5A / HAND2 / BMP4 atrial cardiac muscle GO:0003228 tissue development TBX3 / BMP4 tripartite regional GO:0007351 subdivision WNT5A / TBX3 anterior / posterior axis GO:0008595 specification, embryo WNT5A / TBX3 GO:0009713 catechol-containing compoundMOXD1 / HAND289Patent Atty. 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No.150-35-PCT ID Description geneID biosynthetic process catecholamine GO:0042423 biosynthetic process MOXD1 / HAND2 GO:0060065 uterus development WNT5A / RBP4 cell proliferation involved in kidney GO:0072111 development PTCH1 / BMP4 GO:0043583 ear development COL11A1 / WNT5A / TBX3 / DLL1 / BMP4 regulation of ERK1 GO:0070372 and ERK2 cascade PDGFC / HAND2 / NOX4 / GPBAR1 / TNFSF11 / BMP4 endothelium GO:0003158 development ADAMTS12 / HOXB5 / DLL1 / BMP4 regulation of cell- GO:0010810 substrate adhesion GREM1 / COL8A1 / EDIL3 / SPOCK1 / EPHA3 regulation of osteoblast GO:0045667 differentiation GREM1 / HAND2 / PTCH1 / BMP4 non-canonical Wnt GO:0035567 signaling pathway WNT5A / NKD1 / DACT1 cardiac septum GO:0060411 morphogenesis WNT5A / TBX3 / BMP4 peptide hormone GO:0030072 secretion ANO1 / RBP4 / VSNL1 / IRS1 / TNFSF11 dorsal / ventral neural GO:0021904 tube patterning PTCH1 / BMP4 branching involved in mammary gland duct GO:0060444 morphogenesis WNT5A / TBX3 ammonium ion GO:0097164 metabolic process ALDH7A1 / RNF180 complex of collagen GO:0098644 trimers COL10A1 / COL11A1 / COL8A1 endoplasmic reticulum COL10A1 / COL11A1 / PDGFC / MATN3 / COL8A1 / WNT5 GO:0005788 lumen A / EVA1A / BMP4 Table 5 UNC-sc Single Bulk Sample -cell Single- RNA Bulk Typ Cell Che name lib cell run library run e Line Treatment prep m Pi P190429 am22s1 PDA P1904 FOLFIRIN T1 y05s01 eaton94 4 29T1 OX Yeh V3 P190722 am22s0 A P1907 FOLFIRIN T1 y07s01 eaton96 2 22T1 OX Yeh V3P191121 y10s01 eaton105 am26s0 P1911 FOLFIRIN Yeh V3Patent Atty. Dkt. No.150-35-PCT T2 5 PDA 21T2 OX C Pi P200220 am39s1 PDA P2002 FOLFIRIN T1Pi y11s01 eaton113 5 (TPF) eaton118 C 20T1 OX Yeh V3 Pi P220106 PDA P2201 gemcitabine T1 y18s01 eaton182 p09s12 eaton187 C 06T1 -abraxane Yeh V3 Pi P220330 PDA P2203 T1 y19s01 eaton184 C 30T1 NA Yeh V3.1 Table 6 Bulk public datasets (Part 1 / 3) # # Primar # SCI PuPatent Atty. Dkt. No.150-35-PCT IRC C UROMO BLC A Public 535 Yes# # Non- Su Survi duplicat # D r l i P h D RNAseq A i ID 1 5 5 1 5Table 6 Bulk public datasets (Part 3 / 3) Dataset Publication 5-Patent Atty. Dkt. No.150-35-PCT 203.e13. doi: 10.1016 / j.ccell.2017.07.007. PMID: 28810144; PMCID: PMC5964983. Cao et alell 2021 Sep 16;184(19):5031-5052e26 doi: b - :permCAF Genes restCAF genes Coefficient IGFL2 CHRDL1 1.9400 NOX4 OGN 2.2971 VSNL1 PI16 0.7869 BICD1 ANK2 1.4660 NPR3 ABCA8 1.2198 ETV1 TGFBR3 1.6366 ITGA11 FBLN5 1.5563 CNIH3 SCARA5 1.8657 COL11A1 KIAA1217 2.3576 93Patent Atty. Dkt. No.150-35-PCT Intercept -8.3790 TABLE 8 Survival analysis (Part 1 / 2) NEvt HR (95% CI) Med OS (95% CI)DeCAF=permCAF 493 334 1.634 (1.375,1.943) 17.7 (15.767,20.333) DeCAF=restCAF 432 233 NA 29.04 (23.75,34.5) Elyada_CAF=myCAF 762 469 1.203 (1.532,0.945) 21.32 (19.8,23.4) Elyada_CAF=iCAF-like 139 82 NA 25.2 (21.733,34.34) Maurer=ECM-rich 721 458 1.33 (1.047,1.69) 20.53 (19.21,22.93) Maurer=Immune-rich 180 93 NA 30.033 (24.1,35.53) MS_K2=Activated 785 476 1.279 (0.991,1.651) 21.45 (19.933,23.55) MS_K2=Normal 116 75 NA 30 (21.49,37.72) SCISSORS_CAF_K2=permCAF 695 430 1.4 (1.137,1.725) 20.333 (18.42,22.8) SCISSORS_CAF_K2=restCAF 206 121 NA 30.19 (24.87,35.53) DeCAF=permCAF 76 44 1.819 (1.069,3.094) 19.8 (14.067,25.367) DeCAF=restCAF 54 20 NA 30.033 (24.1,NA) Elyada_CAF=myCAF 97 48 1.575 (2.98,0.833) 20.333 (15.133,30.4) Elyada_CAF=iCAF-like 28 12 NA 30.033 (24.1,NA) Maurer=ECM-rich 81 41 1.507 (0.871,2.605) 20.333 (14.5,27) Maurer=Immune-rich 44 19 NA 30.033 (19.967,NA) MS_K2=Activated 117 58 1.851 (0.451,7.591) 23.833 (15.333,30.033) MS_K2=Normal 8 2 NA NA SCISSORS_CAF_K2=permCAF 100 48 1.3 (0.687,2.46) 21.067 (15.233,30.4) SCISSORS_CAF_K2=restCAF 25 12 NA 24.767 (19.967,NA) DeCAF=permCAF 58 54 1.406 (0.882,2.242) 16.41 (12.45,22.93) DeCAF=restCAF 32 27 NA 21.49 (16.66,58.25) Elyada_CAF=myCAF 82 75 1.711 (3.953,0.741) 16.965 (14.69,22.93) Elyada_CAF=iCAF-like 8 6 NA 29.04 (18.07,NA) Maurer=ECM-rich 85 78 2.01 (0.628,6.433) 17.08 (15.01,24.84) Maurer=Immune-rich 5 3 NA 29.04 (21.49,NA) MS_K2=Activated 71 65 1.302 (0.752,2.255) 17.08 (14.69,24.84) MS_K2=Normal 19 16 NA 21.49 (15.7,65.41) SCISSORS_CAF_K2=permCAF 70 64 1.34 (0.782,2.295) 16.965 (14.69,24.84) SCISSORS_CAF_K2=restCAF 20 17 NA 21.49 (11.93,71.23) DeCAF=permCAF 17 12 1.035 (0.421,2.544) 34.3 (17.333,NA) DeCAF=restCAF 12 8 NA 32.433 (10.267,NA) Elyada_CAF=myCAF 26 17 0.468 (1.639,0.134) 34.3 (17.833,NA) Elyada_CAF=iCAF-like 3 3 NA 10.267 (6.567,NA) Maurer=ECM-rich 14 10 1.143 (0.472,2.773) 34.3 (17.333,NA) Maurer=Immune-rich 15 10 NA 37.633 (12.3,NA) MS_K2=Activated 11 7 0.759 (0.301,1.915) 37.533 (17.833,NA) 94Patent Atty. 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No.150-35-PCT NEvt HR (95% CI) Med OS (95% CI)MS_K2=Normal 18 13 NA 27.733 (10.267,NA) SCISSORS_CAF_K2=permCAF 13 9 0.987 (0.406,2.401) 34.3 (17.833,NA) SCISSORS_CAF_K2=restCAF 16 11 NA 32.433 (10.267,NA) DeCAF=permCAF 15 4 1.219 (0.273,5.453) NA DeCAF=restCAF 13 3 NA NA Elyada_CAF=myCAF 25 6 0.663 (5.592,0.079) NA Elyada_CAF=iCAF-like 3 1 NA NA Maurer=ECM-rich 23 5 0.528 (0.102,2.727) NA Maurer=Immune-rich 5 2 NA NA MS_K2=Activated 26 7 74728001.504 (0,Inf) NA MS_K2=Normal 2 0 NA NA SCISSORS_CAF_K2=permCAF 24 5 0.331 (0.063,1.736) NA SCISSORS_CAF_K2=restCAF 4 2 NA 9 (7,NA) DeCAF=permCAF 65 42 1.19 (0.77,1.837) 15 (12,25) DeCAF=restCAF 60 42 NA 19 (15,23) Elyada_CAF=myCAF 97 66 1.392 (2.362,0.82) 16 (13,19) Elyada_CAF=iCAF-like 28 18 NA 21 (14,NA) Maurer=ECM-rich 111 75 0.968 (0.484,1.936) 18 (14,21) Maurer=Immune-rich 14 9 NA 14 (7,NA) MS_K2=Activated 112 75 1.394 (0.696,2.79) 16 (13,20) MS_K2=Normal 13 9 NA 20 (14,NA) SCISSORS_CAF_K2=permCAF 93 66 2.131 (1.241,3.661) 15 (11,18) SCISSORS_CAF_K2=restCAF 32 18 NA 24 (19,NA) DeCAF=permCAF 43 31 2.15 (1.185,3.903) 14.1 (10.9,23.3) DeCAF=restCAF 39 18 NA 35.8 (15.9,NA) Elyada_CAF=myCAF 43 26 0.969 (1.929,0.487) 20.3 (14.1,42) Elyada_CAF=iCAF-like 21 12 NA 14.1 (10.9,NA) Maurer=ECM-rich 20 16 2.098 (1.099,4.005) 12 (8.7,35.8) Maurer=Immune-rich 44 22 NA 25.6 (15.9,NA) MS_K2=Activated 59 36 2.656 (0.633,11.14) 16.5 (13.2,35.8) MS_K2=Normal 5 2 NA NA SCISSORS_CAF_K2=permCAF 41 25 1.076 (0.548,2.115) 16.6 (13.7,NA) SCISSORS_CAF_K2=restCAF 23 13 NA 25.6 (12,NA) DeCAF=permCAF 52 34 3.406 (1.2,9.668) 14.1 (11.6,23.8) DeCAF=restCAF 15 5 NA 50.4 (25.6,NA) Elyada_CAF=myCAF 50 29 0.165 (0.739,0.037) 16.6 (13.7,NA) Elyada_CAF=iCAF-like 3 2 NA 7.25 (3.6,NA) Maurer=ECM-rich 53 31 NA 16.6 (13.2,NA) MS_K2=Activated 49 29 5.385 (0.718,40.393) 14.1 (12.9,25.6) MS_K2=Normal 4 2 NA 50.4 (15,NA) SCISSORS_CAF_K2=permCAF 46 27 1.105 (0.323,3.785) 16.6 (13.7,NA) SCISSORS_CAF_K2=restCAF 7 4 NA 10.9 (7.8,NA) DeCAF=permCAF 137 97 1.786 (1.33,2.397) 20.53 (16.48,27.53) DeCAF=restCAF 151 84 NA 33.32 (25.26,49.9) 95Patent Atty. 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No.150-35-PCT NEvt HR (95% CI) Med OS (95% CI)Elyada_CAF=myCAF 249 153 0.966 (1.448,0.644) 24.38 (22.47,32.73) Elyada_CAF=iCAF-like 39 28 NA 33.32 (23.13,49.9) Maurer=ECM-rich 228 145 1.241 (0.86,1.791) 24.28 (21.81,32.04) Maurer=Immune-rich 60 36 NA 33.32 (24.11,50.95) MS_K2=Activated 247 153 1.106 (0.739,1.656) 24.28 (21.94,33.55) MS_K2=Normal 41 28 NA 33.32 (23.13,62.76) SCISSORS_CAF_K2=permCAF 221 137 1.189 (0.846,1.671) 24.05 (20.53,32.04) SCISSORS_CAF_K2=restCAF 67 44 NA 32.99 (25.26,49.9) DeCAF=permCAF 63 39 1.893 (1.194,3.003) 15.767 (12.7,22.8) DeCAF=restCAF 83 36 NA 23.033 (17.267,NA) Elyada_CAF=myCAF 126 67 1.455 (3.036,0.697) 20.1 (15.767,23.167) Elyada_CAF=iCAF-like 20 8 NA 44.4 (16.6,NA) Maurer=ECM-rich 121 69 2.063 (0.893,4.768) 19.933 (15.533,23.167) Maurer=Immune-rich 25 6 NA 21.733 (17.033,NA) MS_K2=Activated 136 71 1.712 (0.613,4.778) 20.1 (16.033,23.4) MS_K2=Normal 10 4 NA 21.733 (16.2,NA) SCISSORS_CAF_K2=permCAF 119 67 2.137 (1.023,4.463) 19.767 (15.567,23.033) SCISSORS_CAF_K2=restCAF 27 8 NA 44.4 (21.733,NA) TABLE 8 Survival analysis (Part 2 / 2) CoxPH - Log 6 12 24 HR Rank p- Mo Mo Mo 60 Mo p-value value study DeCAF=permCAF 0.90 0.67 0.39 0.13 <0.0001 <0.0001 AllData DeCAF=restCAF 0.93 0.80 0.54 0.28 NA NA AllData Elyada_CAF=myCAF 0.92 0.72 0.45 0.21 0.13 0.34 AllData Elyada_CAF=iCAF- like 0.92 0.81 0.54 0.14 NA NA AllData Maurer=ECM-rich 0.91 0.71 0.43 0.20 0.02 0.01 AllData Maurer=Immune-rich 0.96 0.83 0.58 0.22 NA NA AllData MS_K2=Activated 0.91 0.73 0.45 0.19 0.06 0.08 AllData MS_K2=Normal 0.96 0.80 0.54 0.25 NA NA AllData SCISSORS_CAF_K2 =permCAF 0.91 0.71 0.42 0.19 0.00 0.00 AllData SCISSORS_CAF_K2 =restCAF 0.94 0.80 0.59 0.24 NA NA AllData DeCAF=permCAF 0.90 0.66 0.38 0.15 0.03 0.03 CPTAC DeCAF=restCAF 0.96 0.79 0.66 0.32 NA NA CPTAC Elyada_CAF=myCAF 0.93 0.68 0.43 0.19 0.16 0.16 CPTAC Elyada_CAF=iCAF- like 0.89 0.81 0.67 0.32 NA NA CPTAC Maurer=ECM-rich 0.91 0.66 0.42 0.18 0.14 0.14 CPTAC Maurer=Immune-rich 0.95 0.80 0.62 0.30 NA NA CPTAC 96Patent Atty. 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No.150-35-PCT CoxPH - Log 6 12 24 HR Rank p- Mo Mo Mo 60 Mo p-value value study MS_K2=Activated 0.93 0.70 0.49 0.21 0.39 0.38 CPTAC MS_K2=Normal 0.86 0.86 0.57 0.57 NA NA CPTAC SCISSORS_CAF_K2 =permCAF 0.94 0.69 0.45 0.21 0.42 0.42 CPTAC SCISSORS_CAF_K2 =restCAF 0.88 0.79 0.63 0.28 NA NA CPTAC DeCAF=permCAF 0.97 0.67 0.35 0.10 0.15 0.15 Dijk DeCAF=restCAF 0.94 0.72 0.50 0.23 NA NA Dijk Elyada_CAF=myCAF 0.96 0.67 0.38 0.13 0.21 0.20 Dijk Elyada_CAF=iCAF- like 0.88 0.88 0.63 0.31 NA NA Dijk Maurer=ECM-rich 0.97 0.68 0.39 0.13 0.24 0.23 Dijk Maurer=Immune-rich 0.80 0.80 0.53 0.27 NA NA Dijk MS_K2=Activated 0.96 0.69 0.38 0.12 0.35 0.35 Dijk MS_K2=Normal 0.95 0.68 0.47 0.23 NA NA Dijk SCISSORS_CAF_K2 =permCAF 0.96 0.70 0.37 0.11 0.29 0.29 Dijk SCISSORS_CAF_K2 =restCAF 0.95 0.65 0.50 0.26 NA NA Dijk DeCAF=permCAF 1.00 0.81 0.56 0.11 0.94 0.94 Grunwald DeCAF=restCAF 1.00 0.67 0.58 0.23 NA NA Grunwald Elyada_CAF=myCAF 1.00 0.80 0.60 0.17 0.24 0.22 Grunwald Elyada_CAF=iCAF- like 1.00 0.33 0.33 0.00 NA NA Grunwald Maurer=ECM-rich 1.00 0.77 0.54 0.14 0.77 0.77 Grunwald Maurer=Immune-rich 1.00 0.73 0.60 0.15 NA NA Grunwald MS_K2=Activated 1.00 0.90 0.70 0.18 0.56 0.56 Grunwald MS_K2=Normal 1.00 0.67 0.50 0.13 NA NA Grunwald SCISSORS_CAF_K2 =permCAF 1.00 0.83 0.58 0.15 0.98 0.98 Grunwald SCISSORS_CAF_K2 =restCAF 1.00 0.69 0.56 0.14 NA NA Grunwald DeCAF=permCAF 0.93 0.87 0.79 0.53 0.80 0.79 Linehan DeCAF=restCAF 1.00 0.85 0.74 0.74 NA NA Linehan Elyada_CAF=myCAF 0.96 0.88 0.78 0.62 0.71 0.70 Linehan Elyada_CAF=iCAF- like 1.00 0.67 0.67 0.67 NA NA Linehan Maurer=ECM-rich 0.96 0.87 0.82 0.66 0.45 0.43 Linehan Maurer=Immune-rich 1.00 0.80 0.53 0.53 NA NA Linehan MS_K2=Activated 0.96 0.85 0.75 0.62 1.00 0.48 Linehan MS_K2=Normal 1.00 1.00 1.00 1.00 NA NA Linehan SCISSORS_CAF_K2 =permCAF 0.96 0.92 0.81 0.65 0.19 0.18 Linehan SCISSORS_CAF_K2 =restCAF 1.00 0.50 0.50 0.50 NA NA Linehan Moffitt_GEO_arra DeCAF=permCAF 0.83 0.60 0.36 0.08 0.43 0.42 y 97Patent Atty. Dkt. No.150-35-PCT CoxPH - Log 6 12 24 HR Rank p- Mo Mo Mo 60 Mo p-value value study Moffitt_GEO_arra DeCAF=restCAF 0.81 0.66 0.30 0.09 NA NA y Moffitt_GEO_arra Elyada_CAF=myCAF 0.80 0.61 0.31 0.12 0.22 0.22 y Elyada_CAF=iCAF- Moffitt_GEO_arra like 0.89 0.69 0.37 0.12 NA NA y Moffitt_GEO_arra Maurer=ECM-rich 0.82 0.63 0.33 0.09 0.93 0.95 y Moffitt_GEO_arra Maurer=Immune-rich 0.85 0.62 0.26 0.26 NA NA y Moffitt_GEO_arra MS_K2=Activated 0.82 0.61 0.33 0.07 0.35 0.35 y Moffitt_GEO_arra MS_K2=Normal 0.85 0.77 0.31 0.31 NA NA y SCISSORS_CAF_K2 Moffitt_GEO_arra =permCAF 0.79 0.58 0.28 0.04 0.01 0.00 y SCISSORS_CAF_K2 Moffitt_GEO_arra =restCAF 0.90 0.77 0.46 0.18 NA NA y DeCAF=permCAF 0.90 0.58 0.26 0.10 0.01 0.01 PACA_AU_array DeCAF=restCAF 0.86 0.75 0.58 0.31 NA NA PACA_AU_array Elyada_CAF=myCAF 0.95 0.76 0.43 0.15 0.93 0.93 PACA_AU_array Elyada_CAF=iCAF- like 0.84 0.53 0.41 0.31 NA NA PACA_AU_array Maurer=ECM-rich 0.84 0.47 0.21 0.14 0.02 0.02 PACA_AU_array Maurer=Immune-rich 0.95 0.78 0.53 0.24 NA NA PACA_AU_array MS_K2=Activated 0.91 0.65 0.39 0.20 0.18 0.17 PACA_AU_array MS_K2=Normal 1.00 1.00 0.80 0.53 NA NA PACA_AU_array SCISSORS_CAF_K2 =permCAF 0.95 0.70 0.36 0.21 0.83 0.83 PACA_AU_array SCISSORS_CAF_K2 =restCAF 0.85 0.64 0.53 0.20 NA NA PACA_AU_array DeCAF=permCAF 0.88 0.60 0.29 0.00 0.02 0.01 PACA_AU_seq DeCAF=restCAF 0.93 0.86 0.76 0.00 NA NA PACA_AU_seq Elyada_CAF=myCAF 0.92 0.70 0.38 0.00 0.02 0.01 PACA_AU_seq Elyada_CAF=iCAF- like 0.50 0.00 0.00 0.00 NA NA PACA_AU_seq Maurer=ECM-rich 0.90 0.67 0.36 0.00 NA NA PACA_AU_seq MS_K2=Activated 0.89 0.64 0.32 0.00 0.10 0.07 PACA_AU_seq MS_K2=Normal 1.00 1.00 0.75 0.00 NA NA PACA_AU_seq SCISSORS_CAF_K2 =permCAF 0.91 0.70 0.35 0.00 0.87 0.88 PACA_AU_seq SCISSORS_CAF_K2 =restCAF 0.80 0.40 0.40 0.00 NA NA PACA_AU_seq DeCAF=permCAF 0.92 0.71 0.46 0.18 0.00 <0.0001 Puleo_array DeCAF=restCAF 0.98 0.87 0.61 0.35 NA NA Puleo_array Elyada_CAF=myCAF 0.95 0.78 0.52 0.30 0.87 0.87 Puleo_array Elyada_CAF=iCAF- like 0.97 0.90 0.62 0.15 NA NA Puleo_array 98Patent Atty. Dkt. No.150-35-PCT CoxPH - Log 6 12 24 HR Rank p- Mo Mo Mo 60 Mo p-value value study Maurer=ECM-rich 0.94 0.77 0.51 0.28 0.25 0.25 Puleo_array Maurer=Immune-rich 0.98 0.88 0.63 0.27 NA NA Puleo_array MS_K2=Activated 0.95 0.79 0.52 0.27 0.62 0.62 Puleo_array MS_K2=Normal 0.98 0.83 0.63 0.30 NA NA Puleo_array SCISSORS_CAF_K2 =permCAF 0.94 0.76 0.50 0.28 0.32 0.32 Puleo_array SCISSORS_CAF_K2 =restCAF 0.99 0.89 0.65 0.27 NA NA Puleo_array DeCAF=permCAF 0.85 0.63 0.24 0.17 0.01 0.01 TCGA_PAAD DeCAF=restCAF 0.91 0.85 0.48 0.25 NA NA TCGA_PAAD Elyada_CAF=myCAF 0.86 0.72 0.36 0.26 0.32 0.31 TCGA_PAAD Elyada_CAF=iCAF- like 1.00 1.00 0.51 0.00 NA NA TCGA_PAAD Maurer=ECM-rich 0.86 0.71 0.35 0.22 0.09 0.08 TCGA_PAAD Maurer=Immune-rich 1.00 1.00 0.50 0.00 NA NA TCGA_PAAD MS_K2=Activated 0.87 0.73 0.37 0.18 0.30 0.30 TCGA_PAAD MS_K2=Normal 1.00 1.00 0.46 0.46 NA NA TCGA_PAAD SCISSORS_CAF_K2 =permCAF 0.86 0.71 0.33 0.23 0.04 0.04 TCGA_PAAD SCISSORS_CAF_K2 =restCAF 0.96 0.96 0.61 0.21 NA NA TCGA_PAAD Table 9 Univariate survival analysis UNC-bulk (Part 1 / 2) Characteris tic N Et Median (95% CI) 6 Months 12 Months 24 Months 60 MonthsPatent Atty. Dkt. No.150-35-PCT Characteris tic N Et Median (95% CI) 6 Months 12 Months 24 Months 60 Months Strong 18 (8.9 80% (64% 57% (38% 29% (13%Patent Atty. Dkt. No.150-35-PCT Characteris tic N Et Median (95% CI) 6 Months 12 Months 24 Months 60 Months 100% 100%Patent Atty. Dkt. No.150-35-PCT Characteris tic N Et Median (95% CI) 6 Months 12 Months 24 Months 60 Months 55) 100%) 88%) 72%) 47%) ,Patent Atty. Dkt. No.150-35-PCT Characteris tic N Et Median (95% CI) 6 Months 12 Months 24 Months 60 Months ) (100% 100%) 77%) 63%)Patent Atty. Dkt. No.150-35-PCT Characteris tic N Et Median (95% CI) 6 Months 12 Months 24 Months 60 Months Neoadj.RegiPatent Atty. Dkt. No.150-35-PCT Characteris N E Median tic t (95% CI) 6 Months 12 Months 24 Months 60 Months Adj Tx.cleaTable 9 Univariate survival analysis UNC-bulk (Part 2 / 2) Characteristic p-value1HR295% CI2p-valuePatent Atty. Dkt. No.150-35-PCT Characteristic p-value1HR295% CI2p-value 5.17Patent Atty. Dkt. No.150-35-PCT Characteristic p-value1HR295% CI2p-value 0.38Patent Atty. Dkt. No.150-35-PCT Characteristic p-value1HR295% CI2p-value 4.03Patent Atty. Dkt. No.150-35-PCT Characteristic p-value1HR295% CI2p-value 1.79Patent Atty. Dkt. No.150-35-PCT Characteristic p-value1HR295% CI2p-value 0.98ORA KEGG ALL (Part 1 / 2) Gene ID Ratio BgRatio pvalue p.adjust qvalue Ct 4 0 2 2 0 6 2 6 0 1 1 9 5 5 2 5 8 1 9 3 7 1 1 3 3 2 7 0 1 3 9 0 2 5 7 0 1TABLE 10 ORA KEGG ALL(Part 2 / 2) ID Description geneIDPatent Atty. Dkt. No.150-35-PCT CD36 / FN1 / ITGA11 / ITGA2 / ITGA3 / ITGA5 / ITGA6 / WPatent Atty. Dkt. No.150-35-PCT hsa00640 Propanoate ACACB / ACOX1 / ACSS1 / ACSS3 / ECHDC1 / metabolism EHHADH / LDHA / LDHB / SUCLG2Patent Atty. Dkt. No.150-35-PCT Protein COL10A1 / COL11A1 / COL12A1 / COL14A1 / COL15A1 / hsa04974 digestion and COL17A1 / COL18A1 / COL28A1 / COL3A1 / absorption COL7A1 / COL8A1 / MME / SLC3A2 hsa05222 Small cell lung CDKN1B / FN1 / ITGA2 / ITGA3 / ITGA6 / ITGAV / cancer ITGB1 / LAMA3 / LAMA5 / LAMB2 / LAMB3 / LAMC2 Starch and hsa00500 sucrose GBE1 / GYS1 / HK1 / HK2 / HK3 / PYGL / PYGM metabolism Rap1 signal BCAR1 / ENAH / EVL / FLT1 / GNAO1 / ITGAM / hsa04015 ing pathway ITGB1 / MAP2K6 / MET / NGFR / PDGFC / PLCB4 / PRKCB / PRKCI / RALB / SIPA1L1 / SKAP1 / THBS1 / VASP / VEGFA Regulation of BCAR1 / ENAH / EZR / FN1 / IQGAP1 / ITGA11 / ITGA2 / hsa04810 actin ITGA3 / ITGA5 / ITGA6 / ITGA7 / ITGAM / ITGAV / ITGB1 / cytoskeleton ITGB4 / ITGB5 / ITGB6 / MYH9 / PDGFC / PPP1R12B / PXN hsa05145 Toxoplasmosis GNAO1 / IRAK4 / ITGA6 / ITGB1 / JAK2 / LAMA3 / LAMA5 / LAMB2 / LAMB3 / LAMC2 / LDLR / MAP2K6 / TLR2 hsa00310 Lysine AASS / ACAT1 / ALDH2 / ALDH9A1 / COLGALT1 degradation / EHHADH / PLOD1 / PLOD2 / PLOD3 hsa05140 Leishmaniasis FCGR3A / IRAK4 / ITGAM / ITGB1 / JAK2 / NCF1 / NCF2 / NCF4 / PRKCB / TLR2 Glucagon hsa04922 signaling ACACB / GYS1 / ITPR3 / LDHA / LDHB / PFKL / PFKP / pathway PGAM1 / PLCB4 / PYGL / PYGM / SLC2A1 Cell adhesi CD2 / CD34 / CD8A / CD99L2 / CDH3 / ITGA6 / hsa04514 on molecules ITGAM / ITGAV / ITGB1 / NCAM1 / NEGR1 / PTPRF / PTPRS / SDC1 / SELP Other types of hsa00514 O-glycan B4GALT1 / COLGALT1 / GALNT1 / GALNT10 / biosynthesis GALNT2 / PLOD3 / POFUT2 Complement hsa04610 and coagulation A2M / CD55 / CR2 / F10 / F9 / ITGAM / PLAU / cascades PLAUR / SERPINE1 / SERPINE2 AGE-RAGE signaling hsa04933 pathway in CDKN1B / COL3A1 / CXCL8 / FN1 / JAK2 / PLCB4 / diabetic PRKCB / PRKCE / SERPINE1 / STAT5A / VEGFA complications Table 10 (continued) 113Patent Atty. Dkt. No.150-35-PCT ORA KEGG permCAF (Part 1 / 2) Gene ID Ratio BgRatio pvalue p.adjust qvalue Ct 9 6 9 3 7 1 9 6 9 5 3 1 0 9 0 6 7 0 6 9 9 9 3 6 9 7 7 8 8 9 4Table 10 (continued) ORA KEGG permCAF (Part 2 / 2)Patent Atty. Dkt. No.150-35-PCT ZYX hsa04 ALDOA / ALDOC / CUL2 / EGLN1 / ENO1 / ENO2 / HIF-1 si nalin athwa FLT1 / HK1 / HK2 / HK3 / LDHA / PFKFB3 / PFKL / PFKP / Patent Atty. Dkt. No.150-35-PCT hsa05 144 Malaria CXCL8 / MET / SDC1 / THBS1 / THBS2 / TLR2 hsa04 Leukocyte BCAR1 / EZR / ITGAM / ITGB1 / NCF1 / NCF2 / Table 10 (continued) ORA KEGG restCAF (Part 1 / 2) Gene ID Ratio BgRatio Pvalue padjust qvalue Ct 0 0 9 6 7 7 5Table 10 (continued) ORA KEGG restCAF (Part 2 / 2)Patent Atty. Dkt. No.150-35-PCT immunodeficiency SEQUENCE DATA

[0158] I hereby state that the information recorded in computer readable form is identical to the written sequence listing below. SEQUENCE LISTING ABCA8, NM_001288985.2 Homo sapiens ATP binding cassette subfamily A member 8 (ABCA8), transcript variant 1, mRNA; DNA; Homo S (SEQ ID NO: 1) ATAACCTCCACTCTGAAAGCAGTCTTCACAGAAACTTTTCACAGAAGTCAAATAGTTAAAGCAAATTCTA GATACATGGTAGAGACCAGGAGAAAATATGAATAACTTTCTTCTAAACAAGGAGCTCAGTGGATAAACCA TACCTCTAGATTCCTTGCTTCCATTTTCCCAGAAGTTTTGGTAGCAGGATGATGTTGGCCTCATAATGTG AGTTAGAGAGGAGTCCCTCTTTTTCGACTGTTTGGAATTGTTTCAGAAGGAATGCTACCAGCTCCTCTTG TACCACTGGTAGAATTCAGCTGTGAATCTGTCTGGTCCTGGGCTTTTTTTGATTGACAAGATGAGGAAGA GAAAGATCAGTGTGTGTCAACAAACTTGGGCCTTATTATGCAAGAACTTTCTTAAAAAATGGAGAATGAA AAGAGAGTCCTTAATGGAATGGCTGAATTCATTGCTCCTACTACTTTGTTTGTATATATATCCTCATAGT CATCAAGTAAATGATTTTTCTTCACTGCTTACCATGGACCTGGGACGGGTAGATACATTTAATGAATCCA GATTTTCTGTTGTATACACACCTGTCACCAACACGACCCAACAGATAATGAATAAAGTAGCCTCTACTCC CTTCCTGGCAGGTAAAGAGGTCTTGGGACTGCCAGATGAGGAAAGTATTAAAGAATTCACAGCAAATTAT CCTGAAGAAATAGTAAGAGTCACCTTTACTAATACATACTCATATCATTTGAAGTTCTTGCTAGGACATG GAATGCCAGCAAAGAAGGAGCACAAGGACCATACAGCTCATTGTTATGAAACAAATGAAGATGTTTACTG TGAAGTTTCAGTATTTTGGAAGGAAGGTTTTGTGGCTCTTCAAGCTGCCATTAATGCTGCTATTATAGAA ATCACAACAAATCACTCAGTGATGGAGGAGCTGATGTCAGTTACTGGAAAAAATATGAAGATGCATTCCT TCATTGGTCAATCAGGAGTTATAACTGATTTGTACCTTTTTTCCTGCATTATTTCATTTTCCTCATTCAT TTACTATGCATCTGTTAATGTCACAAGAGAGAGGAAAAGGATGAAGGCCTTGATGACAATGATGGGTCTT CGGGATTCAGCGTTCTGGCTCTCCTGGGGTTTGCTCTATGCTGGTTTCATCTTCATTATGGCCCTTTTCT TGGCACTTGTTATAAGATCTACCCAGTTTATCATTTTGTCTGGCTTCATGGTAGTCTTCAGCCTCTTTCT CCTGTATGGATTATCTTTGGTAGCTTTGGCTTTCTTAATGAGCATCTTGGTAAAGAAATCTTTCCTCACC GGCCTGGTCGTGTTCCTCCTCACTGTCTTTTGGGGGTGTCTGGGGTTCACATCACTGTACAGACACCTTC CTGCATCCTTGGAGTGGATTTTAAGCTTGCTTAGTCCCTTTGCCTTCATGCTTGGAATGGCCCAGCTTTT ACACTTGGACTATGATTTGAATTCTAATGCATTTCCTCATCCATCGGACGGCTCAAATCTCATTGTAGCA ACAAATTTCATGTTGGCATTTGACACTTGCCTCTATCTGGCATTGGCGATTTACTTTGAAAAAATTTTGC CAAATGAATATGGACATCGACGTCCACCTTTGTTTTTCCTGAAGTCCTCATTTTGGTCTCAAACACAAAA GACTGATCACGTGGCCCTTGAAGATGAAATGGATGCCGATCCTTCATTTCATGACTCTTTTGAACAAGCG CCTCCAGAATTCCAAGGGAAAGAAGCCATCAGAATCAGAAATGTTACAAAAGAATATAAAGGAAAGCCTG ATAAAATAGAAGCCTTGAAAGATCTGGTATTTGACATTTACGAAGGCCAAATCACTGCAATACTTGGTCA CAGTGGAGCTGGAAAGTCAACACTGCTAAACATTCTTAGTGGGTTGTCTGTTCCCACCAAAGGTTCAGTC ACCATCTATAACAATAAGCTTTCAGAAATGGCTGACCTAGAAAATCTCAGCAAGCTGACCGGAGTTTGTC CACAATCCAATGTGCAATTTGACTTCCTCACTGTAAGAGAAAACCTCAGACTCTTTGCTAAAATAAAAGG GATTCTGCCACAAGAAGTGGATAAAGAGATACAAAGGGTTCTGCTGGAATTGGAAATGAAAAATATTCAG GATGTTCTTGCTCAAAACTTAAGTGGTGGACAGAAAAGAAAGCTAACCTTTGGGATTGCCATTTTAGGAG ATCCTCAGATTTTCCTGTTGGATGAACCAACTGCTGGATTGGATCCCTTTTCAAGACACCAAGTATGGAA CCTTCTGAAAGAACGCAAAACAGACCGCGTGATCCTCTTCAGTACCCAGTTCATGGATGAGGCCGACATC CTGGCGGACAGGAAAGTATTTCTCTCCCAAGGGAAGCTAAAGTGCGCGGGCTCTTCTTTGTTTCTAAAGA AGAAATGGGGGATTGGATATCACTTAAGCTTGCAGTTAAATGAAATATGTGTTGAGGAAAACATAACATC ACTTGTTAAACAGCACATCCCTGATGCCAAATTATCAGCCAAAAGCGAAGGAAAACTTATTTATACATTA CCCTTAGAAAGAACAAATAAATTTCCAGAACTTTACAAGGATCTTGATAGCTATCCTGACCTAGGAATTG AGAATTATGGTGTTTCCATGACAACTTTGAATGAAGTATTCCTGAAGCTAGAAGGAAAATCTACAATTAA TGAATCGGACATTGCTATTTTGGGAGAAGTACAAGCGGAAAAAGCTGACGACACTGAAAGGCTTGTTGAG ATGGAACAAGTCCTCTCTTCACTTAACAAGATGAGAAAGACAATAGGTGGTGTGGCTCTCTGGCGACAGC AAATCTGCGCAATTGCAAGGGTTCGCTTGTTAAAGTTAAAGCATGAAAGAAAAGCTCTTTTAGCACTGCT ATTAATTCTAATGGCTGGATTTTGCCCTCTTCTTGTGGAGTATACCATGGTGAAAATATATCAAAACAGT TACACCTGGGAACTTTCTCCTCATTTGTATTTCCTTGCTCCTGGACAACAACCACATGACCCTCTCACTC AACTACTGATCATCAATAAAACAGGGGCAAGCATTGATGACTTTATACAGTCTGTGGAGCACCAGAACAT 117Patent Atty. 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No.150-35-PCT AGCTTTAGAAGTGGATGCATTTGGAACTAGAAATGGCACAGATGACCCATCTTATAATGGAGCCATCACA GTGTGTTGTAATGAAAAGAATTACAGCTTTTCGTTAGCATGCAATGCCAAAAGATTGAATTGCTTCCCAG TTCTTATGGACATTGTTAGTAATGGGCTACTTGGAATGGTTAAACCATCAGTACATATCCGAACTGAAAG AAGTACATTTTTGGAGAATGGACAGGACAATCCAATCGGATTCCTGGCATATATCATGTTCTGGCTGGTT TTAACATCGAGTTGCCCACCTTACATTGCCATGAGCAGCATCGATGATTATAAGAACAGAGCTCGGTCCC AGCTACGGATTTCCGGACTCTCCCCTTCTGCTTACTGGTTTGGGCAGGCGCTGGTGGATGTTTCCCTGTA CTTCTTGGTCTTCGTTTTTATATATTTAATGAGCTACATTTCAAACTTCGAAGACATGCTACTTACAATA ATTCATATTATTCAAATCCCATGTGCTGTTGGTTATTCCTTTTCCCTCATCTTCATGACATACGTGATTT CCTTCATCTTTCGCAAGGGGAGAAAAAATAGTGGCATTTGGTCATTTTGTTTCTATGTTGTCACTGTATT CTCTGTGGCTGGATTTGCGTTCAGTATCTTCGAAAGTGATATTCCATTTATCTTCACTTTTTTAATACCA CCTGCCACAATGATTGGCTGTTTGTTCTTATCTTCTCATCTTCTCTTTTCTTCTCTCTTTTCTGAAGAAC GAATGGATGTACAGCCATTTCTGGTATTCCTAATTCCTTTCCTTCATTTTATCATTTTTCTTTTTACTCT TCGATGTCTGGAATGGAAGTTTGGAAAGAAATCAATGAGAAAGGATCCTTTCTTTAGAATTTCTCCAAGA AGTAGTGATGTGTGTCAAAATCCAGAAGAACCAGAAGGAGAGGATGAAGATGTTCAGATGGAAAGAGTGA GAACAGCAAATGCCTTGAATTCTACTAATTTTGATGAGAAGCCAGTCATCATTGCCAGCTGTCTACGCAA GGAGTATGCAGGGAAGAGGAAAGGCTGTTTTTCCAAGAGGAAGAATAAGATAGCCACGAGAAATGTCTCC TTCTGTGTTAGAAAAGGTGAAGTTTTAGGATTATTAGGACACAATGGAGCTGGTAAAAGCACATCCATTA AGGTGATAACTGGAGACACAAAACCAACTGCTGGACAAGTGCTACTGAAAGGGAGCGGTGGAGGGGATGC CCTGGAGTTCCTGGGGTACTGCCCTCAGGAGAACGCGCTGTGGCCCAACCTGACAGTGAGGCAGCACCTG GAGGTGTACGCCGCCGTGAAAGGGCTGAGGAAAGGGGATGCTGAGGTTGCCATCACACGGTTAGTGGATG CGCTCAAGCTGCAGGACCAGCTGAAGTCTCCCGTGAAGACCTTGTCAGAGGGAATAAAGAGAAAGCTGTG CTTTGTCCTGAGCATACTGGGGAACCCGTCAGTGGTGCTTCTGGATGAGCCGTCGACCGGGATGGACCCC GAGGGGCAGCAGCAAATGTGGCAGGCCATCCGGGCCACCTTTAGAAACACGGAAAGGGGTGCCCTCCTAA CCACCCACTACATGGCAGAGGCTGAGGCCGTGTGTGACCGAGTGGCCATCATGGTATCTGGGAGGTTGAG ATGTATCGGTTCCATCCAACACCTGAAAAGCAAATTTGGCAAAGATTACCTGCTGGAGATGAAGGTGAAG AACCTGGCACAAGTGGAGCCCCTCCATGCAGAGATCCTGAGGCTTTTCCCCCAGGCTGCTCGGCAGGAAA GGTACTCCTCTCTGATGGTTTATAAGTTGCCAGTGGAAGATGTGCAACCTTTAGCCCAAGCTTTCTTCAA ATTAGAGAAGGTTAAACAGAGCTTTGACCTAGAGGAGTACAGCCTCTCACAGTCTACCCTGGAGCAGGTT TTCCTGGAGCTCTCCAAGGAGCAGGAGCTGGGTGATTTTGAGGAGGATTTTGATCCCTCAGTGAAGTGGA AGCTCCTCCCCCAGGAAGAGCCTTAAAACCCCAAATTCTGTGTTCCTGTTTAAACCCGTGGTTTTTTTTA AATACATTTATTTTTATAGCAGCAATGTTCTATTTTTAGAAACTATATTATAAGTACAGAAATGGTTCTC CGTGTGGTGGGAGGAGGAGGTTCGGGTGCTGGGTAAGTGCCATGTCAGTGTGGACAGAGGCATTTGACTA AGCCAACCTCCTCTCACAGCCTCTGTATCTCTGCAGGCCATACTGGTTCCATTGTTCTGTATAATACTGA ATAAATAAATTTACTTTTACATGATCGTATAAGTTTCTAGATAAGATAAACAAATTTTGTTTAAATTTTT TTAATAAAAATCTTAAAACACTTTTTTTCTAACCTAGACTGAGAAATTCATGTTTACTTTTCTAGGTGTA TGATACTTTGTAAAGTTGATACTTTCCTAAGAATTTAACATGTCATATTTTTGAAATAGATTTAAGTGTG CTTCTTATTGCTAAAAATACTAAATGTCATGGGTCATAGTATCTGATATCAATATCGTTGATAACATATC CACAGGTAACACCATGATGTAGGCATAAATGGAAAACAAAAACCCTACTATTTCAAATATATTGTACTTT TTTATTTCTGTAAGCCAACTGTGTGCCATTTTCACTGGACTTTTAAATCTAGACTTTAGTGATGTCTACA TTGTAAATGATCTTTTGTGGATATTTGTCACTTGGTTTCAGAAAGTTCACAAATGTAGCAACAGCTCACA TGACTGAGTAGGTAGAAAATGTGAAATAAATCTCATATATATAGTTTTGAAA ABCA8, NP_001275914.1 ABC-type organic anion transporter ABCA8 isoform 1; AA; Homo sapiens(SEQ ID NO:2) MRKRKISVCQQTWALLCKNFLKKWRMKRESLMEWLNSLLLLLCLYIYPHSHQVNDFSSLLTMDLGRVDTF NESRFSVVYTPVTNTTQQIMNKVASTPFLAGKEVLGLPDEESIKEFTANYPEEIVRVTFTNTYSYHLKFL LGHGMPAKKEHKDHTAHCYETNEDVYCEVSVFWKEGFVALQAAINAAIIEITTNHSVMEELMSVTGKNMK MHSFIGQSGVITDLYLFSCIISFSSFIYYASVNVTRERKRMKALMTMMGLRDSAFWLSWGLLYAGFIFIM ALFLALVIRSTQFIILSGFMVVFSLFLLYGLSLVALAFLMSILVKKSFLTGLVVFLLTVFWGCLGFTSLY RHLPASLEWILSLLSPFAFMLGMAQLLHLDYDLNSNAFPHPSDGSNLIVATNFMLAFDTCLYLALAIYFE KILPNEYGHRRPPLFFLKSSFWSQTQKTDHVALEDEMDADPSFHDSFEQAPPEFQGKEAIRIRNVTKEYK GKPDKIEALKDLVFDIYEGQITAILGHSGAGKSTLLNILSGLSVPTKGSVTIYNNKLSEMADLENLSKLT GVCPQSNVQFDFLTVRENLRLFAKIKGILPQEVDKEIQRVLLELEMKNIQDVLAQNLSGGQKRKLTFGIA ILGDPQIFLLDEPTAGLDPFSRHQVWNLLKERKTDRVILFSTQFMDEADILADRKVFLSQGKLKCAGSSL FLKKKWGIGYHLSLQLNEICVEENITSLVKQHIPDAKLSAKSEGKLIYTLPLERTNKFPELYKDLDSYPD LGIENYGVSMTTLNEVFLKLEGKSTINESDIAILGEVQAEKADDTERLVEMEQVLSSLNKMRKTIGGVAL WRQQICAIARVRLLKLKHERKALLALLLILMAGFCPLLVEYTMVKIYQNSYTWELSPHLYFLAPGQQPHD PLTQLLIINKTGASIDDFIQSVEHQNIALEVDAFGTRNGTDDPSYNGAITVCCNEKNYSFSLACNAKRLN CFPVLMDIVSNGLLGMVKPSVHIRTERSTFLENGQDNPIGFLAYIMFWLVLTSSCPPYIAMSSIDDYKNR ARSQLRISGLSPSAYWFGQALVDVSLYFLVFVFIYLMSYISNFEDMLLTIIHIIQIPCAVGYSFSLIFMT YVISFIFRKGRKNSGIWSFCFYVVTVFSVAGFAFSIFESDIPFIFTFLIPPATMIGCLFLSSHLLFSSLF SEERMDVQPFLVFLIPFLHFIIFLFTLRCLEWKFGKKSMRKDPFFRISPRSSDVCQNPEEPEGEDEDVQM ERVRTANALNSTNFDEKPVIIASCLRKEYAGKRKGCFSKRKNKIATRNVSFCVRKGEVLGLLGHNGAGKS 118Patent Atty. 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No.150-35-PCT TSIKVITGDTKPTAGQVLLKGSGGGDALEFLGYCPQENALWPNLTVRQHLEVYAAVKGLRKGDAEVAITR LVDALKLQDQLKSPVKTLSEGIKRKLCFVLSILGNPSVVLLDEPSTGMDPEGQQQMWQAIRATFRNTERG ALLTTHYMAEAEAVCDRVAIMVSGRLRCIGSIQHLKSKFGKDYLLEMKVKNLAQVEPLHAEILRLFPQAA RQERYSSLMVYKLPVEDVQPLAQAFFKLEKVKQSFDLEEYSLSQSTLEQVFLELSKEQELGDFEEDFDPS VKWKLLPQEEP ANK2, NM_001148.6 Homo sapiens ankyrin 2 (ANK2), transcript variant 1, mRNA; DNA; Homo sapiens (SEQ ID NO:3) AAGTGCATACCCGCTAGTGGTCTGTACAGGCGGCACGGTTTGATGGCAGAGATATTTTCTTTCCAAACTG TTCAAAATGATGAACGAAGATGCAGCTCAGAAAAGCGACAGTGGAGAGAAGTTCAACGGCAGTAGTCAGA GGAGAAAAAGACCCAAGAAGTCTGACAGCAATGCAAGCTTCCTCCGTGCTGCCAGAGCAGGCAACCTGGA CAAAGTTGTGGAATATCTGAAGGGGGGCATAGACATCAATACCTGCAATCAGAATGGACTCAACGCTCTC CATCTGGCTGCCAAGGAAGGCCACGTGGGGCTGGTGCAGGAGCTGCTGGGAAGAGGGTCCTCTGTGGATT CTGCCACTAAGAAGGGAAATACCGCTCTTCACATTGCATCTTTGGCTGGACAAGCAGAAGTTGTCAAAGT TCTTGTTAAGGAAGGAGCCAATATTAATGCACAGTCTCAGAATGGCTTTACTCCTTTATACATGGCTGCC CAAGAGAATCACATTGATGTTGTAAAATATTTGCTGGAAAATGGAGCTAATCAGAGCACTGCTACAGAGG ATGGCTTTACTCCTCTAGCTGTGGCACTCCAGCAAGGACACAACCAGGCGGTGGCCATCCTCTTGGAGAA TGACACCAAAGGGAAAGTGAGGCTGCCAGCTCTGCATATTGCCGCTAGGAAAGACGACACCAAATCTGCC GCACTTCTGCTTCAGAATGACCACAATGCTGACGTACAATCCAAGATGATGGTGAATAGGACAACTGAGA GTGGTTTTACCCCTTTGCACATAGCTGCACATTACGGAAATGTCAACGTGGCAACTCTTCTTCTAAACCG GGGAGCTGCTGTGGACTTCACAGCCAGGAATGGAATCACTCCTCTGCATGTGGCTTCCAAAAGAGGAAAT ACAAACATGGTGAAGCTCTTACTGGATCGAGGCGGTCAGATCGATGCCAAAACTAGGGATGGGTTGACAC CACTTCACTGTGCTGCACGAAGTGGGCATGACCAAGTGGTGGAACTTCTGTTGGAACGGGGTGCCCCCTT GCTGGCAAGGACTAAGAATGGGCTGTCTCCACTACACATGGCTGCCCAGGGAGACCACGTGGAATGTGTG AAGCACCTGTTACAGCACAAGGCACCTGTTGATGATGTCACCCTAGACTACCTGACAGCCCTCCACGTTG CTGCGCACTGTGGCCACTACCGTGTAACCAAACTCCTTTTAGACAAGAGAGCCAATCCGAACGCCAGAGC CCTGAATGGTTTTACTCCACTGCACATTGCCTGCAAGAAAAACCGCATCAAAGTCATGGAACTGCTGGTG AAATATGGGGCTTCAATCCAAGCTATAACAGAGTCTGGCCTCACACCAATACATGTGGCTGCCTTCATGG GCCACTTGAACATTGTCCTCCTTCTGCTGCAGAACGGAGCCTCTCCAGATGTCACTAACATTCGTGGTGA GACGGCACTACACATGGCAGCCCGAGCCGGGCAGGTGGAAGTGGTCCGATGCCTCCTGAGAAATGGTGCC CTTGTTGATGCCAGAGCCAGGGAGGAACAGACACCTTTACATATTGCCTCCCGCCTGGGTAAGACAGAAA TTGTCCAGCTGCTTCTACAACATATGGCTCATCCAGATGCGGCCACTACAAATGGGTACACACCACTGCA CATCTCTGCCCGGGAGGGCCAGGTGGATGTGGCATCAGTCCTATTGGAAGCAGGAGCAGCCCACTCCTTA GCTACCAAGAAGGGTTTTACTCCCCTGCATGTAGCAGCCAAGTATGGAAGCCTGGATGTGGCAAAACTTC TCTTGCAACGCCGTGCTGCCGCAGATTCTGCAGGGAAGAACGGCCTTACCCCGCTCCATGTTGCTGCTCA TTATGACAACCAGAAGGTGGCGCTGCTGTTACTGGAGAAGGGTGCTTCCCCTCATGCCACTGCCAAGAAT GGCTATACTCCGTTACATATTGCTGCCAAGAAGAATCAAATGCAGATAGCTTCCACACTCCTGAACTATG GAGCAGAGACAAACATTGTGACAAAGCAAGGAGTAACTCCACTCCATCTGGCCTCGCAGGAGGGGCACAC AGATATGGTTACCTTGCTTCTGGATAAGGGAGCCAATATCCACATGTCAACTAAGAGTGGACTCACATCC TTACACCTTGCAGCCCAGGAAGATAAAGTGAATGTTGCTGATATTCTCACCAAGCATGGAGCTGATCAGG ATGCTCATACAAAGCTTGGTTACACACCTTTAATTGTGGCCTGTCACTATGGAAATGTGAAAATGGTCAA CTTTCTTCTGAAGCAGGGAGCAAATGTTAACGCAAAAACCAAGAACGGCTACACGCCTTTGCACCAGGCC GCTCAGCAGGGTCACACGCACATCATCAACGTCCTGCTCCAGCATGGGGCCAAGCCCAACGCCACCACTG CGAATGGCAACACTGCCTTGGCGATTGCTAAGCGTCTGGGCTACATCTCCGTGGTCGACACCCTGAAGGT TGTGACTGAGGAGGTCACCACCACCACCACAACTATTACAGAAAAACACAAACTAAATGTACCTGAGACG ATGACTGAGGTTCTTGATGTTTCTGATGAAGAGGGTGATGACACAATGACTGGTGATGGGGGAGAATACC TTAGGCCTGAGGACCTAAAAGAACTGGGTGATGACTCACTACCCAGCAGTCAGTTCCTGGATGGTATGAA TTACCTGCGATACAGCTTGGAGGGAGGACGATCTGACAGCCTTCGATCCTTCAGTTCCGACAGGTCTCAC ACTCTGAGCCATGCCTCCTACCTGAGGGACAGTGCCGTGATGGATGACTCAGTTGTGATTCCCAGTCACC AGGTGTCAACTCTAGCCAAGGAGGCAGAAAGGAATTCTTATCGCCTAAGCTGGGGCACTGAGAACTTAGA CAACGTGGCTCTTTCTTCTAGTCCTATTCATTCAGGTTTCCTGGTTAGTTTTATGGTGGATGCCCGAGGT GGTGCTATGCGAGGATGCAGACACAATGGGCTCCGAATCATTATTCCACCTCGGAAATGTACTGCTCCAA CGCGAGTCACCTGCCGACTGGTCAAGCGCCACAGACTGGCAACAATGCCTCCAATGGTGGAAGGAGAAGG CCTGGCCAGTCGCCTGATCGAAGTTGGACCTTCTGGTGCTCAGTTCCTTGGTAAACTTCACCTGCCAACG GCTCCTCCCCCACTTAATGAGGGAGAAAGTTTGGTCAGCCGCATTCTTCAGCTGGGGCCTCCTGGAACCA AATTCCTTGGGCCTGTGATCGTGGAGATCCCTCACTTTGCGGCCCTTCGAGGAAAGGAAAGGGAACTGGT GGTCCTGCGCAGTGAGAATGGGGACAGCTGGAAAGAGCATTTCTGTGACTACACTGAAGATGAATTGAAT GAAATTCTTAACGGCATGGATGAAGTACTGGATAGCCCAGAAGACCTAGAAAAGAAACGAATCTGCCGCA TCATCACCCGAGACTTCCCACAGTACTTTGCAGTGGTGTCTCGTATCAAACAGGACAGCAATCTGATTGG CCCAGAAGGAGGTGTACTGAGCAGCACAGTGGTGCCCCAGGTGCAGGCCGTCTTCCCAGAGGGGGCACTC ACCAAGCGGATCCGCGTAGGCCTGCAGGCTCAACCTATGCACAGTGAGCTGGTTAAGAAGATCCTAGGCA ACAAAGCTACCTTCAGCCCTATAGTCACTTTGGAACCTAGAAGAAGAAAATTCCACAAACCAATTACCAT GACCATTCCTGTCCCCAAAGCTTCAAGTGATGTCATGTTGAATGGTTTTGGGGGAGATGCACCAACCTTA 119Patent Atty. Dkt. No.150-35-PCT AGATTACTATGCAGCATAACAGGTGGAACCACCCCTGCCCAGTGGGAAGATATTACAGGAACTACGCCAT TAACATTTGTCAATGAATGTGTTTCCTTTACAACAAACGTGTCTGCCAGGTTCTGGCTGATAGATTGTCG ACAGATCCAGGAATCCGTTACTTTTGCATCACAAGTATACAGAGAAATTATCTGCGTACCTTATATGGCC AAATTTGTAGTGTTTGCCAAATCACATGACCCCATTGAAGCCAGGTTGAGGTGTTTCTGCATGACTGATG ATAAAGTGGATAAGACCCTTGAACAACAAGAAAATTTTGCTGAGGTGGCCAGAAGCAGGGATGTGGAGGT GTTAGAAGGAAAACCCATCTACGTTGATTGTTTCGGCAACTTGGTACCATTAACTAAAAGTGGCCAGCAT CATATATTCAGTTTTTTTGCCTTCAAAGAAAATAGACTTCCTCTATTTGTCAAGGTACGCGATACGACTC AGGAACCTTGCGGACGACTATCATTTATGAAGGAGCCAAAATCCACGAGAGGCCTGGTGCATCAAGCTAT TTGCAACTTAAACATCACTTTGCCGATTTATACAAAGGAATCAGAGTCAGATCAAGAACAGGAGGAAGAG ATCGATATGACATCAGAAAAAAATGATGAGACAGAATCTACAGAAACATCTGTCCTGAAAAGTCACCTGG TTAATGAAGTTCCTGTCCTAGCAAGTCCGGACTTGCTCTCTGAAGTTTCTGAGATGAAACAAGATTTGAT CAAAATGACCGCCATCTTGACCACAGATGTGTCTGATAAGGCAGGTTCTATTAAAGTGAAGGAGCTGGTG AAGGCTGCTGAGGAAGAGCCAGGAGAGCCTTTTGAAATCGTTGAAAGAGTTAAAGAGGACTTAGAGAAAG TGAATGAAATCCTGAGAAGTGGAACCTGCACAAGAGATGAAAGCAGTGTGCAGAGCTCTCGGTCTGAGAG AGGATTAGTTGAAGAGGAATGGGTTATTGTCAGTGATGAGGAAATAGAAGAGGCTAGGCAAAAAGCACCT TTAGAAATCACTGAATATCCATGTGTAGAAGTTAGAATAGATAAAGAGATCAAAGGAAAAGTAGAGAAAG ACTCAACTGGGCTAGTGAACTACCTTACTGATGATCTGAATACCTGTGTGCCTCTTCCCAAAGAGCAGCT GCAGACAGTTCAAGATAAGGCAGGGAAGAAATGTGAGGCTCTGGCTGTTGGCAGGAGCTCTGAAAAGGAA GGGAAAGACATACCCCCAGATGAGACACAGAGTACACAGAAACAGCACAAACCAAGCTTGGGAATAAAGA AGCCAGTAAGAAGGAAATTAAAAGAAAAGCAGAAACAAAAAGAGGAAGGTTTACAAGCTAGTGCAGAGAA AGCTGAACTTAAAAAAGGTAGTTCAGAAGAGTCATTAGGTGAAGACCCAGGTTTAGCCCCTGAACCCCTT CCCACTGTCAAGGCCACATCTCCTTTGATAGAAGAAACTCCCATTGGTTCCATAAAGGACAAAGTAAAGG CCCTTCAGAAGCGAGTGGAAGATGAACAGAAAGGTCGAAGCAAGTTGCCCATCAGAGTCAAAGGCAAGGA GGACGTGCCAAAAAAGACCACCCACAGGCCACATCCAGCTGCGTCACCCTCTCTGAAGTCAGAGAGACAT GCGCCAGGGTCTCCCTCCCCTAAAACAGAAAGACACTCTACTCTTTCCTCTTCCGCAAAAACTGAAAGGC ACCCTCCAGTATCACCATCAAGTAAAACTGAGAAACACTCACCTGTGTCACCCTCTGCAAAAACGGAAAG ACATTCACCTGCGTCATCATCGAGTAAAACTGAGAAACACTCACCTGTATCACCCTCGACAAAAACTGAA AGGCACTCTCCTGTGTCATCTACAAAAACAGAAAGACACCCACCTGTTTCGCCTTCAGGCAAAACAGACA AACGTCCACCTGTATCGCCCTCCGGGAGGACAGAAAAACACCCGCCAGTATCGCCTGGGAGAACAGAAAA ACGCTTGCCTGTTTCACCCTCCGGAAGAACGGACAAGCACCAACCTGTATCAACAGCTGGGAAAACTGAG AAGCACCTGCCTGTGTCACCTTCTGGCAAAACAGAAAAGCAACCACCTGTATCCCCCACTTCAAAAACAG AGAGGATTGAGGAAACCATGTCTGTTCGGGAGCTGATGAAGGCTTTCCAGTCAGGTCAGGACCCTTCTAA ACATAAAACTGGACTCTTTGAGCACAAATCAGCAAAACAAAAGCAGCCACAAGAGAAAGGTAAAGTTCGG GTAGAAAAAGAAAAGGGGCCGATACTAACCCAGAGAGAAGCTCAGAAAACAGAGAATCAGACAATCAAAC GAGGCCAGAGACTCCCGGTAACGGGCACAGCAGAATCCAAAAGAGGAGTTCGTGTTTCCTCCATAGGAGT TAAGAAAGAAGATGCAGCTGGAGGAAAGGAGAAAGTTCTCAGCCACAAAATACCTGAACCTGTTCAGTCA GTGCCTGAAGAAGAAAGCCACAGAGAGAGCGAAGTGCCCAAAGAAAAGATGGCTGATGAGCAGGGAGACA TGGATCTACAGATCAGCCCAGATAGGAAAACCTCCACTGACTTCTCTGAGGTCATTAAGCAAGAGTTGGA AGACAATGACAAATACCAACAATTCCGCCTGAGTGAGGAGACAGAAAAGGCACAGCTTCACTTAGACCAA GTACTCACTAGTCCTTTCAACACAACATTTCCACTCGACTACATGAAAGATGAGTTCCTTCCAGCTCTGT CTTTACAAAGCGGTGCTTTAGATGGCAGTTCTGAAAGCCTAAAGAATGAGGGGGTAGCCGGCTCTCCGTG TGGCAGCCTGATGGAGGGGACCCCTCAGATTAGTTCAGAAGAAAGCTATAAGCATGAAGGCCTAGCAGAG ACCCCTGAGACGAGCCCAGAAAGCCTTTCTTTCTCACCAAAGAAAAGTGAGGAGCAAACTGGGGAAACAA AGGAAAGCACCAAGACAGAAACCACCACAGAAATTCGTTCAGAAAAAGAGCATCCCACGACCAAAGACAT TACTGGTGGCTCTGAAGAGCGAGGTGCCACAGTCACTGAGGACTCAGAGACCTCTACTGAGAGTTTTCAG AAAGAGGCCACTCTAGGCTCTCCCAAAGACACAAGCCCTAAAAGACAAGATGATTGCACAGGCAGCTGTA GTGTAGCATTAGCTAAAGAGACACCTACAGGACTGACTGAGGAGGCAGCCTGTGATGAAGGTCAACGTAC CTTTGGTAGTTCAGCCCACAAGACACAAACTGATAGTGAGGTTCAAGAATCCACAGCCACCTCAGACGAG ACAAAGGCCTTGCCGCTGCCTGAGGCTTCTGTAAAGACAGATACAGGAACTGAATCAAAACCTCAGGGAG TCATTAGAAGTCCCCAAGGGTTAGAACTTGCACTCCCTAGCCGAGATAGCGAAGTCCTCAGCGCTGTGGC TGATGACTCATTAGCAGTGAGCCACAAAGACTCTCTGGAAGCCAGCCCTGTGCTAGAAGATAACTCTTCA CACAAAACCCCTGATTCTCTGGAGCCAAGTCCTCTGAAAGAATCCCCTTGCCGTGACTCTCTGGAAAGCA GCCCTGTTGAACCAAAGATGAAGGCTGGAATTTTTCCAAGTCACTTTCCTCTTCCTGCAGCTGTTGCCAA AACAGAACTCTTGACGGAAGTGGCCTCTGTGCGGTCCCGGCTACTCCGAGACCCTGATGGCAGTGCTGAG GATGACAGTCTTGAGCAGACATCGCTCATGGAGAGCTCAGGGAAGAGCCCCCTTTCTCCTGACACCCCCA GCTCTGAAGAAGTCAGCTATGAGGTTACACCCAAAACCACAGATGTAAGTACACCAAAACCAGCTGTGAT TCATGAATGTGCAGAGGAGGATGATTCAGAAAACGGGGAGAAAAAGAGGTTCACACCTGAAGAGGAGATG TTTAAAATGGTAACCAAAATCAAAATGTTTGATGAACTTGAACAAGAAGCAAAGCAGAAAAGGGACTACA AAAAAGAACCCAAACAAGAAGAATCTTCTTCATCTTCTGACCCAGATGCTGACTGTTCAGTAGATGTGGA TGAACCAAAACATACAGGCAGTGGGGAGGATGAAAGTGGTGTCCCTGTGTTAGTAACTTCGGAGAGCAGG TT CCPatent Atty. Dkt. No.150-35-PCT AGAAGAAGTACAATTCCAGCCTGTCGTTTCCAAACAATATACTTTCAAGATGAATGAAGATACTCAGGAA GAGCCAGGCAAATCAGAAGAAGAAAAAGATTCTGAATCCCATTTAGCTGAAGACCGTCATGCTGTTTCCA CTGAGGCTGAAGACAGGTCTTATGATAAGCTAAACAGAGACACTGATCAGCCAAAAATCTGTGATGGCCA TGGATGTGAGGCCATGAGTCCTAGCAGCTCAGCTGCTCCTGTCTCTTCAGGTCTACAGAGTCCGACTGGT GATGATGTTGATGAACAGCCAGTCATCTATAAAGAATCATTAGCTCTCCAAGGCACTCATGAAAAAGACA CAGAGGGAGAAGAGCTTGATGTTTCTAGAGCAGAATCTCCACAAGCAGATTGCCCCAGTGAAAGCTTTTC ATCTTCATCCTCTTTGCCTCATTGTTTGGTATCTGAAGGAAAAGAATTAGATGAAGACATATCTGCCACA TCTTCTATTCAAAAAACAGAGGTCACAAAAACTGATGAAACATTTGAGAACTTACCAAAGGACTGCCCCT CTCAAGACTCATCCATTACTACTCAAACAGATAGATTTTCCATGGATGTTCCCGTGTCTGACCTAGCTGA GAATGATGAAATCTATGATCCACAAATCACTAGCCCTTATGAAAATGTCCCTTCCCAATCTTTTTTCTCT AGTGAAGAAAGCAAAACCCAAACAGATGCAAATCACACCACAAGTTTTCACTCTTCTGAAGTGTATTCTG TTACCATCACATCCCCTGTTGAAGACGTTGTAGTGGCAAGCTCCTCTAGTGGAACTGTTTTAAGCAAAGA ATCTAATTTTGAGGGCCAGGACATAAAAATGGAATCCCAACAGGAAAGTACCTTGTGGGAAATGCAATCA GACAGTGTCTCTTCATCTTTCGAGCCTACTATGTCCGCTACAACAACAGTTGTTGGTGAACAAATAAGCA AAGTCATCATCACAAAAACTGATGTGGATTCTGATTCTTGGAGTGAAATTCGGGAAGACGATGAAGCCTT TGAGGCTCGTGTGAAAGAGGAAGAACAAAAGATATTTGGTTTGATGGTAGACAGACAATCACAGGGTACC ACCCCTGACACCACTCCTGCTAGGACCCCAACTGAAGAGGGGACCCCAACAAGTGAGCAAAACCCATTTC TGTTTCAGGAAGGAAAATTGTTTGAAATGACCCGAAGTGGTGCCATTGATATGACCAAAAGGTCCTATGC AGATGAAAGTTTTCACTTTTTCCAAATTGGTCAAGAATCCAGGGAAGAGACTCTCTCTGAAGATGTGAAA GAAGGGGCTACTGGGGCTGATCCCCTACCGCTGGAGACATCAGCTGAATCACTAGCACTTTCAGAATCAA AAGAAACAGTGGATGATGAGGCAGACTTACTTCCAGATGACGTGAGTGAGGAAGTAGAGGAAATACCTGC TTCGGATGCTCAACTTAACTCCCAAATGGGGATTTCAGCCTCCACTGAAACACCTACAAAAGAAGCTGTT AGTGTAGGGACCAAGGACCTCCCCACCGTGCAAACGGGTGATATACCTCCTCTCTCTGGTGTAAAGCAGA TATCCTGCCCCGACTCTTCTGAACCAGCTGTACAAGTCCAGTTAGATTTTTCCACACTCACCAGGTCTGT TTATTCAGATAGGGGTGATGATTCTCCCGATTCTTCCCCAGAAGAACAGAAATCAGTAATCGAGATTCCT ACTGCACCCATGGAGAATGTGCCTTTTACTGAAAGCAAATCCAAAATTCCTGTAAGGACTATGCCCACTT CCACCCCAGCACCTCCATCTGCAGAGTATGAGAGTTCAGTTTCTGAAGATTTTCTATCCAGTGTAGATGA GGAAAATAAGGCGGATGAAGCAAAACCAAAGTCCAAACTCCCTGTCAAAGTACCCCTCCAAAGAGTTGAA CAGCAGCTCTCAGATCTAGACACCTCTGTCCAGAAGACAGTGGCTCCTCAGGGACAGGACATGGCAAGCA TCGCACCAGATAATAGAAGCAAATCTGAATCTGATGCTAGTTCTTTGGATTCAAAGACCAAATGCCCAGT AAAAACCCGAAGTTACACTGAGACAGAAACAGAGAGCAGAGAGAGGGCCGAGGAACTTGAGTTAGAATCA GAAGAAGGGGCCACAAGACCAAAGATACTTACATCCCGATTGCCAGTTAAGAGCAGAAGCACTACATCTT CCTGCAGGGGGGGCACGAGCCCCACAAAAGAAAGTAAGGAGCATTTCTTTGACCTTTACAGAAATTCCAT AGAATTCTTTGAGGAGATTAGTGATGAGGCTTCCAAATTAGTGGATAGGCTGACACAGTCAGAGAGGGAG CAGGAAATAGTTTCAGACGATGAAAGTAGTAGTGCCCTGGAAGTATCAGTAATTGAAAATCTGCCACCTG TTGAGACCGAGCACTCAGTTCCTGAGGACATCTTTGACACAAGGCCCATTTGGGATGAGTCTATTGAGAC TCTGATTGAACGCATCCCTGATGAAAATGGCCATGACCATGCTGAAGATCCACAGGATGAGCAGGAACGG ATCGAGGAAAGGCTGGCTTATATTGCTGATCACCTTGGCTTCAGCTGGACAGAATTAGCAAGAGAACTGG ATTTCACTGAGGAGCAAATTCATCAAATTCGAATTGAAAATCCCAACTCTCTTCAAGACCAGAGTCATGC ACTGTTGAAGTACTGGCTAGAGAGGGATGGGAAACATGCTACAGATACCAACCTCGTTGAATGTCTCACC AAGATCAACCGAATGGATATTGTTCATCTCATGGAGACCAACACAGAACCTCTCCAGGAGCGCATCAGTC ATAGTTATGCAGAAATTGAACAGACCATTACACTGGATCATAGTGAAGGGTTCTCGGTACTTCAAGAGGA GTTATGCACTGCACAGCACAAGCAGAAAGAGGAGCAAGCTGTTTCTAAAGAAAGTGAGACCTGCGATCAC CCTCCTATCGTCTCAGAGGAAGACATTTCTGTTGGTTATTCCACTTTTCAGGATGGCGTCCCCAAAACTG AGGGGGACAGCTCAGCAACAGCACTCTTTCCCCAAACTCACAAGGAGCAAGTTCAACAGGATTTCTCAGG GAAAATGCAAGACCTGCCTGAAGAGTCATCTCTGGAATATCAGCAGGAATATTTTGTGACAACTCCAGGA ACAGAAACATCAGAGACTCAGAAGGCTATGATAGTACCCAGCTCTCCCAGCAAGACACCTGAGGAAGTTA GCACCCCTGCAGAGGAGGAGAAGCTGTACCTCCAGACCCCAACATCCAGCGAGCGGGGAGGCTCTCCCAT CATACAAGAACCCGAAGAGCCCTCAGAGCACAGAGAGGAGAGCTCTCCGCGGAAAACCAGCCTCGTAATA GTGGAGTCTGCCGATAACCAGCCTGAGACCTGTGAAAGACTCGATGAAGATGCAGCTTTTGAAAAGGGAG ACGATATGCCTGAAATACCCCCAGAAACAGTCACAGAAGAAGAATACATTGATGAGCATGGACACACCGT GGTAAAGAAGGTTACTAGGAAAATCATTAGGCGGTATGTATCCTCTGAAGGCACAGAGAAAGAAGAGATT ATGGTGCAGGGAATGCCACAGGAACCTGTCAACATCGAGGAAGGGGATGGCTATTCCAAAGTTATAAAGC GTGTTGTATTGAAGAGTGACACCGAGCAGTCAGAGGACAACAATGAGTAAAGCCATCACACAGAAGAGGG CTGTGGTGAAGGACCAGCATGGAAAACGCATTGACTTGGAGCACCTGGAGGATGTACCAGAAGCACTAGA CCAGGACGACCTCCAGCGCGATCTCCAGCAGCTCCTTCGGCATTTCTGCAAGGAGGACTTGAAGCAAGAG GCCAAGTGAGGGGCTGCCCAGTTCTCACACCAGAAACCACACATTCACTCAATATGCAGCTTCCTGTTTC AGTAGGGGAGTGACCTAACTGGCCTAATTAATGGGATACCCCGACATTTCCACTGTTAGCAAATATACGG CATTTTGCTTTAGTTTTCCCCCATCCTCTTTAACTATAAAGCTAATTTGTGACCAAAGATGGCATCCTTC ATACTGGATGCTGTATCCAATACTTTGTTGTGTCTGTGCTAACCTGGGAACTGGCCACCTCCATTGTTCT TTGCTTCTGCACAAGATCCATGAAAATCCATTGATCAGAAGAACTTCACCTGCAGACCTCTTCAAGTGAC ACTATGTAGGAATCCTTCCAAGGAATATCTATGTACAATGTATATAGCTGAAATGCTCAGATGAACAACA 121Patent Atty. Dkt. No.150-35-PCT TATTAAAATTAAAACCACTGCCTATTGTAACTACACTGGGCATCAGAATAAAAGGCCTCTAGAAATTGCT GAACAATGGTTAATTAAGATATTGCTAACACAATCGAGTGATAATACAGTTTTACTGCAAAAGAAGCACT TCAAACCTATTATGTCCTTAGAACTTCCAGAGTAGCCACTGCTCCCAGTTAAAGGTGGGTCAGTAGCCTT GCAGAACTGTCCTGAGAAGTTATTGCTGGTGCTGGCCAGCCATGGCTTAGGACTCCAACAGCCACTCTGA GGGAGGGGAGAAGGGAGCAGAGGCCACGCAGAATGAACCGATGGGGTATTCAGTTGCTGGCAGCTACATT GTGTGGCATTCTAGCATCTTCAGGTCTTTAGATCTTGGACAAGTTGGCAGGGTATTTTAAAAGCTATAAC TACTGTAGTTTTCCAGTTTTCATTGCTGCTTTAGCAAACCACGCTGTCTTACAGTGGTACTTTCTTCTGG CCACTGCACTGTAGATAATTCATTGGAAACAAGATTTACCCACTACATAAAAGGTTAAACTCCTTCAGTA TGTTGGAGTGGTTTCTTTTTTTTTTTCTTTCTTTCTTTTTTTTCTTCAGGTTTATATCTTCTCTAATACC TGCATGTGGCGTTTAAAAATCAAGACCACGGTCAAACCCCTCTTCTAATCACATTAATTGTTTCCATTCT TTTTACCCTGAGTGAGCACTTTTCACTTTCCAGCTAGGTCTGTTTTTCAGCTTGCAGACAAGATTGAGAA ATCCTTGAAAATTTGGTTTTGGTTAAAATTTTTGGTTTATTTATTTGAAATCCACACTCCCTTGGAAACT CTTAAGTGCATTTGTGCACTTCTGTTTGTTTGTCTCAAAGAAGGGACTGTAACAATCTGAGTAATTTCCA TGTCCTCTTCCTTATTCCTCTAGTGGTTGAAGCTGTGTAGCATTTTAACATATATATATTCACAAATATA TTCATATAAACAGTATACATTTTGAATCAGTCATTTGTTAAAGAAAAGTATATTCAATGAAGATGAAATT TAAATAAAAAAGGACAGAGTCTATCCTCCAGGGATTGAACATTTTCCAATTATCTGGTCTTTTCCTGTTG TGCAAAAATGACTCATTGCTCCGAATGTCAAAAACAAATGCGACAAACAATGGCACTTCATCATTTAAAG TAATGTTGCCAAGAGAAAAAATTTCCTGGGAGGGAGGTTTCCCACAAGCCAAATCTCCTAAGCCTCAAAT GCTAGCACTTTTTGGCAGTTGGATAGGAAATGAGACATTCTTTGGCAGCCAAAATAAGAGAGGCCGATGG TGAAACTTTTTGAGACACCCTATGGCCTTCTTGTCAAAACCTTCACTGGAGCTCAAGAAAAGCATTTCTG TTGTGTTATTTGCAGTGCAGATGATGTCTGTGTAACAACATAATGGTTATTCACCTTTTTTTGATTTTGA TTTTTGCTGTGTTATCAAAAACTTGAATACTGTGAGAAGAAGTGAATTTTCAGTTGACGAATCAGCATCT TGTTCCCATGGTGATAACACTAATTGAATATATCTATGAGGGCATGTATTAGTTAATGGAAAAAAAAATA CAACACTAACAATACATAGCTGCAATGTGTACAATGGCTGATTTAATTAAATAAAATGTACAAGTGTTAA ATGTG ANK2, NP001139.3 ankyrin-2 isoform 1; AA; Homo sapiens (SEQ ID NO:4) YLKGGIDINTCNQNGLNALHL GANINAQSQNGFTPLYMAAQENHIDVVKYLLENGANQSTATEDGFTPLAVALQQGHNQAVAILLENDTKGKVRLPALHIAARKDDTKSAAL LLQNDHNADVQSKMMVNRTTESGFTPLHIAAHYGNVNVATLLLNRGAAVDFTARNGITPLHVASKRGNTN MVKLLLDRGGQIDAKTRDGLTPLHCAARSGHDQVVELLLERGAPLLARTKNGLSPLHMAAQGDHVECVKH LLQHKAPVDDVTLDYLTALHVAAHCGHYRVTKLLLDKRANPNARALNGFTPLHIACKKNRIKVMELLVKY GASIQAITESGLTPIHVAAFMGHLNIVLLLLQNGASPDVTNIRGETALHMAARAGQVEVVRCLLRNGALV DARAREEQTPLHIASRLGKTEIVQLLLQHMAHPDAATTNGYTPLHISAREGQVDVASVLLEAGAAHSLAT KKGFTPLHVAAKYGSLDVAKLLLQRRAAADSAGKNGLTPLHVAAHYDNQKVALLLLEKGASPHATAKNGY TPLHIAAKKNQMQIASTLLNYGAETNIVTKQGVTPLHLASQEGHTDMVTLLLDKGANIHMSTKSGLTSLH LAAQEDKVNVADILTKHGADQDAHTKLGYTPLIVACHYGNVKMVNFLLKQGANVNAKTKNGYTPLHQAAQ QGHTHIINVLLQHGAKPNATTANGNTALAIAKRLGYISVVDTLKVVTEEVTTTTTTITEKHKLNVPETMT EVLDVSDEEGDDTMTGDGGEYLRPEDLKELGDDSLPSSQFLDGMNYLRYSLEGGRSDSLRSFSSDRSHTL SHASYLRDSAVMDDSVVIPSHQVSTLAKEAERNSYRLSWGTENLDNVALSSSPIHSGFLVSFMVDARGGA MRGCRHNGLRIIIPPRKCTAPTRVTCRLVKRHRLATMPPMVEGEGLASRLIEVGPSGAQFLGKLHLPTAP PPLNEGESLVSRILQLGPPGTKFLGPVIVEIPHFAALRGKERELVVLRSENGDSWKEHFCDYTEDELNEI LNGMDEVLDSPEDLEKKRICRIITRDFPQYFAVVSRIKQDSNLIGPEGGVLSSTVVPQVQAVFPEGALTK RIRVGLQAQPMHSELVKKILGNKATFSPIVTLEPRRRKFHKPITMTIPVPKASSDVMLNGFGGDAPTLRL LCSITGGTTPAQWEDITGTTPLTFVNECVSFTTNVSARFWLIDCRQIQESVTFASQVYREIICVPYMAKF VVFAKSHDPIEARLRCFCMTDDKVDKTLEQQENFAEVARSRDVEVLEGKPIYVDCFGNLVPLTKSGQHHI FSFFAFKENRLPLFVKVRDTTQEPCGRLSFMKEPKSTRGLVHQAICNLNITLPIYTKESESDQEQEEEID MTSEKNDETESTETSVLKSHLVNEVPVLASPDLLSEVSEMKQDLIKMTAILTTDVSDKAGSIKVKELVKA AEEEPGEPFEIVERVKEDLEKVNEILRSGTCTRDESSVQSSRSERGLVEEEWVIVSDEEIEEARQKAPLE ITEYPCVEVRIDKEIKGKVEKDSTGLVNYLTDDLNTCVPLPKEQLQTVQDKAGKKCEALAVGRSSEKEGK DIPPDETQSTQKQHKPSLGIKKPVRRKLKEKQKQKEEGLQASAEKAELKKGSSEESLGEDPGLAPEPLPT VKATSPLIEETPIGSIKDKVKALQKRVEDEQKGRSKLPIRVKGKEDVPKKTTHRPHPAASPSLKSERHAP GSPSPKTERHSTLSSSAKTERHPPVSPSSKTEKHSPVSPSAKTERHSPASSSSKTEKHSPVSPSTKTERH SPVSSTKTERHPPVSPSGKTDKRPPVSPSGRTEKHPPVSPGRTEKRLPVSPSGRTDKHQPVSTAGKTEKH LPVSPSGKTEKQPPVSPTSKTERIEETMSVRELMKAFQSGQDPSKHKTGLFEHKSAKQKQPQEKGKVRVE KEKGPILTQREAQKTENQTIKRGQRLPVTGTAESKRGVRVSSIGVKKEDAAGGKEKVLSHKIPEPVQSVP EEESHRESEVPKEKMADEQGDMDLQISPDRKTSTDFSEVIKQELEDNDKYQQFRLSEETEKAQLHLDQVL TSPFNTTFPLDYMKDEFLPALSLQSGALDGSSESLKNEGVAGSPCGSLMEGTPQISSEESYKHEGLAETP ETSPESLSFSPKKSEEQTGETKESTKTETTTEIRSEKEHPTTKDITGGSEERGATVTEDSETSTESFQKE ATLGSPKDTSPKRQDDCTGSCSVALAKETPTGLTEEAACDEGQRTFGSSAHKTQTDSEVQESTATSDETK ALPLPEASVKTDTGTESKPQGVIRSPQGLELALPSRDSEVLSAVADDSLAVSHKDSLEASPVLEDNSSHK TPDSLEPSPLKESPCRDSLESSPVEPKMKAGIFPSHFPLPAAVAKTELLTEVASVRSRLLRDPDGSAEDD 122Patent Atty. Dkt. No.150-35-PCT SLEQTSLMESSGKSPLSPDTPSSEEVSYEVTPKTTDVSTPKPAVIHECAEEDDSENGEKKRFTPEEEMFK MVTKIKMFDELEQEAKQKRDYKKEPKQEESSSSSDPDADCSVDVDEPKHTGSGEDESGVPVLVTSESRKV SSSSESEPELAQLKKGADSGLLPEPVIRVQPPSPLPSSMDSNSSPEEVQFQPVVSKQYTFKMNEDTQEEP GKSEEEKDSESHLAEDRHAVSTEAEDRSYDKLNRDTDQPKICDGHGCEAMSPSSSAAPVSSGLQSPTGDD VDEQPVIYKESLALQGTHEKDTEGEELDVSRAESPQADCPSESFSSSSSLPHCLVSEGKELDEDISATSS IQKTEVTKTDETFENLPKDCPSQDSSITTQTDRFSMDVPVSDLAENDEIYDPQITSPYENVPSQSFFSSE ESKTQTDANHTTSFHSSEVYSVTITSPVEDVVVASSSSGTVLSKESNFEGQDIKMESQQESTLWEMQSDS VSSSFEPTMSATTTVVGEQISKVIITKTDVDSDSWSEIREDDEAFEARVKEEEQKIFGLMVDRQSQGTTP DTTPARTPTEEGTPTSEQNPFLFQEGKLFEMTRSGAIDMTKRSYADESFHFFQIGQESREETLSEDVKEG ATGADPLPLETSAESLALSESKETVDDEADLLPDDVSEEVEEIPASDAQLNSQMGISASTETPTKEAVSV GTKDLPTVQTGDIPPLSGVKQISCPDSSEPAVQVQLDFSTLTRSVYSDRGDDSPDSSPEEQKSVIEIPTA PMENVPFTESKSKIPVRTMPTSTPAPPSAEYESSVSEDFLSSVDEENKADEAKPKSKLPVKVPLQRVEQQ LSDLDTSVQKTVAPQGQDMASIAPDNRSKSESDASSLDSKTKCPVKTRSYTETETESRERAEELELESEE GATRPKILTSRLPVKSRSTTSSCRGGTSPTKESKEHFFDLYRNSIEFFEEISDEASKLVDRLTQSEREQE IVSDDESSSALEVSVIENLPPVETEHSVPEDIFDTRPIWDESIETLIERIPDENGHDHAEDPQDEQERIE ERLAYIADHLGFSWTELARELDFTEEQIHQIRIENPNSLQDQSHALLKYWLERDGKHATDTNLVECLTKI NRMDIVHLMETNTEPLQERISHSYAEIEQTITLDHSEGFSVLQEELCTAQHKQKEEQAVSKESETCDHPP IVSEEDISVGYSTFQDGVPKTEGDSSATALFPQTHKEQVQQDFSGKMQDLPEESSLEYQQEYFVTTPGTE TSETQKAMIVPSSPSKTPEEVSTPAEEEKLYLQTPTSSERGGSPIIQEPEEPSEHREESSPRKTSLVIVE SADNQPETCERLDEDAAFEKGDDMPEIPPETVTEEEYIDEHGHTVVKKVTRKIIRRYVSSEGTEKEEIMV QGMPQEPVNIEEGDGYSKVIKRVVLKSDTEQSEDNNE BICD1, NM_001714.4 Homo sapiens BICD cargo adaptor 1 (BICD1), transcript variant 1, mRNA; DNA; Homo sapiens (SEQ ID NO:5) ATCATTCCGCACCGGCTGCTGCAGGGCCAGAGGGAGCAGGTGGAGCGAGAGAGCGAGCCGCGAGCCGGAG CGCGCCAGACCCAGGGCGAGACTGCAGTGACGCGGCCCGGGAGACATGGCGGACGGGCGTCTCTGAATAA GCAGAATCCGGAGCCCCTCGCTACCCGCGGCCGCCGCAGCCCGGGCCATGCCGCACGGCTGCTGACCGCA CGCAGGGGCCGGCCCCGAGGACACATGCGGCGGCCTTTGCCGCCTCGCCCCTGACCCTCTGCCCTGTTCT CCATGTTGCATTTCTCGTCAGTTTCTCGGGCGGTGTAGCTGCCGCTGCCACCAGAGCCGGCGGGGCATCG CGCTGCTCATTCATCCGGCCGCACTTTCTTTTCCGTTTCCACCCATCCCTTCCCATTTCCTTCTCCCTTT CCCCGCCAGCTTCGCATCCATCTCCCCCACCCCGTAACCCCCTCCTGCCTCCATCCACCGGGGCTATGGC CGCAGAAGAGGTATTGCAGACGGTGGACCATTATAAGACTGAGATAGAGAGGCTAACCAAGGAGCTCACG GAGACCACCCACGAGAAGATCCAGGCTGCCGAGTACGGGCTGGTGGTGCTGGAGGAGAAGCTGACCCTCA AACAGCAGTATGATGAACTGGAGGCTGAGTACGACAGCCTCAAACAGGAGCTGGAGCAGCTCAAAGAGGC ATTTGGGCAGTCCTTCTCCATCCACCGGAAGGTTGCTGAAGATGGAGAGACTCGGGAGGAAACGCTTCTG CAGGAGTCAGCATCGAAGGAGGCTTACTATCTGGGGAAGATCTTGGAGATGCAGAACGAGCTGAAACAGA GCCGGGCTGTGGTCACTAATGTACAGGCAGAAAACGAGAGGCTCACCGCAGTCGTGCAGGATCTGAAGGA GAACAATGAGATGGTGGAGCTACAGAGAATACGGATGAAGGATGAAATCCGAGAATATAAGTTCCGGGAG GCACGGCTCCTTCAGGACTATACTGAATTGGAAGAAGAAAATATCACATTGCAGAAACTAGTGTCCACGT TGAAGCAGAACCAGGTTGAATACGAAGGCTTAAAGCATGAGATTAAGCGATTTGAGGAGGAGACGGTACT GCTGAACAGCCAGCTGGAAGATGCCATCCGATTGAAAGAGATTGCTGAGCACCAACTGGAAGAAGCCCTC GAGACTTTAAAAAATGAAAGAGAGCAAAAGAACAACCTGCGGAAGGAGCTCTCCCAGTATATCAGCCTCA ATGATAACCATATCAGCATCTCAGTAGATGGACTCAAATTTGCCGAGGATGGGAGTGAACCAAACAATGA TGACAAAATGAACGGTCATATCCATGGGCCTCTTGTGAAACTGAATGGAGACTATCGGACTCCCACCTTA AGGAAAGGAGAGTCTCTGAACCCTGTCTCTGACTTATTCAGTGAGCTGAACATTTCAGAAATACAGAAGT TGAAGCAGCAGCTTATGCAGGTAGAGCGGGAAAAGGCCATTCTTTTGGCCAACCTACAGGAGTCACAGAC ACAGCTGGAACACACCAAGGGGGCACTGACGGAGCAGCATGAGCGGGTGCACCGGCTCACAGAGCACGTC AATGCCATGAGGGGCCTGCAAAGCAGCAAGGAGCTCAAGGCTGAGCTGGACGGGGAGAAGGGCCGGGACT CAGGGGAGGAGGCCCATGACTATGAGGTGGACATCAATGGTTTAGAGATCCTTGAATGCAAATACAGGGT GGCAGTAACTGAGGTGATTGATCTGAAAGCTGAAATTAAGGCCTTAAAGGAGAAATATAATAAATCTGTA GAAAACTACACTGATGAGAAGGCCAAGTATGAGAGTAAAATCCAGATGTATGATGAGCAGGTGACAAGCC TTGAGAAGACCACCAAGGAGAGTGGTGAGAAGATGGCCCACATGGAGAAGGAGTTGCAAAAGATGACCAG CATAGCCAACGAAAATCACAGTACCCTTAATACGGCCCAGGATGAGTTAGTGACATTCAGTGAGGAGTTA GCTCAGCTTTACCACCATGTGTGTCTATGTAATAATGAAACTCCCAACAGGGTCATGCTGGATTACTATA GGCAGAGCAGAGTCACCCGCAGTGGCAGCCTGAAAGGGCCCGATGATCCCAGAGGACTTTTGTCCCCACG ATTAGCCAGGCGGGGTGTGTCATCCCCGGTAGAAACAAGGACCTCATCTGAACCAGTTGCAAAAGAAAGC ACAGAGGCCAGCAAAGAACCAAGTCCAACTAAGACCCCCACAATCTCTCCTGTTATTACTGCCCCACCGT CATCTCCAGTATTGGATACAAGTGACATCCGCAAAGAGCCAATGAATATCTACAACCTTAATGCCATAAT CCGGGACCAAATCAAGCATCTGCAGAAAGCTGTGGACCGGTCCTTGCAACTGTCTCGTCAAAGAGCAGCG GCTCGGGAGCTAGCCCCCATGATTGATAAAGACAAGGAAGCCTTAATGGAAGAGATCCTCAAGCTAAAGT CCCTGCTGAGCACCAAACGGGAGCAGATCGCCACATTGAGGGCGGTGTTGAAAGCCAACAAGCAGACAGC TGAGGTGGCGCTAGCTAATCTCAAGAACAAATATGAAAATGAAAAAGCAATGGTGACTGAAACCATGACG AAGCTTAGAAATGAACTGAAGGCTTTGAAAGAAGATGCTGCAACCTTCTCATCCCTGAGAGCAATGTTTG 123Patent Atty. Dkt. No.150-35-PCT CAACAAGATGTGATGAATATGTCACCCAGTTGGATGAGATGCAGAGACAGTTAGCAGCTGCAGAGGATGA GAAGAAGACTCTGAACACTTTGTTACGAATGGCTATCCAGCAAAAACTCGCCCTGACCCAGAGGCTGGAG GACTTAGAGTTTGACCATGAGCAGTCCCGACGCAGCAAAGGCAAACTTGGAAAGAGCAAGATCGGCAGCC CTAAAGTAAGTGGGGAGGCATCAGTCACCGTGCCCACCATAGACACTTACCTCCTGCATAGTCAGGGCCC ACAGACACCCAACATTCGGGTCAGCAGTGGCACTCAGAGGAAAAGACAATTTTCACCTTCCCTTTGTGAT CAGAGCCGTCCCAGGACTTCAGGGGCTTCCTACCTACAGAATTTATTAAGAGTTCCCCCTGATCCCACCT CCACAGAATCATTTCTTCTGAAGGGCCCCCCTTCCATGAGTGAATTCATCCAAGGGCACCGGCTCAGCAA GGAAAAAAGGTTAACCGTGGCTCCACCAGATTGTCAGCAGCCTGCTGCCTCCGTACCGCCACAGTGCTCA CAACTAGCCGGGAGGCAAGACTGCCCAACTGTCAGTCCTGACACAGCTCTCCCTGAGGAGCAGCCACATT CCAGCTCCCAGTGCGCCCCTCTCCACTGTCTCTCCAAGCCTCCTCACCCCTAGTCTTCATCTCCTGTGGA CGAACATCTGGGGTGGAAGTTTTGTAGCCACACACAGGATACTGCCCAAGATCCAGCGGGTGTTTTCTTC TCGGTTGTTAGATGTACAATTGGATTAATGTCCATCGTTTTGGAAGACGAGAGAAAGTTGAGAAGAACAC GAAGCACAGACCCTGATGTGATAAAACATTTTGTGGTTTCTCTGAGTCACAGATAAACTTCTGCCATCAA ATGGCTACAGTTCATTTAAATTTAAAAAAAAGAAAAAAGAAACAGAAAACGTGTCTCAGATGGCTGGCTT TACCTCGATAGCATAAGAGAGACCTAAGACATGTAAAATACGTATATTGCAGTATCATCTTTCCTCACAC TCCAAATTCAGCTAGGGAAGTTGATTCCAATATGTTTGTCATTGATATTTATTTTGTACTTTATTTGCTA CATGATTTATGTCTATACAAATAATTTCTCTGAGGTGAATTTAATTCATTTATTTTCAAATAAGCATAAT TTGCTCAATTAAGTATGAGTTTGAATTTAGTTTGAAATCTGGAATTGGCCAGACTGTGGTCATTTTTCTT GCACAAAATGATAAATGAGGTGCATCAGAATGTTAACAATAACTGTATTTTGCTGCTACGCTGGTATTGT TTAGGCACTTACTTTCTAATCAGTAGCTCATTAACTGCTGGGTTTTGTTTTTGTATTTTTAACTAGAGTT CTTCACTGGACATTACTAAGTAAATCTAAGAAAGAGACTAAGTTATGATTTATTGACTTATTCAAGTTTT GATGGCATCTTTACTTTTATTTTTTCATTGCAGTTGAGTAGATGTACTGGTGCTGCTCCTTTGTATGTGT GTATGTGTGTGATAACGTTAAAGAAGGCTCAATAACTTGAAGGGAAAAAAATGGTGTGTTTATTTAATGA CCAGAATTTTTTTTACTTCTCCCAAAATCAGGGTCCTACTGAGTCTTTCCTGATAAAAGGTATCAAGTAC AAATGGGAAAATATATACATATATAGATGTAAGATAGCCTTTAATTAATTAATTTACCCAGAGAGTGTTC AAAGTTTGATTAAAATTGTATGTTTTGTTGTTGTTAGTTTTTTTCATAACGAATCTTCCTTGCCAAAAAA ACAATAGATAATAAACCTTAGCTCATTGTCTACTTTTGACAAACACTCAGGTGCCTACAAACATTCTATT ATCTTGAGATAATACATGTTCCTGGTTAATTTACAGATTCTGCTGGGTAACTTTTATGACTTGATTTAAG GCAGTGGATTTTCATAGCAAAATTTATTTTGCACATAATCTGACAAACAAGGAAAACAGCTAACTGAGCT GAAAGGTCTAACACTCTCGGGCTCCTTAACCATCAAGTGCTGCCCACACAATTGCTCCTAGCCCTGATTC CTTGTCTTTGTCAGGTAGCCTTAACTTATTTAAAACCATAAGGGTTTGACCTTTTCATATAAAGACATCT GTAACTTCTCTTCAAAACAAAAATGACCCTCACTGTTAACACAAAGGACAGTTACCAGTGTAGGGCACTG AGAAAGGAGATCCAGGAGCCACTCAGCTTATTGAGCGGACATGGGTGGCACAGAAATGGAGTGGTCCATC AGAGACCAAATGGTAAGTCGTAAAGCACATTGCAGGAGCTTTCGTTAGTCATACGCCTATTAAGTAGTGG TCGCTATTACCAAAGCAACCAGGACGTTTTGTGTTCTTTATATGAGTGCTATTTTCCACAGTGTCATTTA TTATGCAACGTGGAGTAAAGAGTTGAAATCTTCACCAAAATAAGGGTTCAGGTTAAAGTACAGAAACAGA AACAAAACGATTCGACATGAAGTTCCCAACCATAGCAGCCTAACCTTCTGCTCTTTTCTACCTGCATGGC CTTGCTGTTCCTAAACATTGTCTTCATTTCACTGGCGTTGTATCTGCCTAGTACCAGTATTAGTGAGACT GTGGATTTTATCAGAGTTCAATGAAAGAAAGCTTACCCCTGCCCTCACTTTGTGTTTTTTATTTTTCCCC CTTTCTCAAGCACCACGTATTTGGACCTGAGAAGTGGCATAGCTGCTAAGTTGACTTTTAATAAAAAACT GTTTGTGCCTGAGGGAAATATATGCCTTTTTAAAAAGTACCTCAGAACATGTTCGTAGATCGTCTCATCG GTTTTGTTTGGTGGGACTGGGAGTTCAGCAGGAAGTATTGTCTGTGTGTGATGACGGGGCAGTATTGCCA GTCGGCAATGTTGTATTTGCATTCTTTATCCCTAACTCTGAATCTAGGACTCCATGAAAAGCCGGGTCAC CCACAAAACATTTCTTCCAATACAAAGTGTATTATTACGTCTATTATAAACTAGTTTCATTTCAGTTATT TATCTTCATAGAGTGGGAAAGTCTTTTTCTGAAATACTAATTCTATGAAAATAATAATTTTAGTGAATCT TTGCCAAGAAGTTATAGAAACTTGGAAATAAATTTCTCATTTTCAGCACAAAATTAAGTGATAGTCCCTA AGCAGTAAGAGAGAATACCATGTATTTACACTGTGGCATCATTTAGTATAGTTTACACTGAGCCATATTT ATTTATAGGCATTTAAAGTGAATCAGTATGTGTAGTGTTGATAAAAATCAGTATCTGTAAAGATAACATC AGGAATTCAAAAGGAAATTGAAAAGGGGCAGAACTAGTGAGAACCAAAAAGAATGAACTCCAGTAAGACT AATTGAAGACATACTTGGAGAGGAAAAATAAACAGCAGAAATGCACTAAAAAATACTGGCTAATTATTGC AAACAGAGTGAGCAAAGATTAATGCTAACTAGTAAAAGTAGTTAGCAAAGTAAACAGGTAGTTTTTTAAA AGTAAGCACAATTACAATATTGAATAGTATGGAGAAATGCTTTTCTCCTGAGGATTTTCCTTAATCAAAA AATAAGAAGAAGCAATAAATTGTCTTTGGCCTGAGTGCTGAGTGGCATAAATAAAGGAGCTTGGCTTAAT CTTTCTGGTCCACACATAATCCATTAGATCCCATTCATATATCCAACTCTGGATTCTAATAAAATAATTT GGAGAACTTTGAGAAAAAGGAAAACTGTTAAATAAGAAAAGACCTATTTAGAAATTATACTTTAGTCTAA CGAAGAGGAGGTACAATAGTAGTCTTCAAGAAAAGAATATTTAACAAATGATAGATATCAGCTATAGATA TTGTTACTAAGTCTAGAATAAAAAAGGCTTCAGTGTGAAGGATGTATAGTAACTCTAGGAAAGAGATTTT TAACACTGGGAAATTAACGTGGAAATTGATAATCATAAAGAATATTTGTTTTGTAAAAATTGAATATCAT TGGTGGTCTAGTAAGTATTAAGTGGCAAGATAGGAGAATGCATTTCAGTTCTGGGAGCTCATAATCCTGT GATTCTTTTATTTTAAGTTTTAAAATACATTAAAATTTTACTGGTTAATCATAAAATATTTTATATTTGA AAATAGGATGGCAATCTTTATTTTTCCAAGATATTTGTTGGAAAAAAATGATCGTTGGTATTATTTTTTC TTTCAGCTATATTCCATGGTATCTTTAAAATTGTTCAGAATATAGGACTTTTACTAAAAAAATTCAATTG 124Patent Atty. Dkt. No.150-35-PCT TCAGAGTCTAAAAAAACAATGTCCTCAGGAATACTTCAGAAATAGAAGGTATGCAATCCCTTAGTGGGGG GCAAACACATTTCAGATTTCGTCTTTATTTAAAAGGATCTTCAGTCTACAACATTTGCTTTTTTCGTGCT TTGGAAAATATCCTTGTGCAGATAAGTTCTTCTGTTTGAAACAAGCATGAAACATTGGTCCAATAACCTA AGAATGTGGAGATTTCTTGATATTCTGTATTAATTAAAGTTCTCTACATGTCTCAAATGGAGATCACAAA ACATGAAAAGGAAGAAATGAAATATCTTTTCTTCTGGGATGAGTGTCAATTTTAATGTATAATTGTCATA ATCAATCAGCCAAAAGTTACAATCTGTCCCTCAGAGACATTGGGGGAAGCTGATGGATTTCCAGTAAGGA ACTGTGGTGGGTTCAAACTCAGGCTGCCACAAATACATTGATATGGTAGGTAGGAAGTAGGACTAAATTT GAAAGAAACTTATGGGATAAAGTTCACAATTTTAAAAAGGTTGCCCTCCAGTTTTTTTGTTTGTTTATAA ACTAGAGTGATTTTTAAGTAACCCTTATATTTAAGGCTGCAAAAAATGTACAAGAGTATGTTTTCAAGTA AAGGGAACATAATTCTTCAAAAAGCTGTTGAACTGGAGTTATGATAGGTTATGACAGAGAGCATGATCAG TGCTGATACTGACAAGTACTTTTTTACCTTAAAATCAACTTCTATGGAACTACAAGATCAATCTAGCTCC CGAGTGACATTTTCCATTGTCTGTAATAATGCCCTCGGATGAGTTGTGTCTAAAATTAAGTTCATCTTTA TTTATATGCGAACTTAACTGCCATAGTCCCTAATGTATTGCGTTTGTAACCTGATCGTATTATGTTTACA GCTGAAAGATTTCATCTAGACATGTCTTTCGTCCTTATTATTCAAAGTGTAATTGAAAGAGATATTTAGT ATTAAGACATGTTCCCCAATTGAGAATTTTCCAGAATATTCTACTTAAGAAGAAGAAGAGCAATTAACTG CCTTTAGTGTAAGGGCGAGAGTGCATAGAAATATGCAATGTAAAATGTTTGCATGAATTATTTCACATCA TGTAAGCTTTCCCATATTCATAAGATGAACACTATAGAAGTCTCATTTCTCTGTGATCTTCTGTCCATTA GGAAAGTAAGGAGATTGTTATCTATATCTAGTCTCCTTTCCATATTGAACTGCATGGCTCTAATCCTCAG TGTATTTTTATCCCTTCTCGAGTTATTTAAAATTTGCCCTATTTAAGCTGAAGCCTGGATAAACTGCTGA GCCAGATTATTCCTGTGATTGGAGTTTAATTGCTGTAGAACACTTGTTGAGAACACATTTTTTACTTTTT TTCTTTCAGAATTATTCCTCAATCATTGTTCTCTAATGAAAACACCGAGAAGTAAATCTGGTGCTTCTTA GTGTAAATATGTTTTTCTTTTTAAAAAGTCATTTTAAAACAAAGATGAGAGAACTATAAAGTAAGGGGAA ATATCATTTTATTTAAAAATAATTATTCAATGATAGATAATGGAGATACAGAATGACTCATTGGGTTCAT AGGTATGATTTGTGCAGCCAGTCTTAGAGGAAATACATCATTTTAACATTATTCCCACAAAATGTTAAAG CTCAATGGTTTGACTATGAGAGTCAAACAATTACTATTTGAAAATCTCTTATGACATTTTTATAATCTAC TCTGTTTTTATTTGCATGATTATGCTTATGTGATGAACCATCCATGATTCTGATATTGTATTTCTTTCCA GTATTAACATGTGTATTGTGTGGCCAACTCTGATTTGTACACCGTATTATTGTTGTAATGATTCAACTGT TCCTACATTTAATTGCAGTTTAATTATTATGCCTTTTGGGGTTAAATGATGTGAAGTGTTTCCACCTACT GATAAATACCATATGAAAACACGACTAAAAGACTGATTTAAGAAACTTGTTATTTTTAAAAATATGAATT TCAAAAGAAATGTTCTCAAAGACACATGCATTTATTTTAAATTCAAAAAATTCTTATGAATTTATTATTG CTTGTACTTTAACTTTTTTTATTGTAGACAATCCTAAGTGAATAATGTCTCATGGGAGAACACATGATAT GTGCTTGTATTTGTGTAATCTGATCATGCACTCAATGGTTGGAAAAGGCACTCCAGTGCTAAGAAAATAA CCAGAAGCCAATATATCGATTCTTATATCTCGGTTTATGTTACCAACTGAATATGGTGTAATGCATAACT TTTTCCAGTAAATAAACTGGTTATTTTTTGTTCATTTCA BICD1, NP_001705.2 protein bicaudal D homolog 1 isoform 1; AA; Homo sapiens(SEQ ID NO:6) MAAEEVLQTVDHYKTEIERLTKELTETTHEKIQAAEYGLVVLEEKLTLKQQYDELEAEYDSLKQELEQLK EAFGQSFSIHRKVAEDGETREETLLQESASKEAYYLGKILEMQNELKQSRAVVTNVQAENERLTAVVQDL KENNEMVELQRIRMKDEIREYKFREARLLQDYTELEEENITLQKLVSTLKQNQVEYEGLKHEIKRFEEET VLLNSQLEDAIRLKEIAEHQLEEALETLKNEREQKNNLRKELSQYISLNDNHISISVDGLKFAEDGSEPN NDDKMNGHIHGPLVKLNGDYRTPTLRKGESLNPVSDLFSELNISEIQKLKQQLMQVEREKAILLANLQES QTQLEHTKGALTEQHERVHRLTEHVNAMRGLQSSKELKAELDGEKGRDSGEEAHDYEVDINGLEILECKY RVAVTEVIDLKAEIKALKEKYNKSVENYTDEKAKYESKIQMYDEQVTSLEKTTKESGEKMAHMEKELQKM TSIANENHSTLNTAQDELVTFSEELAQLYHHVCLCNNETPNRVMLDYYRQSRVTRSGSLKGPDDPRGLLS PRLARRGVSSPVETRTSSEPVAKESTEASKEPSPTKTPTISPVITAPPSSPVLDTSDIRKEPMNIYNLNA IIRDQIKHLQKAVDRSLQLSRQRAAARELAPMIDKDKEALMEEILKLKSLLSTKREQIATLRAVLKANKQ TAEVALANLKNKYENEKAMVTETMTKLRNELKALKEDAATFSSLRAMFATRCDEYVTQLDEMQRQLAAAE DEKKTLNTLLRMAIQQKLALTQRLEDLEFDHEQSRRSKGKLGKSKIGSPKVSGEASVTVPTIDTYLLHSQ GPQTPNIRVSSGTQRKRQFSPSLCDQSRPRTSGASYLQNLLRVPPDPTSTESFLLKGPPSMSEFIQGHRL SKEKRLTVAPPDCQQPAASVPPQCSQLAGRQDCPTVSPDTALPEEQPHSSSQCAPLHCLSKPPHP CHRDL1, NM_001143981.2 Homo sapiens chordin like 1 (CHRDL1), transcript variant 1, mRNA; DNA; Homo sapiens (SEQ ID NO:7) AGACCTCGGACGAGAGCGCCCCGGGGAGCTCGGAGCGCGTGCACGCGTGGCAGACGGAGAAGGCCAGTGC CCAGCTTGAAGGTTCTGTCACCTTTTGCAGTGGTCCAAATGAGAAAAAAGTGGAAAATGGGAGGCATGAA ATACATCTTTTCGTTGTTGTTCTTTCTTTTGCTAGAAGGAGGCAAAACAGAGCAAGTAAAACATTCAGAG ACATATTGCATGTTTCAAGACAAGAAGTACAGAGTGGGTGAGAGATGGCATCCTTACCTGGAACCTTATG GGTTGGTTTACTGCGTGAACTGCATCTGCTCAGAGAATGGGAATGTGCTTTGCAGCCGAGTCAGATGTCC AAATGTTCATTGCCTTTCTCCTGTGCATATTCCTCATCTGTGCTGCCCTCGCTGCCCAGAAGACTCCTTA CCCCCAGTGAACAATAAGGTGACCAGCAAGTCTTGCGAGTACAATGGGACAACTTACCAACATGGAGAGC TGTTCGTAGCTGAAGGGCTCTTTCAGAATCGGCAACCCAATCAATGCACCCAGTGCAGCTGTTCGGAGGG AAACGTGTATTGTGGTCTCAAGACTTGCCCCAAATTAACCTGTGCCTTCCCAGTCTCTGTTCCAGATTCC TGCTGCCGGGTATGCAGAGGAGATGGAGAACTGTCATGGGAACATTCTGATGGTGATATCTTCCGGCAAC 125Patent Atty. Dkt. No.150-35-PCT CTGCCAACAGAGAAGCAAGACATTCTTACCACCGCTCTCACTATGATCCTCCACCAAGCCGACAGGCTGG AGGTCTGTCCCGCTTTCCTGGGGCCAGAAGTCACCGGGGAGCTCTTATGGATTCCCAGCAAGCATCAGGA ACCATTGTGCAAATTGTCATCAATAACAAACACAAGCATGGACAAGTGTGTGTTTCCAATGGAAAGACCT ATTCTCATGGCGAGTCCTGGCACCCAAACCTCCGGGCATTTGGCATTGTGGAGTGTGTGCTATGTACTTG TAATGTCACCAAGCAAGAGTGTAAGAAAATCCACTGCCCCAATCGATACCCCTGCAAGTATCCTCAAAAA ATAGACGGAAAATGCTGCAAGGTGTGTCCAGGTAAAAAAGCAAAAGAAGAACTTCCAGGCCAAAGCTTTG ACAATAAAGGCTACTTCTGCGGGGAAGAAACGATGCCTGTGTATGAGTCTGTATTCATGGAGGATGGGGA GACAACCAGAAAAATAGCACTGGAGACTGAGAGACCACCTCAGGTAGAGGTCCACGTTTGGACTATTCGA AAGGGCATTCTCCAGCACTTCCATATTGAGAAGATCTCCAAGAGGATGTTTGAGGAGCTTCCTCACTTCA AGCTGGTGACCAGAACAACCCTGAGCCAGTGGAAGATCTTCACCGAAGGAGAAGCTCAGATCAGCCAGAT GTGTTCAAGTCGTGTATGCAGAACAGAGCTTGAAGATTTAGTCAAGGTTTTGTACCTGGAGAGATCTGAA AAGGGCCACTGTTAGGCAAGACAGACAGTATTGGATAGGGTAAAGCAAGAAAACTCAAGCTGCAGCTGGA CTGCAGGCTTATTTTGCTTAAGTCAACAGTGCCCTAAAACTCCAAACTCAAATGCAGTCAATTATTCACG CCATGCACAGCATAATTTGCTCCTTTGTGTGGAGTGGTGTGTCAGCCCTTGAACATCTCCTCCAAAGAGA CTAGAAGAGTCTTAAATTATATGTGGGAGGAGGAGGGATAGAACATCACAACACTGCTCTAGTTTCTTGG AGAATCACATTTCTTTACAGGTTAAAGACAAACAAGACCCCAGGGTTTTTATCTAGAAAGTTATTCAAGT GAAAGAAAGAGAAGGGAATTGCTTAGTAGGAGTTCTGCAGTATAGAACAATTACTTGTATGAAATTATAC CTTTGAATTTTAGAATGTCATGTGTTCTTTTAAAAAAATTAGCTCCCCATCCTCCCTCCTCACTCCCTCC CTCCCTCCTTCTCTCTCTCTCTCTCTCTCCCTCCCTCTCTCACAGACACACACACACACACACACACACA CACACACACGCACGTCCACACTCACATTAAACGAAAGCTTTATTTGAAGCAAAGCTAGCCAAGATTCTAC GTTACTTTTCCCTTGACTGGATCCCAAGTAGCTTGGAAGTTTTTGTGCCCAGGAGAGTAAATAACTGTGA ACAAGAGGCTCTGCCCTTAGGTCTTTGTGGCTGTTTAAGTCACCAACAATAGAGTCAGGGTAAAGAATAA AAACACTTTCATAGCCTCATTCATTCACTTAGAAGTGGTAATAATTTTTCCCTAATGATACCACTTTTCT TTTCCCCCTGTACCTATGGGACTTCCAGAAAGAAGTTAAATTGAGTAAAATCATCAGAAACTGAATCCAT GTAAGAAAAAATAATTGTTGAAGAAAGAAGTTGATAGAATTCAAAAAGGCCATCTTTTTGCTTTCACATC AATAAAATTTACCAAGTAATAGATCAGTACTCACTAATATTTTTGAGACCATAGTTGTCTGGTCAGAAAA ATTATATTAAATTAGTAAATTCTAGAAGCTCTTTAAAAGGGAAGTTTTCCTTCTTCTCCAATTATAGGAG TTGATTTTTACTTTGCAAAGTGGCTCGGTCCTCATGAGCATCTGCATGTTGACTCTTCAGTTAAGAAAAT TGTTGTTCATTTAGGGAGGTGGATATTCTGATGAAGATCTTTATCCTAAACCTTCCTACTATCCTTGTCT TATTCATCAAGCAGATATTTTAGTCAAGAATTCCAGAGAAGGCTGCTCCTAAAATGTCTACTTGCAGCCC AATACCAGAGCATAAACTATCCATTCTGGGGTCTGGCTTTAGAAATCATCTTTGTGGGAAGACCTAATTC TTCACAGCAAGGATCTCAGGCATGCCTTCTAGATTTGTTCCCTCTGAGGGGCAGGAATGAACTGTAGAAA TGTTTTAAGGACCCAGAAACCCCATATGTCTCATTCCATGACTATAGGTGAGAGAATTCTTTCCTAAGAG GGTTTGATACCAATAGGGGAAAATGTAAAATGTTCAGTCTTTATGACAACCTGGCATAAAGGAGTCAATT CTTATGAAAGAGACACAAGGGCCTTATGGCCAGGGTTTCTTGGGACAAGACTCTCACCAGCACATCACAC ACGTTCTCCTTGGAAGAGAGAAGCAGTACATCCCGGTTGAGAGGTCACAAAGCATTAGTTTGTGTGTGTG TGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGGTAAAGGGGGGAAGGTGTTATGCGGCTGCTCC CTCCGTCCCAGAGGTGGCAGTGATTCCATAATGTGGAGACTAGTAACTAGATCCTAAGGCAAAGAGGTGT TTCTCCTTCTGGATGATTCATCCCAAAGCCTTCCCACCCAGGTGTTCTCTGAAAGCTTAGCCTTAAGAGA ACACGCAGAGAGTTTCCCTAGATATACTCCTGCCTCCAGGTGCTGGGACACACCTTTGCAAAATGCTGTG GGAAGCAGGAGCTGGGGAGCTGTGTTAAGTCAAAGTAGAAACCCTCCAGTGTTTGGTGTTGTGTAGAGAA TAGGACATAGGGTAAAGAGGCCAAGCTGCCTGTAGTTAGTAGAGAAGAATGGATGTGGTTCTTCTTGTGT ATTTATTTGTATCATAAACACTTGGAACAACAAAGACCATAAGCATCATTTAGCAGTTGTAGCCATTTTC TAGTTAACTCATGTAAACAAGTAAGAGTAACATAACAGTATTACCCTTTCACTGTTCTCACAGGACATGT ACCTAATTATGGTACTTATTTATGTAGTCACTGTATTTCTGGATTTTTAAATTAATAAAAAAGTTAATTT TGAAAAATCA CHRDL1, NP_001137453.1 chordin-like protein 1 isoform 1 precursor; AA; Homo sapiens(SEQ ID NO:8) MRKKWKMGGMKYIFSLLFFLLLEGGKTEQVKHSETYCMFQDKKYRVGERWHPYLEPYGLVYCVNCICSEN GNVLCSRVRCPNVHCLSPVHIPHLCCPRCPEDSLPPVNNKVTSKSCEYNGTTYQHGELFVAEGLFQNRQP NQCTQCSCSEGNVYCGLKTCPKLTCAFPVSVPDSCCRVCRGDGELSWEHSDGDIFRQPANREARHSYHRS HYDPPPSRQAGGLSRFPGARSHRGALMDSQQASGTIVQIVINNKHKHGQVCVSNGKTYSHGESWHPNLRA FGIVECVLCTCNVTKQECKKIHCPNRYPCKYPQKIDGKCCKVCPGKKAKEELPGQSFDNKGYFCGEETMP VYESVFMEDGETTRKIALETERPPQVEVHVWTIRKGILQHFHIEKISKRMFEELPHFKLVTRTTLSQWKI FTEGEAQISQMCSSRVCRTELEDLVKVLYLERSEKGHC CNIH3, NM_152495.2 Homo sapiens cornichon family AMPA receptor auxiliary protein 3 (CNIH3), trans variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:9) GC TC GC CG GCPatent Atty. Dkt. No.150-35-PCT CGCTCGGGCACCTCGCTGGACACTATCCGTTTGCGCCCCGGTGGCGCGGGAGGGTCCGGAGCGGAGCGCT CGTCTCTCCTCAGCGGTTTAGTGGAGAAAAGCAGAGAGCTCTTCCTGGGGCGAATGGGACCTCCTCCCTC GGTCCTCCGTGGAGTCGTCGCATCGCTTGTCGTGTTGGTCTCGAGGGGCTCACAGCTTGGCACTAATTTG CAGGTGTTCGCTGCTGATTTGGTTTCTTCTTCGATTTGCGGACGGTTCCCTCCAGCGACTCTCGACACAC GTTTTCCTGTCTTCGCCGGAGGGCCGGGTCTGGGGTCGCCGGAGCCTGCGGGAATCCAGCGCTTATTCGC TGACCCTCGAGTCGCTTCGCTAGCTGTGCGCCCTCCTGGGCACTAGCCTGGAGAGGAGCGTGCAGACGCG GCTCCTTGGAGGGAGTGCGGTCCTCTAGGGAGGCATCGGGCTCCTAGGGGCTTCTTGGCGTGTGTGGTGG GATTGGGGTCCGCCGGCCATGGCCTTCACTTTCGCTGCGTTCTGCTACATGCTGTCTCTGGTGCTGTGCG CTGCGCTCATCTTCTTCGCCATCTGGCACATAATTGCCTTTGATGAGTTAAGGACAGATTTTAAGAGCCC CATAGACCAGTGCAATCCTGTTCATGCGAGGGAACGGTTGAGGAACATCGAGCGCATCTGCTTCCTTCTG CGAAAGCTGGTGCTGCCAGAATACTCCATCCATAGCCTCTTCTGCATTATGTTCCTGTGTGCGCAAGAGT GGCTCACGCTGGGGCTGAATGTCCCTCTACTTTTCTATCACTTCTGGAGGTATTTCCACTGTCCAGCAGA TAGCTCAGAACTAGCCTACGACCCACCGGTGGTCATGAATGCCGACACTTTGAGTTACTGTCAGAAGGAG GCCTGGTGTAAGCTGGCCTTCTATCTCCTCTCCTTCTTCTACTACCTTTACTGCATGATCTACACTTTAG TGAGCTCTTAACGCAAAGACCATGCACATCATCAGAGACTGAGATGGGAGAGGCCTGAGACGGAGAGGTG CATTTCTGCTGGTGACTGGAGGAGGGACCAGAATGAGGATACGTGAGAAATAGACCCGGCAGGCAGTCAG ACTGAATGGGAGCTGGAATCACGCAGCAGCTGGGAGCCGAGTTAACCCTGCGTGTCTGTGTCACCCTGTT TGTCAATCTTTGGCATTCGAATTCCACACACGGGGTCCTAGAGCCCTTCTGAGCATCAGTGGTGTGGGGG AGTAGGTGACGAAACACTAGACCTCTCCTGAGAGAGAATTGCTGCTTCCTGAATCCACTTCATTGAACAG CACCTTGCAAGTTCAAATGAGTTCCTGGGAGCGGAGGCTGGAAGGCCACAAGGTGCTTGCTAAGGAACAG AATGACCCAGAGTCAAGGCCAAGTCTGCAGGGACCTGTTGAAAGCCTCGAGAATGTCTTGGCTGCCCAAG ACTCTTGTTGCCTTTCTTCCAAGCCATGGCCATGCCCTTTTTCTCAAATGGGAGGGGCTGGAGGGTGTGT GGGATTTGTCTTCAGCTGCAACCAGCCTTGAGCCTGCTGGGCTATTTTCAGCTGAGGAGGGGTGAATATA GGAAAAATGCATTTTTGAAACGTTTGCAACATGATCAAGGTGTTAGTTCTCCACCACACAAGTTGTATTC TTCTTTTGCCACCTCAAACCATCACAGAGTCTTTAAATGCAAATCAATTGGTCAATGCTAGTCAAAGCTA TGTTCTTACAAAAACCCCAGACAGCTCAGAGCTCAGAAAATCCTGTGGAGTGGCTGCTCTGTACCGTGGG CATCCGGCAGCCAGGAAGTGAGACAACATAATTATAACTTTGTTTTATGATGCTGCATCATTTGTACTGT TTAGGTCGACGTGAGGACATCATCTTATTTAGAATTTTCCGTTTGGCATTCTCTTTTGGGTGGGAGTTAT GCTGGGGGTTGTAAATAATGACAAGGCTGAGATTTTTATGATGTTTAAATTGGGCACAATGATTTTGACC TTATTCCCCAAACTTCTTTTCTTTTCTACTGTTTAACATACACAGGCTATTTATACACGTCCCCAGCTCC CATCTGAAACCTGTGACTCAGGTTTATGAATGGTGTTTGTGTAGCAACACATTGTGTGCTATGTTTATTA AAATGCAGCGACAACTTGA CNIH3, NP_689708.1 protein cornichon homolog 3 isoform 1; AA; Homo sapiens(SEQ ID NO:10) MAFTFAAFCYMLSLVLCAALIFFAIWHIIAFDELRTDFKSPIDQCNPVHARERLRNIERICFLLRKLVLP EYSIHSLFCIMFLCAQEWLTLGLNVPLLFYHFWRYFHCPADSSELAYDPPVVMNADTLSYCQKEAWCKLA FYLLSFFYYLYCMIYTLVSS COL11A1, NM_001854.4 Homo sapiens collagen type XI alpha 1 chain (COL11A1), transcript variant A, mRNA; DNA; Homo sapiens(SEQ ID NO:11) ACTGACGGCATGAAGCCTTTAGGGGCACACAGTACTCTCAGCTTGTTGGTGGAAGCCCCTCATCTGCCTT CATTCTGAAGGCAGGGCCCGGCAGAGGAAGGATCAGAGGGTCGCGGCCGGAGGGTCCCGGCCGGTGGGGC CAACTCAGAGGGAGAGGAAAGGGCTAGAGACACGAAGAACGCAAACCATCAAATTTAGAAGAAAAAGCCC TTTGACTTTTTCCCCCTCTCCCTCCCCAATGGCTGTGTAGCAAACATCCCTGGCGATACCTTGGAAAGGA CGAAGTTGGTCTGCAGTCGCAATTTCGTGGGTTGAGTTCACAGTTGTGAGTGCGGGGCTCGGAGATGGAG CCGTGGTCCTCTAGGTGGAAAACGAAACGGTGGCTCTGGGATTTCACCGTAACAACCCTCGCATTGACCT TCCTCTTCCAAGCTAGAGAGGTCAGAGGAGCTGCTCCAGTTGATGTACTAAAAGCACTAGATTTTCACAA TTCTCCAGAGGGAATATCAAAAACAACGGGATTTTGCACAAACAGAAAGAATTCTAAAGGCTCAGATACT GCTTACAGAGTTTCAAAGCAAGCACAACTCAGTGCCCCAACAAAACAGTTATTTCCAGGTGGAACTTTCC CAGAAGACTTTTCAATACTATTTACAGTAAAACCAAAAAAAGGAATTCAGTCTTTCCTTTTATCTATATA TAATGAGCATGGTATTCAGCAAATTGGTGTTGAGGTTGGGAGATCACCTGTTTTTCTGTTTGAAGACCAC ACTGGAAAACCTGCCCCAGAAGACTATCCCCTCTTCAGAACTGTTAACATCGCTGACGGGAAGTGGCATC GGGTAGCAATCAGCGTGGAGAAGAAAACTGTGACAATGATTGTTGATTGTAAGAAGAAAACCACGAAACC ACTTGATAGAAGTGAGAGAGCAATTGTTGATACCAATGGAATCACGGTTTTTGGAACAAGGATTTTGGAT GAAGAAGTTTTTGAGGGGGACATTCAGCAGTTTTTGATCACAGGTGATCCCAAGGCAGCATATGACTACT GTGAGCATTATAGTCCAGACTGTGACTCTTCAGCACCCAAGGCTGCTCAAGCTCAGGAACCTCAGATAGA TGAGTATGCACCAGAGGATATAATCGAATATGACTATGAGTATGGGGAAGCAGAGTATAAAGAGGCTGAA AGTGTAACAGAGGGACCCACTGTAACTGAGGAGACAATAGCACAGACGGAGGCAAACATCGTTGATGATT TTCAAGAATACAACTATGGAACAATGGAAAGTTACCAGACAGAAGCTCCTAGGCATGTTTCTGGGACAAA TGAGCCAAATCCAGTTGAAGAAATATTTACTGAAGAATATCTAACGGGAGAGGATTATGATTCCCAGAGG AAAAATTCTGAGGATACACTATATGAAAACAAAGAAATAGACGGCAGGGATTCTGATCTTCTGGTAGATG GAGATTTAGGCGAATATGATTTTTATGAATATAAAGAATATGAAGATAAACCAACAAGCCCCCCTAATGA AGAATTTGGTCCAGGTGTACCAGCAGAAACTGATATTACAGAAACAAGCATAAATGGCCATGGTGCATAT 127Patent Atty. Dkt. No.150-35-PCT GGAGAGAAAGGACAGAAAGGAGAACCAGCAGTGGTTGAGCCTGGTATGCTTGTCGAAGGACCACCAGGAC CAGCAGGACCTGCAGGTATTATGGGTCCTCCAGGTCTACAAGGCCCCACTGGACCCCCTGGTGACCCTGG CGATAGGGGCCCCCCAGGACGTCCTGGCTTACCAGGGGCTGATGGTCTACCTGGTCCTCCTGGTACTATG TTGATGTTACCGTTCCGTTATGGTGGTGATGGTTCCAAAGGACCAACCATCTCTGCTCAGGAAGCTCAGG CTCAAGCTATTCTTCAGCAGGCTCGGATTGCTCTGAGAGGCCCACCTGGCCCAATGGGTCTAACTGGAAG ACCAGGTCCTGTGGGGGGGCCTGGTTCATCTGGGGCCAAAGGTGAGAGTGGTGATCCAGGTCCTCAGGGC CCTCGAGGCGTCCAGGGTCCCCCTGGTCCAACGGGAAAACCTGGAAAAAGGGGTCGTCCAGGTGCAGATG GAGGAAGAGGAATGCCAGGAGAACCTGGGGCAAAGGGAGATCGAGGGTTTGATGGACTTCCGGGTCTGCC AGGTGACAAAGGTCACAGGGGTGAACGAGGTCCTCAAGGTCCTCCAGGTCCTCCTGGTGATGATGGAATG AGGGGAGAAGATGGAGAAATTGGACCAAGAGGTCTTCCAGGTGAAGCTGGCCCACGAGGTTTGCTGGGTC CAAGGGGAACTCCAGGAGCTCCAGGGCAGCCTGGTATGGCAGGTGTAGATGGCCCCCCAGGACCAAAAGG GAACATGGGTCCCCAAGGGGAGCCTGGGCCTCCAGGTCAACAAGGGAATCCAGGACCTCAGGGTCTTCCT GGTCCACAAGGTCCAATTGGTCCTCCTGGTGAAAAAGGACCACAAGGAAAACCAGGACTTGCTGGACTTC CTGGTGCTGATGGGCCTCCTGGTCATCCTGGGAAAGAAGGCCAGTCTGGAGAAAAGGGGGCTCTGGGTCC CCCTGGTCCACAAGGTCCTATTGGATACCCGGGCCCCCGGGGAGTAAAGGGAGCAGATGGTGTCAGAGGT CTCAAGGGATCTAAAGGTGAAAAGGGTGAAGATGGTTTTCCAGGATTCAAAGGTGACATGGGTCTAAAAG GTGACAGAGGAGAAGTTGGTCAAATTGGCCCAAGAGGGGAAGATGGCCCTGAAGGACCCAAAGGTCGAGC AGGCCCAACTGGAGACCCAGGTCCTTCAGGTCAAGCAGGAGAAAAGGGAAAACTTGGAGTTCCAGGATTA CCAGGATATCCAGGAAGACAAGGTCCAAAGGGTTCCACTGGATTCCCTGGGTTTCCAGGTGCCAATGGAG AGAAAGGTGCACGGGGAGTAGCTGGCAAACCAGGCCCTCGGGGTCAGCGTGGTCCAACGGGTCCTCGAGG TTCAAGAGGTGCAAGAGGTCCCACTGGGAAACCTGGGCCAAAGGGCACTTCAGGTGGCGATGGCCCTCCT GGCCCTCCAGGTGAAAGAGGTCCTCAAGGACCTCAGGGTCCAGTTGGATTCCCTGGACCAAAAGGCCCTC CTGGACCACCTGGGAAGGATGGGCTGCCAGGACACCCTGGGCAACGTGGGGAGACTGGATTTCAAGGCAA GACCGGCCCTCCTGGGCCAGGGGGAGTGGTTGGACCACAGGGACCAACCGGTGAGACTGGTCCAATAGGG GAACGTGGGCATCCTGGCCCTCCTGGCCCTCCTGGTGAGCAAGGTCTTCCTGGTGCTGCAGGAAAAGAAG GTGCAAAGGGTGATCCAGGTCCTCAAGGTATCTCAGGGAAAGATGGACCAGCAGGATTACGTGGTTTCCC AGGGGAAAGAGGTCTTCCTGGAGCTCAGGGTGCACCTGGACTGAAAGGAGGGGAAGGTCCCCAGGGCCCA CCAGGTCCAGTTGGCTCACCAGGAGAACGTGGGTCAGCAGGTACAGCTGGCCCAATTGGTTTACCAGGGC GCCCGGGACCTCAGGGTCCTCCTGGTCCAGCTGGAGAGAAAGGTGCTCCTGGAGAAAAAGGTCCCCAAGG GCCTGCAGGGAGAGATGGAGTTCAAGGTCCTGTTGGTCTCCCAGGGCCAGCTGGTCCTGCCGGCTCCCCT GGGGAAGACGGAGACAAGGGTGAAATTGGTGAGCCGGGACAAAAAGGCAGCAAGGGTGACAAGGGAGAAA ATGGCCCTCCCGGTCCCCCAGGTCTTCAAGGACCAGTTGGTGCCCCTGGAATTGCTGGAGGTGATGGTGA ACCAGGTCCTAGAGGACAGCAGGGGATGTTTGGGCAAAAAGGTGATGAGGGTGCCAGAGGCTTCCCTGGA CCTCCTGGTCCAATAGGTCTTCAGGGTCTGCCAGGCCCACCTGGTGAAAAAGGTGAAAATGGGGATGTTG GTCCCATGGGGCCACCTGGTCCTCCAGGCCCAAGAGGCCCTCAAGGTCCCAATGGAGCTGATGGACCACA AGGACCCCCAGGGTCTGTTGGTTCAGTTGGTGGTGTTGGAGAAAAGGGTGAACCTGGAGAAGCAGGGAAC CCAGGGCCTCCTGGGGAAGCAGGTGTAGGCGGTCCCAAAGGAGAAAGAGGAGAGAAAGGGGAAGCTGGTC CACCTGGAGCTGCTGGACCTCCAGGTGCCAAGGGGCCACCAGGTGATGATGGCCCTAAGGGTAACCCGGG TCCTGTTGGTTTTCCTGGAGATCCTGGTCCTCCTGGGGAACCTGGCCCTGCAGGTCAAGATGGTGTTGGT GGTGACAAGGGTGAAGATGGAGATCCTGGTCAACCGGGTCCTCCTGGCCCATCTGGTGAGGCTGGCCCAC CAGGTCCTCCTGGAAAACGAGGTCCTCCTGGAGCTGCAGGTGCAGAGGGAAGACAAGGTGAAAAAGGTGC TAAGGGGGAAGCAGGTGCAGAAGGTCCTCCTGGAAAAACCGGCCCAGTCGGTCCTCAGGGACCTGCAGGA AAGCCTGGTCCAGAAGGTCTTCGGGGCATCCCTGGTCCTGTGGGAGAACAAGGTCTCCCTGGAGCTGCAG GCCAAGATGGACCACCTGGTCCTATGGGACCTCCTGGCTTACCTGGTCTCAAAGGTGACCCTGGCTCCAA GGGTGAAAAGGGACATCCTGGTTTAATTGGCCTGATTGGTCCTCCAGGAGAACAAGGGGAAAAAGGTGAC CGAGGGCTCCCTGGAACTCAAGGATCTCCAGGAGCAAAAGGGGATGGGGGAATTCCTGGTCCTGCTGGTC CCTTAGGTCCACCTGGTCCTCCAGGTTTACCAGGTCCTCAAGGCCCAAAGGGTAACAAAGGCTCTACTGG ACCCGCTGGCCAGAAAGGTGACAGTGGTCTTCCAGGGCCTCCTGGGTCTCCAGGTCCACCTGGTGAAGTC ATTCAGCCTTTACCAATCTTGTCCTCCAAAAAAACGAGAAGACATACTGAAGGCATGCAAGCAGATGCAG ATGATAATATTCTTGATTACTCGGATGGAATGGAAGAAATATTTGGTTCCCTCAATTCCCTGAAACAAGA CATTGAGCATATGAAATTTCCAATGGGTACTCAGACCAATCCAGCCCGAACTTGTAAAGACCTGCAACTC AGCCATCCTGACTTCCCAGATGGTGAATATTGGATTGATCCTAACCAAGGTTGCTCAGGAGATTCCTTCA AAGTTTACTGTAATTTCACATCTGGTGGTGAGACTTGCATTTATCCAGACAAAAAATCTGAGGGAGTAAG AATTTCATCATGGCCAAAGGAGAAACCAGGAAGTTGGTTTAGTGAATTTAAGAGGGGAAAACTGCTTTCA TACTTAGATGTTGAAGGAAATTCCATCAATATGGTGCAAATGACATTCCTGAAACTTCTGACTGCCTCTG CTCGGCAAAATTTCACCTACCACTGTCATCAGTCAGCAGCCTGGTATGATGTGTCATCAGGAAGTTATGA CAAAGCACTTCGCTTCCTGGGATCAAATGATGAGGAGATGTCCTATGACAATAATCCTTTTATCAAAACA CTGTATGATGGTTGTGCGTCCAGAAAAGGCTATGAAAAGACTGTCATTGAAATCAATACACCAAAAATTG ATCAAGTACCTATTGTTGATGTCATGATCAATGACTTTGGTGATCAGAATCAGAAGTTCGGATTTGAAGT TGGTCCTGTTTGTTTTCTTGGCTAAGATTAAGACAAAGAACATATCAAATCAACAGAAAATATACCTTGG TGCCACCAACCCATTTTGTGCCACATGCAAGTTTTGAATAAGGATGGTATAGAAAACAACGCTGCATATA CAGGTACCATTTAGGAAATACCGATGCCTTTGTGGGGGCAGAATCACATGGCAAAAGCTTTGAAAATCAT 128Patent Atty. Dkt. No.150-35-PCT AAAGATATAAGTTGGTGTGGCTAAGATGGAAACAGGGCTGATTCTTGATTCCCAATTCTCAACTCTCCTT TTCCTATTTGAATTTCTTTGGTGCTGTAGAAAACAAAAAAAGAAAAATATATATTCATAAAAAATATGGT GCTCATTCTCATCCATCCAGGATGTACTAAAACAGTGTGTTTAATAAATTGTAATTATTTTGTGTACAGT TCTATACTGTTATCTGTGTCCATTTCCAAAACTTGCACGTGTCCCTGAATTCCATCTGACTCTAATTTTA TGAGAATTGCAGAACTCTGATGGCAATAAATATATGTATTATGAAAAAATAAAGTTGTAATTTCTGATGA CTCTAAGTCCCTTTCTTTGGTTAATAATAAAATGCCTTTGTATATATTGATGTTGAAGAGTTCAATTATT TGATGTCGCCAACAAAATTCTCAGAGGGCAAAAATCTGGAAGACTTTTGGAAGCACACTCTGATCAACTC TTCTCTGCCGACAGTCATTTTGCTGAATTTCAGCCAAAAATATTATGCATTTTGATGCTTTATTCAAGGC TATACCTCAAACTTTTTCTTCTCAGAATCCAGGATTTCACAGGATACTTGTATATATGGAAAACAAGCAA GTTTATATTTTTGGACAGGGAAATGTGTGTAAGAAAGTATATTAACAAATCAATGCCTCCGTCAAGCAAA CAATCATATGTATACTTTTTTTCTACGTTATCTCATCTCCTTGTTTTCAGTGTGCTTCAATAATGCAGGT TAATATTAAAGATGGAAATTAAGCAATTATTTATGAATTTGTGCAATGTTAGATTTTCTTATCAATCAAG TTCTTGAATTTGATTCTAAGTTGCATATTATAACAGTCTCGAAAATTATTTTACTTGCCCAACAAATATT ACTTTTTTCCTTTCAAGATAATTTTATAAATCATTTGACCTACCTAATTGCTAAATGAATAACATATGGT GGACTGTTATTAAGAGTATTTGTTTTAAGTCATTCAGGAAAATCTAAACTTTTTTTTCCACTAAGGTATT TACTTTAAGGTAGCTTGAAATAGCAATACAATTTAAAAATTAAAAACTGAATTTTGTATCTATTTTAAGT AATATATGTAAGACTTGAAAATAAATGTTTTATTTCTTATATAAAGTGTTAAATTAATTGATACCAGATT TCACTGGAACAGTTTCAACTGATAATTTATGACAAAAGAACATACCTGTAATATTGAAATTAAAAAGTGA AATTTGTCATAAAGAATTTCTTTTATTTTTGAAATCGAGTTTGTAAATGTCCTTTTAAGAAGGGAGATAT GAATCCAATAAATAAACTCAAGTCTTGGCTA COL11A1, NP_001845.3 collagen alpha-1(XI) chain isoform A preproprotein; AA; Homo sapiens(SEQ ID NO:12) MEPWSSRWKTKRWLWDFTVTTLALTFLFQAREVRGAAPVDVLKALDFHNSPEGISKTTGFCTNRKNSKGS DTAYRVSKQAQLSAPTKQLFPGGTFPEDFSILFTVKPKKGIQSFLLSIYNEHGIQQIGVEVGRSPVFLFE DHTGKPAPEDYPLFRTVNIADGKWHRVAISVEKKTVTMIVDCKKKTTKPLDRSERAIVDTNGITVFGTRI LDEEVFEGDIQQFLITGDPKAAYDYCEHYSPDCDSSAPKAAQAQEPQIDEYAPEDIIEYDYEYGEAEYKE AESVTEGPTVTEETIAQTEANIVDDFQEYNYGTMESYQTEAPRHVSGTNEPNPVEEIFTEEYLTGEDYDS QRKNSEDTLYENKEIDGRDSDLLVDGDLGEYDFYEYKEYEDKPTSPPNEEFGPGVPAETDITETSINGHG AYGEKGQKGEPAVVEPGMLVEGPPGPAGPAGIMGPPGLQGPTGPPGDPGDRGPPGRPGLPGADGLPGPPG TMLMLPFRYGGDGSKGPTISAQEAQAQAILQQARIALRGPPGPMGLTGRPGPVGGPGSSGAKGESGDPGP QGPRGVQGPPGPTGKPGKRGRPGADGGRGMPGEPGAKGDRGFDGLPGLPGDKGHRGERGPQGPPGPPGDD GMRGEDGEIGPRGLPGEAGPRGLLGPRGTPGAPGQPGMAGVDGPPGPKGNMGPQGEPGPPGQQGNPGPQG LPGPQGPIGPPGEKGPQGKPGLAGLPGADGPPGHPGKEGQSGEKGALGPPGPQGPIGYPGPRGVKGADGV RGLKGSKGEKGEDGFPGFKGDMGLKGDRGEVGQIGPRGEDGPEGPKGRAGPTGDPGPSGQAGEKGKLGVP GLPGYPGRQGPKGSTGFPGFPGANGEKGARGVAGKPGPRGQRGPTGPRGSRGARGPTGKPGPKGTSGGDG PPGPPGERGPQGPQGPVGFPGPKGPPGPPGKDGLPGHPGQRGETGFQGKTGPPGPGGVVGPQGPTGETGP IGERGHPGPPGPPGEQGLPGAAGKEGAKGDPGPQGISGKDGPAGLRGFPGERGLPGAQGAPGLKGGEGPQ GPPGPVGSPGERGSAGTAGPIGLPGRPGPQGPPGPAGEKGAPGEKGPQGPAGRDGVQGPVGLPGPAGPAG SPGEDGDKGEIGEPGQKGSKGDKGENGPPGPPGLQGPVGAPGIAGGDGEPGPRGQQGMFGQKGDEGARGF PGPPGPIGLQGLPGPPGEKGENGDVGPMGPPGPPGPRGPQGPNGADGPQGPPGSVGSVGGVGEKGEPGEA GNPGPPGEAGVGGPKGERGEKGEAGPPGAAGPPGAKGPPGDDGPKGNPGPVGFPGDPGPPGEPGPAGQDG VGGDKGEDGDPGQPGPPGPSGEAGPPGPPGKRGPPGAAGAEGRQGEKGAKGEAGAEGPPGKTGPVGPQGP AGKPGPEGLRGIPGPVGEQGLPGAAGQDGPPGPMGPPGLPGLKGDPGSKGEKGHPGLIGLIGPPGEQGEK GDRGLPGTQGSPGAKGDGGIPGPAGPLGPPGPPGLPGPQGPKGNKGSTGPAGQKGDSGLPGPPGSPGPPG EVIQPLPILSSKKTRRHTEGMQADADDNILDYSDGMEEIFGSLNSLKQDIEHMKFPMGTQTNPARTCKDL QLSHPDFPDGEYWIDPNQGCSGDSFKVYCNFTSGGETCIYPDKKSEGVRISSWPKEKPGSWFSEFKRGKL LSYLDVEGNSINMVQMTFLKLLTASARQNFTYHCHQSAAWYDVSSGSYDKALRFLGSNDEEMSYDNNPFI KTLYDGCASRKGYEKTVIEINTPKIDQVPIVDVMINDFGDQNQKFGFEVGPVCFLG ETV1, NM_004956.5 Homo sapiens ETS variant transcription factor 1 (ETV1), transcript variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:13) AGAGGCGCTTTCGGCTTCCAAGGGGGAAGTGCTGGGCTATAATTAATGTTTTTATTAAATTTGGAGGGAA GTTTTTGCAGCCTTTCGCCTAGCGTGGCCTTCAGTCCCGTTAGGTGCAAAGCAAGTCTCGTTGATCGCCA TTGCTAGTTTTGCACACGTTTGCGAATCAGAGCTGCCCGGGGTACACCGACCGCGCAGGGAAACATCGAG AGTGTAAATAAATACATCGCCTCTTGTTCGGATTTTTGCTACTACCGAAAATATGTAAATTGTGAACTCT GTTGGCTCTCTTTGGATCCAGGTTGATAGAAGTCCAGATCCTGAGGAAATCTCCAGCTAAATGCTCAAAA TATAAAATACTGAGCTGAGATTTGCGAAGAGCAGCAGCATGGATGGATTTTATGACCAGCAAGTGCCTTA CATGGTCACCAATAGTCAGCGTGGGAGAAATTGTAACGAGAAACCAACAAATGTCAGGAAAAGAAAATTC ATTAACAGAGATCTGGCTCATGATTCAGAAGAACTCTTTCAAGATCTAAGTCAATTACAGGAAACATGGC TTGCAGAAGCTCAGGTACCTGACAATGATGAGCAGTTTGTACCAGACTATCAGGCTGAAAGTTTGGCTTT TCATGGCCTGCCACTGAAAATCAAGAAAGAACCCCACAGTCCATGTTCAGAAATCAGCTCTGCCTGCAGT CAAGAACAGCCCTTTAAATTCAGCTATGGAGAAAAGTGCCTGTACAATGTCAGTGCCTATGATCAGAAGC CACAAGTGGGAATGAGGCCCTCCAACCCCCCCACACCATCCAGCACGCCAGTGTCCCCACTGCATCATGC 129Patent Atty. Dkt. No.150-35-PCT ATCTCCAAACTCAACTCATACACCGAAACCTGACCGGGCCTTCCCAGCTCACCTCCCTCCATCGCAGTCC ATACCAGATAGCAGCTACCCCATGGACCACAGATTTCGCCGCCAGCTTTCTGAACCCTGTAACTCCTTTC CTCCTTTGCCGACGATGCCAAGGGAAGGACGTCCTATGTACCAACGCCAGATGTCTGAGCCAAACATCCC CTTCCCACCACAAGGCTTTAAGCAGGAGTACCACGACCCAGTGTATGAACACAACACCATGGTTGGCAGT GCGGCCAGCCAAAGCTTTCCCCCTCCTCTGATGATTAAACAGGAACCCAGAGATTTTGCATATGACTCAG AAGTGCCTAGCTGCCACTCCATTTATATGAGGCAAGAAGGCTTCCTGGCTCATCCCAGCAGAACAGAAGG CTGTATGTTTGAAAAGGGCCCCAGGCAGTTTTATGATGACACCTGTGTTGTCCCAGAAAAATTCGATGGA GACATCAAACAAGAGCCAGGAATGTATCGGGAAGGACCCACATACCAACGGCGAGGATCACTTCAGCTCT GGCAGTTTTTGGTAGCTCTTCTGGATGACCCTTCAAATTCTCATTTTATTGCCTGGACTGGTCGAGGCAT GGAATTTAAACTGATTGAGCCTGAAGAGGTGGCCCGACGTTGGGGCATTCAGAAAAACAGGCCAGCTATG AACTATGATAAACTTAGCCGTTCACTCCGCTATTACTATGAGAAAGGAATTATGCAAAAGGTGGCTGGAG AGAGATATGTCTACAAGTTTGTGTGTGATCCAGAAGCCCTTTTCTCCATGGCCTTTCCAGATAATCAGCG TCCACTGCTGAAGACAGACATGGAACGTCACATCAACGAGGAGGACACAGTGCCTCTTTCTCACTTTGAT GAGAGCATGGCCTACATGCCGGAAGGGGGCTGCTGCAACCCCCACCCCTACAACGAAGGCTACGTGTATT AACACAAGTGACAGTCAAGCAGGGCGTTTTTGCGCTTTTCCTTTTTTCTGCAAGATACAGAGAATTGCTG AATCTTTGTTTTATTTCTGTTGTTTGTATTTTATTTTTAAATAATAATACACAAAAAGGGGCTTTTCCTG TTGCATTATTCTATGGTCTGCCATGGACTGTGCACTTTATTTGAGGGTGGGTGGGAGTAATCTAAACATT TATTCTGTGTAACAGGAAGCTAATGGGTGAATGGGCAGAGGGATTTGGGGATTACTTTTTACTTAGGCTT GGGATGGGGTCCTACAAGTTTTGAGTATGATGAAACTATATCATGTCTGTTTGATTTCATAACAACATAA GATAATGTTTATTTTATCGGGGTATCTATGGTACAGTTAATTTCACGTTGTGTAAATATCCACTTGGAGA CTATTTGCCTTGGGCATTTTCCCCTGTCATTTATGAGTCTCTGCAGGTGTACAAAAAAACCCCAATCTAC TGTAAATGGCAGTTTAATTGTTAGAAATGACTGTTTTTGCACCACTTGTAAAAAGGTATTTAGCGATTGC ATTTGCTGTTTGTTGTTTTATTTTGCTTTATATATGACTTGCAGAGGATAACCATAAAATGGGTAATTCT CTCTGAAGTTGAATAATCACCATGACTGTAAATGAGGGGCACAATTTTGGACTCTGGCGCCAAACTGAGT CATAGGCCAGTAGCATTACGTGTATCTGGTGCCACCTTGCTGTTTAGATACAAATCATACCGTCTTTTAA ATATTTTGAAGCCCATTTCAGTTAAATAATGACATGTCATGGTCCTTTGGAATCTTCATTTAAATGTTAA ATCTGGAATCAAAATGAAGCAAAAAATATCTGTCTCCTTTTCACTTTCTTCAGTACATAAATACATTATT TAATCAATAAGAATTAACTGTACTAAATCATGTATTATGCTGTTCTAGTTACAGCAAACACTCTTTAAGA AAAATATCCAATACACTAAATAGGTACTATAGTAATTTTTAGACATGGTACCCATTGATATGCATTTAAA CCTTTTACTGCTGTGTTATGTTGATAACATATATAAATATTAGATAATGCTAATGCTTCTGCTGCTGTCT TTTCTGTAATATTCTCTTTCATGCTGAATTTACTATGACCATTTATAAGCAGTGCAGTTAACTACAGATA GCATTTCAGGACAAAATAGATGACTCAAACCATTTATTGCTTAAAAAATAGCTTACGCCATGCTATGCTA TAAGCAGCTTTTATGCACATTGACAAATGAAGAGTAAGCTTCAGCTTGCTAAAGGAAACTGTGGAACCTT TTGTAACTTTTGGTGATATGGAAAATTATTTACAAACCGTCAAAGAATATGAGGAAGTTGCTGTATGACA TAGTGCTGGCACTGATATTATCCATCATCTCTTTTTGGACACTTCTGTAAATGTGATTGGATTGTTTGAA AGAAGATTTAAAGTTTCAAAGTTTTTTGTTCTGTTTTTGCTTTGCATTTGGAGAAAATATTGAAAGCAGG GTATGTTGTTTCATTCACCTTGAAAAAACCATGAGTAAATGGGGATATAGAATCTCTGAATAGCTCGCTA AAAGATTCAAGCAAGGGACATGAATTTTGTTCCATCTATCAATAATATCCAGAAGAACAACTTTTTTAAA GAGTCTATAGCAAAAAGCAAAAAAAAAAAAAAATTCTAAACACAAAGTCAAAATAAACCTATTGTAAAAG CATTTCGTGATGAGCATGAAAAAGATTGTTTAAAGATGATCCCCCCAGCTACCCATTTTCCAAAACTACA CAGATCACAGCTCATTTCTCTAAGTGGAGCAGTTATCAAGAAACCCAAACACCAAAATTGCTACTCTTCA CATTTAATCCTACAAAAAGTACTCCAATTTCAAAATATGTATGTAACCTGCGATTTCAATGATTGTTGTT CATATACATCATGTATTATTTTGGCCCATTTTGGGCCTAAAAAAGAAAACTATGCCTTAAAAATCAGAAC CTTTTCTCCCCACTATGCTTATGTGGCCATCTACAGCACTTAGAATAAAAACAGATGTTAAAATATTCAG TGAAAGTTTTATTGGAAAAAGGAATTGAGATATATAATTGAGATTTGGTGAAATTGAAGGAGAAAATTTA AGTGAGTCTTTAAAATATATTCTGAATGAAAACTGTATTGAGGATTCATTTTTGTTCCTTTTTTTTCTTT TTCTCTTTTCTCCTTTTTCTTCTTTTTAATAGTCTAGTTTTAGTCAGTCAGTGAGGAAGAATTGGGCCAT GCTAACGTTATCACAAGAGAACAATGGCAGAAATGGTATTAGTTATATAATATTTAAGGACAAACTATAT GTTTTGCTGTTTTAACGTAGTGACTCACTGAACTAAATACATAATTGACCAACATTAAGTGTATTTCCAA TACAGAAGGGTTGAAAATATTACATTATAAACTCTTTTGAAAAATGTATCTAAAATTTTTTAAGTTCTGT TTTGATTCCACTTTTTGGTTGAGTTTTTATGTTTTTGTTTTCAGGTAGATTAATAAATCTGGCAGCTGAT TTCTGCAAGATTCTTGTGTTTTGAATTTCTCATTGAATTGGCTACTCAAACATAGAAATCATTTGTTAAT GATGTAATGTCTTCTCTCAGCTTTTATCTTCACTGCTGTTTGCTGTCTCTTGATGATGACATGTTAATAC CCAATAGATTAATTGCAACAAACACTTATACTCAAATAACTAAGTAAAAATAATTTTTCTTGTTATGTCC ATGAAAAGTGCTTCAGAATAAAAATCCACAAGACTGACAGTGCAGAACATTTTTCTCAAATCATGGGCGG ATCTTGGAGGTCTAGTTTCCCGTAGATGCTGTAACCAATTACCACAACTTCAGTAATTTACACAAATTTA TCTTATAGTTCTGGAGGCAGAAGTTCAAAAGAAGCCTTAAGAGACTAAAACCAAGATGTCCTTAGGTCTG GTTCCTTCTGGAGGCTCCAGGGGAGATTCTTCCAGCTTTCACTTCTAGAGTCTGCTGACATTCCTTGGCT CCTGGCTACATCACTTCAATCTCTGCTTCCATGGTCACATACTCTTCTACTATAGTCAAATTTCCTTCCT GCCTCTTATAAGGATGCTTGTGATTACATTTAGGGGATGCTCAGATAATCCAGGACAATCTCTCCATCTC AAGATCCTTAACTTAATGACGTGTGCCAAGTCCCTTTGGCTAGATAATTATTCATAGGTCCCAGGGATTA GGACATGGATGTAAGGGGTGAGGGCAGGGCTGTTATTCAGAACACCGCACGGAGGAGGAAGACTGTGTAG 130Patent Atty. Dkt. No.150-35-PCT CAAAGACTCTAATTGATTTACTCAGGAACAGTGGAGTTCTGCTGAGGGATCTAGGATTTGAAAGTACTAG AGTTTGCTTTTATTTACCACTGAGATATTTTCCCCTTATTCTGCATAAATAATTTTGAAAACTTTCTATA TTAAATTTCAACTATTCCACTAAAATGTCTGGTAATCACATCAAGCCTTTAGATTATTCAAATCCTTCCC CAGCCCCCAGGAAAACACTAAGTCATGAAACAGAAAAACAGAAGGTATGATAATAATAGTAATAACAGTT AAATCAGTGGTCTAATCCAGATTTTATTTTTTAATACATTTCTTTTGGTGTTAATATGGGTTACTATGTG ATCTTATCATTTGCTAGTGATTATTACTTATTAGGTAAGAACAATGTGTAAAATATGTCTATTACTCAAA AGAACAATTGCAAAATGAGTCAACTTATCTTTATATAACCAGGAAAGAAATATATTGCCAGAAGCTACAG AATTTTGCCAGATGATAGGGATTTCTAAAATGAGCCACTTTGTCTATCATGCAGCCTTTTCAGAGCTTGT AATGAGAAAACATTACAGAGGAGAAGGTCATTTGGATGTTTGTTACTTGGAATCCTAGAAAACAAAAACT AAAATTTAAAAATAAGAAGTGAGTAAGCTATTTTCCATTTGCGATTTGGTATGGAGAAGAGAGGAAATAG AATTATTAAAAAAATACAAATTGGGTAAAAGTGATGGTGGAAAAAATATAAAGAAGGCAAATGTACATAT TAAGCAATTCTACTAAGAATTGGAAAAATCAAGTTTCAAAAAGATGGTAATAGTTGGGCATGATACTAGA AAATTTCACCCAGTTTATTCAGAGCTCAACTAGTACTTTTAGGACTTCTTTTTTTATATACATGAGACTC ACTTTGACATACTTAAAAAAAAAACAGTTTATGGAAAGTACAGTTTAAGAGGAGAATTTGATTAGACTAA GTGGATATCTTTATAGAAATATTAATGATTTCAGAATTTTCAGTTACAAGTGTATATACCGTGGCTATTG TTTATGGATTCATATGTAAGGTAGGGTCTTTTTTGCATATAGACTCCAGTATTAGTTACTTTCATTCTAA AATTATATTTATGCTTCTATGGGGAAGAAAATTTTTAATTCACTTGGTTGTATTAAAATTATACTTACGG TTTGAGAAAACATGCTATGAAAATCATGATTATAGCAAATTAAATATGCTCAAAATTTAAATCTAAAATA AAAGCCCAGAAACTGAAAA ETV1, NP_004947.2 ETS translocation variant 1 isoform a; AA; Homo sapiens(SEQ ID NO:14) MDGFYDQQVPYMVTNSQRGRNCNEKPTNVRKRKFINRDLAHDSEELFQDLSQLQETWLAEAQVPDNDEQF VPDYQAESLAFHGLPLKIKKEPHSPCSEISSACSQEQPFKFSYGEKCLYNVSAYDQKPQVGMRPSNPPTP SSTPVSPLHHASPNSTHTPKPDRAFPAHLPPSQSIPDSSYPMDHRFRRQLSEPCNSFPPLPTMPREGRPM YQRQMSEPNIPFPPQGFKQEYHDPVYEHNTMVGSAASQSFPPPLMIKQEPRDFAYDSEVPSCHSIYMRQE GFLAHPSRTEGCMFEKGPRQFYDDTCVVPEKFDGDIKQEPGMYREGPTYQRRGSLQLWQFLVALLDDPSN SHFIAWTGRGMEFKLIEPEEVARRWGIQKNRPAMNYDKLSRSLRYYYEKGIMQKVAGERYVYKFVCDPEA LFSMAFPDNQRPLLKTDMERHINEEDTVPLSHFDESMAYMPEGGCCNPHPYNEGYVY FBLN5, NM_006329.4 Homo sapiens fibulin 5 (FBLN5), transcript variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:15) GCCTTCTGCCCGGGCGCTCGCAGCCGAGCGCGGCCGGGGAAGGGCTCTCCTCCCAGCGCCGAGCACTGGG CCCTGGCAGACGCCCCAAGATTGTTGTGAGGAGTCTAGCCAGTTGGTGAGCGCTGTAATCTGAACCAGCT GTGTCCAGACTGAGGCCCCATTTGCATTGTTTAACATACTTAGAAAATGAAGTGTTCATTTTTAACATTC CTCCTCCAATTGGTTTAATGCTGAATTACTGAAGAGGGCTAAGCAAAACCAGGTGCTTGCGCTGAGGGCT CTGCAGTGGCTGGGAGGACCCCGGCGCTCTCCCCGTGTCCTCTCCACGACTCGCTCGGCCCCTCTGGAAT AAAACACCCGCGAGCCCCGAGGGCCCAGAGGAGGCCGACGTGCCCGAGCTCCTCCGGGGGTCCCGCCCGC GAGCTTTCTTCTCGCCTTCGCATCTCCTCCTCGCGCGTCTTGGACATGCCAGGAATAAAAAGGATACTCA CTGTTACCATTCTGGCTCTCTGTCTTCCAAGCCCTGGGAATGCACAGGCACAGTGCACGAATGGCTTTGA CCTGGATCGCCAGTCAGGACAGTGTTTAGATATTGATGAATGCCGAACCATCCCCGAGGCCTGCCGAGGA GACATGATGTGTGTTAACCAAAATGGCGGGTATTTATGCATTCCCCGGACAAACCCTGTGTATCGAGGGC CCTACTCGAACCCCTACTCGACCCCCTACTCAGGTCCGTACCCAGCAGCTGCCCCACCACTCTCAGCTCC AAACTATCCCACGATCTCCAGGCCTCTTATATGCCGCTTTGGATACCAGATGGATGAAAGCAACCAATGT GTGGATGTGGACGAGTGTGCAACAGATTCCCACCAGTGCAACCCCACCCAGATCTGCATCAATACTGAAG GCGGGTACACCTGCTCCTGCACCGACGGATATTGGCTTCTGGAAGGCCAGTGCTTAGACATTGATGAATG TCGCTATGGTTACTGCCAGCAGCTCTGTGCGAATGTTCCTGGATCCTATTCTTGTACATGCAACCCTGGT TTTACCCTCAATGAGGATGGAAGGTCTTGCCAAGATGTGAACGAGTGTGCCACCGAGAACCCCTGCGTGC AAACCTGCGTCAACACCTACGGCTCTTTCATCTGCCGCTGTGACCCAGGATATGAACTTGAGGAAGATGG CGTTCATTGCAGTGATATGGACGAGTGCAGCTTCTCTGAGTTCCTCTGCCAACATGAGTGTGTGAACCAG CCCGGCACATACTTCTGCTCCTGCCCTCCAGGCTACATCCTGCTGGATGACAACCGAAGCTGCCAAGACA TCAACGAATGTGAGCACAGGAACCACACGTGCAACCTGCAGCAGACGTGCTACAATTTACAAGGGGGCTT CAAATGCATTGACCCCATCCGCTGTGAGGAGCCTTATCTGAGGATCAGTGATAACCGCTGTATGTGTCCT GCTGAGAACCCTGGCTGCAGAGACCAGCCCTTTACCATCTTGTACCGGGACATGGACGTGGTGTCAGGAC GCTCCGTTCCCGCTGACATCTTCCAAATGCAAGCCACGACCCGCTACCCTGGGGCCTATTACATTTTCCA GATCAAATCTGGGAATGAGGGCAGAGAATTTTACATGCGGCAAACGGGCCCCATCAGTGCCACCCTGGTG ATGACACGCCCCATCAAAGGGCCCCGGGAAATCCAGCTGGACTTGGAAATGATCACTGTCAACACTGTCA TCAACTTCAGAGGCAGCTCCGTGATCCGACTGCGGATATATGTGTCGCAGTACCCATTCTGAGCCTCGGG CTGGAGCCTCCGACGCTGCCTCTCATTGGCACCAAGGGACAGGAGAAGAGAGGAAATAACAGAGAGAATG AGAGCGACACAGACGTTAGGCATTTCCTGCTGAACGTTTCCCCGAAGAGTCAGCCCCGACTTCCTGACTC TCACCTGTACTATTGCAGACCTGTCACCCTGCAGGACTTGCCACCCCCAGTTCCTATGACACAGTTATCA AAAAGTATTATCATTGCTCCCCTGATAGAAGATTGTTGGTGAATTTTCAAGGCCTTCAGTTTATTTCCAC TATTTTCAAAGAAAATAGATTAGGTTTGCGGGGGTCTGAGTCTATGTTCAAAGACTGTGAACAGCTTGCT GTCACTTCTTCACCTCTTCCACTCCTTCTCTCACTGTGTTACTGCTTTGCAAAGACCCGGGAGCTGGCGG 131Patent Atty. Dkt. No.150-35-PCT GGAACCCTGGGAGTAGCTAGTTTGCTTTTTGCGTACACAGAGAAGGCTATGTAAACAAACCACAGCAGGA TCGAAGGGTTTTTAGAGAATGTGTTTCAAAACCATGCCTGGTATTTTCAACCATAAAAGAAGTTTCAGTT GTCCTTAAATTTGTATAACGGTTTAATTCTGTCTTGTTCATTTTGAGTATTTTTAAAAAATATGTCGTAG AATTCCTTCGAAAGGCCTTCAGACACATGCTATGTTCTGTCTTCCCAAACCCAGTCTCCTCTCCATTTTA GCCCAGTGTTTTCTTTGAGGACCCCTTAATCTTGCTTTCTTTAGAATTTTTACCCAATTGGATTGGAATG CAGAGGTCTCCAAACTGATTAAATATTTGAAGAGA FBLN5, NP_006320.2 fibulin-5 isoform 1 precursor; AA; Homo sapiens (SEQ ID NO:16) MPGIKRILTVTILALCLPSPGNAQAQCTNGFDLDRQSGQCLDIDECRTIPEACRGDMMCVNQNGGYLCIP RTNPVYRGPYSNPYSTPYSGPYPAAAPPLSAPNYPTISRPLICRFGYQMDESNQCVDVDECATDSHQCNP TQICINTEGGYTCSCTDGYWLLEGQCLDIDECRYGYCQQLCANVPGSYSCTCNPGFTLNEDGRSCQDVNE CATENPCVQTCVNTYGSFICRCDPGYELEEDGVHCSDMDECSFSEFLCQHECVNQPGTYFCSCPPGYILL DDNRSCQDINECEHRNHTCNLQQTCYNLQGGFKCIDPIRCEEPYLRISDNRCMCPAENPGCRDQPFTILY RDMDVVSGRSVPADIFQMQATTRYPGAYYIFQIKSGNEGREFYMRQTGPISATLVMTRPIKGPREIQLDL EMITVNTVINFRGSSVIRLRIYVSQYPF IGFL2, NM_001002915.3 Homo sapiens IGF like family member 2 (IGFL2), transcript variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:17) TTTGGGTTTGGACGGGTGCGTTTGTTTCTCATAGTGCAGGTCTGGAGCCGGACTGAGATGGGGAGTAGAG GGACCCCTTGAAACTTCAGGGTGGATGAATATGAAGTTTCATCACCAGCTGTGATGTTTGATATTGGACT GTGGTTGTGCCAGTTGACACTCAGGAGTGGAGACTAGATCTGCAATCTGTTGGGACTGTGATGAGGGGAT CATCCTGCCCTCGAACCAGACCCAGCCCTGTAGCCCAGGCACTATTGCCTGGAGTTCCTGGGCTCTCAGC GCCAGGAAATCATGAGGTTCAGTGTCTCAGGCATGAGGACCGACTACCCCAGGAGTGTGCTGGCTCCTGC TTATGTGTCAGTCTGTCTCCTCCTCTTGTGTCCAAGGGAAGTCATCGCTCCCGCTGGCTCAGAACCATGG CTGTGCCAGCCGGCACCCAGGTGTGGAGACAAGATCTACAACCCCTTGGAGCAGTGCTGTTACAATGACG CCATCGTGTCCCTGAGCGAGACCCGCCAATGTGGTCCCCCCTGCACCTTCTGGCCCTGCTTTGAGCTCTG CTGTCTTGATTCCTTTGGCCTCACAAACGATTTTGTTGTGAAGCTGAAGGTTCAGGGTGTGAATTCCCAG TGCCACTCATCTCCCATCTCCAGTAAATGTGAAAGCAGAAGACGTTTTCCCTGAGAAGACATAGAAAGAA AATCAACTTTCACTAAGGCATCTCAGAAACATAGGCTAAGGTAATATGTGTACCAGTAGAGAAGCCTGAG GAATTTACAAAATGATGCAGCTCCAAGCCATTGTATGGCCCATGTGGGAGACTGATGGGACATGGAGAAT GACAGTAGATTATCAGGAAATAAATAAAGTGGTTTTTCCAATGTA IGFL2, NP_001002915.2 insulin growth factor-like family member 2 isoform a; AA; Homo sapiens(SEQ ID NO:18) MRFSVSGMRTDYPRSVLAPAYVSVCLLLLCPREVIAPAGSEPWLCQPAPRCGDKIYNPLEQCCYNDAIVS LSETRQCGPPCTFWPCFELCCLDSFGLTNDFVVKLKVQGVNSQCHSSPISSKCESRRRFP ITGA11, NM_001004439.2 Homo sapiens integrin subunit alpha 11 (ITGA11), mRNA; DNA; Homo sapiens(SEQ ID NO:19) AGTGCAGGCTGCAGGCGCCGCGCCGAGGAGGCTGCCGCTCTGGCTTGCCGCCCCCCGCCGCCGCTGCACA CCGGACCCAGCCGCCGTGCCGCGGGCCATGGACCTGCCCAGGGGCCTGGTGGTGGCCTGGGCGCTCAGCC TGTGGCCAGGGTTCACGGACACCTTCAACATGGACACCAGGAAGCCCCGGGTCATCCCTGGCTCCAGGAC CGCCTTCTTTGGCTACACAGTGCAGCAGCACGACATCAGTGGCAATAAGTGGCTGGTCGTGGGCGCCCCA CTGGAAACCAATGGCTACCAGAAGACGGGAGACGTGTACAAGTGTCCAGTGATCCACGGGAACTGCACCA AACTCAACCTGGGAAGGGTCACCCTGTCCAACGTGTCCGAGCGGAAAGACAACATGCGCCTCGGCCTTAG TCTCGCCACCAACCCCAAGGACAACAGCTTCCTGGCCTGCAGCCCCCTCTGGTCTCATGAGTGTGGGAGC TCCTACTACACCACAGGGATGTGTTCAAGAGTCAACTCCAACTTCAGGTTCTCCAAGACCGTGGCCCCAG CTCTCCAAAGGTGCCAGACCTACATGGACATCGTCATTGTCCTGGATGGCTCCAACAGCATCTACCCCTG GGTGGAGGTTCAGCACTTCCTCATCAACATCCTGAAAAAGTTTTACATTGGCCCAGGGCAGATCCAGGTT GGAGTTGTGCAGTATGGCGAAGATGTGGTGCATGAGTTTCACCTCAACGACTACAGGTCTGTAAAAGATG TGGTGGAAGCTGCCAGCCACATTGAGCAGAGAGGAGGAACAGAGACCCGGACGGCATTTGGCATTGAATT TGCACGCTCAGAGGCTTTCCAGAAGGGTGGAAGGAAAGGAGCCAAGAAGGTGATGATTGTCATCACAGAT GGGGAGTCCCACGACAGCCCAGACCTGGAGAAGGTGATCCAGCAAAGCGAAAGAGACAACGTAACAAGAT ATGCGGTGGCCGTCCTGGGCTACTACAACCGCAGGGGGATCAATCCAGAAACTTTTCTAAATGAAATCAA ATACATCGCCAGTGACCCTGATGACAAGCACTTCTTCAATGTCACTGATGAGGCTGCCTTGAAGGACATT GTCGATGCCCTGGGGGACAGAATCTTCAGCCTGGAAGGCACCAACAAGAACGAGACCTCCTTTGGGCTGG AGATGTCACAGACGGGCTTTTCCTCGCACGTGGTGGAGGATGGGGTTCTGCTGGGAGCCGTCGGTGCCTA TGACTGGAATGGAGCTGTGCTAAAGGAGACGAGTGCCGGGAAGGTCATTCCTCTCCGCGAGTCCTACCTG AAAGAGTTCCCCGAGGAGCTCAAGAACCATGGTGCATACCTGGGGTACACAGTCACATCGGTCGTGTCCT CCAGGCAGGGGCGGGTGTACGTGGCCGGAGCCCCCCGGTTCAACCACACGGGCAAGGTCATCCTGTTCAC CATGCACAACAACCGGAGCCTCACCATCCACCAGGCTATGCGGGGCCAGCAGATAGGCTCTTACTTTGGG AGTGAAATCACCTCGGTGGACATCGACGGCGACGGCGTGACTGATGTCCTGCTGGTGGGCGCACCCATGT ACTTCAACGAGGGCCGTGAGCGAGGCAAGGTGTACGTCTATGAGCTGAGACAGAACCTGTTTGTTTATAA CGGAACGCTAAAGGATTCACACAGTTACCAGAATGCCCGATTTGGGTCCTCCATTGCCTCAGTTCGAGAC CTCAACCAGGATTCCTACAATGACGTGGTGGTGGGAGCCCCCCTGGAGGACAACCACGCAGGAGCCATCT 132Patent Atty. Dkt. No.150-35-PCT ACATCTTCCACGGCTTCCGAGGCAGCATCCTGAAGACACCTAAGCAGAGAATCACAGCCTCAGAGCTGGC TACCGGCCTCCAGTATTTTGGCTGCAGCATCCACGGGCAATTGGACCTCAATGAGGATGGGCTCATCGAC CTGGCAGTGGGAGCCCTTGGCAACGCTGTGATTCTGTGGTCCCGCCCAGTGGTTCAGATCAATGCCAGCC TCCACTTTGAGCCATCCAAGATCAACATCTTCCACAGAGACTGCAAGCGCAGTGGCAGGGATGCCACCTG CCTGGCCGCCTTCCTCTGCTTCACGCCCATCTTCCTGGCACCCCATTTCCAAACAACAACTGTTGGCATC AGATACAACGCCACCATGGATGAGAGGCGGTATACACCGAGGGCCCACCTGGACGAGGGCGGGGACCGAT TCACCAACAGAGCCGTACTGCTCTCCTCCGGCCAGGAGCTCTGTGAGCGGATCAACTTCCATGTCCTGGA CACTGCTGACTACGTGAAGCCAGTGACCTTCTCAGTCGAGTATTCCCTGGAGGACCCTGACCATGGCCCC ATGCTGGACGACGGCTGGCCCACCACTCTCAGAGTCTCGGTGCCCTTCTGGAACGGCTGCAATGAGGATG AGCACTGTGTCCCTGACCTTGTGTTGGATGCCCGGAGTGACCTGCCCACGGCCATGGAGTACTGCCAGAG GGTGCTGAGGAAGCCTGCGCAGGACTGCTCCGCATACACGCTGTCCTTCGACACCACAGTCTTCATCATA GAGAGCACACGCCAGCGAGTGGCGGTGGAGGCCACACTGGAGAACAGGGGCGAGAACGCCTACAGCACGG TCCTAAATATCTCGCAGTCAGCAAACCTGCAGTTTGCCAGCTTGATCCAGAAGGAGGACTCAGACGGTAG CATTGAGTGTGTGAACGAGGAGAGGAGGCTCCAGAAGCAAGTCTGCAACGTCAGCTATCCCTTCTTCCGG GCCAAGGCCAAGGTGGCTTTCCGTCTTGATTTTGAGTTCAGCAAATCCATCTTCCTACACCACCTGGAGA TCGAGCTCGCTGCAGGCAGTGACAGTAATGAGCGGGACAGCACCAAGGAAGACAACGTGGCCCCCTTACG CTTCCACCTCAAATACGAGGCTGACGTCCTCTTCACCAGGAGCAGCAGCCTGAGCCACTACGAGGTCAAG CCCAACAGCTCGCTGGAGAGATACGATGGTATCGGGCCTCCCTTCAGCTGCATCTTCAGGATCCAGAACT TGGGCTTGTTCCCCATCCACGGGATGATGATGAAGATCACCATTCCCATCGCCACCAGGAGCGGCAACCG CCTACTGAAGCTGAGGGACTTCCTCACGGACGAGGCGAACACGTCCTGTAACATCTGGGGCAATAGCACT GAGTACCGGCCCACCCCAGTGGAGGAAGACTTGCGTCGTGCTCCACAGCTGAATCACAGCAACTCTGATG TCGTCTCCATCAACTGCAATATACGGCTGGTCCCCAACCAGGAAATCAATTTCCATCTACTGGGGAACCT GTGGTTGAGGTCCCTAAAAGCACTCAAGTACAAATCCATGAAAATCATGGTCAACGCAGCCTTGCAGAGG CAGTTCCACAGCCCCTTCATCTTCCGTGAGGAGGATCCCAGCCGCCAGATCGTGTTTGAGATCTCCAAGC AAGAGGACTGGCAGGTCCCCATCTGGATCATTGTAGGCAGCACCCTGGGGGGCCTCCTACTGCTGGCCCT GCTGGTCCTGGCACTGTGGAAGCTCGGCTTCTTTAGAAGTGCCAGGCGCAGGAGGGAGCCTGGTCTGGAC CCCACCCCCAAAGTGCTGGAGTGAGGCTCCAGAGGAGACTTTGAGTTGATGGGGGCCAGGACACCAGTCC AGGTAGTGTTGAGACCCAGGCCTGTGGCCCCACCGAGCTGGAGCGGAGAGGAAGCCAGCTGGCTTTGCAC TTGACCTCATCTCCCGAGCAATGGCGCCTGCTCCCTCCAGAATGGAACTCAAGCTGGTTTTAAGTGGAAC TGCCCTACTGGGAGACTGGGACACCTTTAACACAGACCCCTAGGGATTTAAAGGGACACCCCTACACACA CCCAGGCCCATGCCAAGGCCTCCCTCAGGCTCTGTGGAGGGCATTTGCTGCCCCAGCTACTAAGGTGCTA GGAATTCGTAATCATCCCCATCCTCCAGAGAAACCCAGGGAGGAAGACTGTAAATACGAACCCAATCTGC ACACTCCAGGCCTCTAGTTCCAGAAGGATCCAAGACAAAACAGATCTGAATTCTGCCCTTTTCTCTCACC CATCCCACCCCTCCATTGGCTCCCAAGTCACACCCACTCCCTTCCCCATAGATAGGCCCCTGGGGCTCCC GAAGAATGAACCCAAGAGCAAGGGCTTGATGGTGACAGCTGCAAGCCAGGGATGAAGAAAGACTCTGAGA TGTGGAGACTGATGGCCAGGCAAGTGGGACCAGGATACTGGACGCTGTCCTGAGATGAGAGGTAGCCGGG CTCTGCACCCACGTGCATTCACATTGACCGCAACTCACACATTCCCCCACCAGCTGCAGCCCCTTGCTCT CAGCTGCCAACCCTCCCGGGTCACTTTTGTTCCCAGGTACCTCATGGGAAGCATGTGGATGACACAATCC CTGGGGCTGTGCATTCCCACGTCTTCTTGCTGCAGCCTGCCCCTAGACATGGACGCACCGGCCTGGCTGC AGCTGGGCAGCAGGGGTAGGGGTAGGGAGCCTCCCCTCCCTGTATCACCCCCTCCCTACACACACACACA CACACACACACACACACACACACACACACACACACACACACACACACTGCCTCCCATCCTTCCCTCATGC CCGCCAGTGCACAGGGAAGGGCTTGGCCAGCGCTGTTGAGGGGTCCCCTCTGGAATGCACTGAATAAAGC ACGTGCAAGGACTCCCGGAGCCTGTGCAGCCTTGGTGGCAAATATCTCATCTGCCGGCCCCCAGGACAAG TGGTATGACCAGTGATAATGCCCCAAGGACAAGGGGCGTGCCTGGCGCCCAGTGGAGTAATTTATGCCTT AGTCTTGTTTTGAGGTAGAAATGCAAGGGGGACACATGAAAGGCATCAGTCCCCCTGTGCATAGTACGAC CTTTACTGTCGTATTTTTGAAAAATTAAAAATACAGTGTTTAAAAACAACCAAGCACTGACATCCCATTC TGTGGGCAGAGCATATCACAGTGAGCCATACTCCCCTTTGAAGGAGAGGAAGTAGAATGAGGGAGTTCCT TGCTTCCTCCCCCCTACCTCTACATGTCAGAAGGGACTCATCCACCATTTGCTGCCCACAACATGCCCTC CTAGTGGCTGCCTGGCCTCCGTGTGACGTCTCCAGTGGTGGAGCGCTCCCTCTCCCAAGATCACCCTTCC ATCTATGGCCAGTGTGGACGGTTAGGACCTAAATGTTTCACTGTAGCTTCTGCCCTTGGTTCCAGCTCTT CCCTCTCACGCCTCCCAGACTTCTCCAGGCCGGTTTCATTGTTAACCGTCTTACACTCTGACATCAGCCA AGGCGTCTCCATTCTGTTCTTGTGCCATTCATGTCTTGGATTCCCAGTAAGTAGAACCTTGGAAATAATT TGATCTTGTTTTTGCATAAATGAGGACACTCAGAACCAGGAAGAGCCCTAGGCTCCCACAGCAAAACCAA AACTAAACCCAGGACTGCTATTTCCCAAGCCAGATTCTGTTATTCGAGCCCAGCCTTAGAAGGGCTTGAT GTGGAGCAAAAGGTGAAAATGGTGAAACTAAAATTTGAGTATCAAAACCCATTGCCTTCTAATAGAATCA GAAGGAAATGTTGCTAAATCATATTCCATTTCCGTCATCACTCTTATGAATGGGGTAACCTGGCTAAATG AGAATTAATGAACCCACACTCATAAGTTTTCATTGACTTAGCACCAAGTCGTCCATCAAATATCATCAGA TCTGAGAATGCTCTTATGGATATCTGATTTTTAGAGGCTGGCATTCATATTTTTAAAAACTGCCACCTGT GACCACACTGCAGGCCAAACAGAATGTACCTGCTGGTCAGATGCAGCCCAGAGGTCACTGAATTGCAACC TCTGGACTCTCGGTCAGAGGCAAGCAGCCCTTATTCCAGAACTCCACAGTCCTTCACACCCTTCCCCAGA CCTACACCAAGACCAACTAAGTGGTCAAAAGGTGGACAAACTGAGAGTTGTATCAAGGCCCTTAGCCTCT CAATTTGTTATCAAGTTTCCCTTTCTGAATCTATTTACCCTGAAGTATAAATACCCAAGATGAGCCTTAA 133Patent Atty. Dkt. No.150-35-PCT GAGTGCCTGGTAGAGCAAACAAAGATGCATCTTATAGGGAGCAAAGTCTATGCTAACGCAGTGTTTCTCA ATCCTGGCTGCACCTTTGAACCACGGGAGCTTTAAAAGTGACCACTGCAAGGGCCCTACCCACTATGGAT CCCAATTTCATTGGTTGGGAGAGGGGCCAAGTTTGTTTCCAACTTCCCCAGATGACTCTAATGGCTGAGA GTTGCAATCAACAGGTAAGTGAATATCCAGGCTGTAAGATGAAGAAAGAGGGGGTTGTGCCCAAGCCCAC TGTGCCTCATAAAGCAGATGATCTCTGCAGCGCTGCGCTTCTCAAAGAGTGGTCCCAGGACTGCCTCAGT CAGACCACAGACTCCTAAGTTCCTCCTCAGACTTCATGGATCCAAGCTCTGTGAGGTAATTCTAAGCACA TTAAACTTGTAGAACAGCCATCTGGATTTAATATTACATAATAGCTATAATATTCTGCTATTCTCTAATC TTCAATGTCAGTTTCTTAAACTGTCAGGCCTGTCTTTAGATGCCCTTCAACTGTGCTGGGGACTATCTTG ATGGCAGCCAGCAAAGAAAATCAGCAAAAACCCCAGTGGAGTTTCTGGGTTTTACTTTTGTTAAGGAAGG TGATGGTTTCTTGACATGACAGGTATCTAGGTGGAAAGGGCAAAGTGCTAATGCAAACACAATGGAGACA CTATGGAATAGCTCTGCCTAGGGACATGTGGAAGAGCTTCTAGGAGACAGTGTGGACCTTTCCATCCCTA GAGGTCTTCACAAGATAAATTCCTACCTCCGTCAGTATTCAAAAGGTTTTAGCATCAATACTGTCTGAGA ATAAGACATTAGACTTGAGTCAGTCCCCTGGCTTCAATCCCAGGATGCCAAGCAGCCTCTAATGGAGACC GCTGGCTTAATCGTGCTCCTTTCCTGGCATAACAACTCACTGCACCCATGCCTCACCACCACGAAGCAGT CTCCTCACCACCCAAATGTGCCTTGGGTGACTTAAATACAGCCATTAGTATGAATGGTCCCCTGTTTTTA TTCAACACCACACCAGTCTTTGCTTTTACCTTCGGCTAATGTGGTTCCAGCCTTTTATCCTGCACTCCTT CTTATAATTTAAAAAAAAAAAAAACTCCCCTACTATCTTTATGTTAATATTAACATCAACTAGGTTCTTC TCAAAGGACAGCCAGGCCTAACTGGCCACGTTAAAATCTGCACAGTGCTTTTGTGTCACTGTCTATTCTA TTAGTTTCAACATCATGCTAAAATAGGACAGCATGTTCCAAAACTGAAACTGAAACAGGAACGGAGCCTT GCTGATTTAGCATGAGGAGGGAATTGTAAGCCTTGCACCTGGACACTAAAACTTTTCAATAAGATGTATG CTAAGCCGTACCTAGCAAACTTACCAGGTCCAAAGTAGAGTACAAGCAGAAAGTTATTTTTAAAGGATGG GCACTATCCTTGAGGGACTTACCCTTTCTAATCAGCTTTGCATGGTTTGTTTTGAGACAGTGTCTCACTC TGTTGCCCAGGCTAGAGTGCAGCGGCACCATCACAGCTCACGGCAGCCTCTGCCTCCCGGGCTCAAGCAA TCCCACCTCAGTTTCCCAAGTAGCTGGGACTACAGGCACACACCACACTCAGCTAATTTTAGTATTTTTT GTAGAGACAGGGTCTCGCCATGTTGCCCAGGCTGGTCTCAAACTCCTGGATTATCTCCCTGGCCCTGCAT TAAAAAAGATGTGCAACAACTTAGTGATGTGTCTGAAATGTTTTCAGAAGGTGGCCCAAGTCAGAGTCAA AAAATTTTTTTATTTGGAAAATTAGAGGAAATACAGAAAATCAAATTTCAAATAGATGCATCTAAATGGA GAACAAGCTTATCAAGGACAGAGTCCATCTTTCTTATTTTTATTTTTGAGACAGGGTCTTGCTCTGTCAC CCAGGCTAGAGTGCAGCGGCACAATCACAGCTCCCTGCAGCCTCGACCTCCTGGACTTCAGTGATCCTCC CACCTCAGCCTCTTGAGTAGCTGGGACTACAGACATGCACCACCATGCCCAGCTAATTTTTTTTTTAATT TTGTGCAGAGAGGGGGTCTCACTTTGTTGCCCACACTGGTCTCTCTTATTTTTGTATGCATATCTGTGGT GCAGTGCCTGAAATACAGTAGGTGTTCAATAAGCGCCAACATGCAAGAGTATCTTGCCATTGATTAAGGC AAAAGCAAAACCCCAGTCCGCCCCTCTGATGGACTGAGCACACCAAATTTCTAAAGCACAGGCAAATTAG AAAATATAATTTTGTCTAAACTTGCCAACAAGCTAAGGTTTTGTGAACCACCTAAAATTTGCCTCTCTCA TACTGAAATTTTCTAGGTCAAGTATCTGAAGGAATACACTACTGCCAGTATTTTCTTTGGTGATCTGTCA TATACAGCAGACATTACTTGAAACAAAGAAAAAAATGTTTTAAAACCTGTCTGGATGATTTCCGCAGTCT CACTAGGTTATTGCAGCCAGGGAGTGACCTAGCAGAGATCTGAAGGTGAGCTTCCCTAGTACTGGCATCT CACAGTGAAAGAGCACTGTTCAGTGGGTCAAGAGACCCAGAGCCTACTCTCAGTTACGACACACATAGTC CTTGTGTGGCCTTTCTGGGCTTGTGTCCTGAACTATAAAATGAGAGGGTGGCACTAAATGTTTTTTTCAG ATCTCTATAGAGGCTGGAATGGCCACAGAGAATCTAAATTTGAAAACAAACATGTCCTGAGGGTGTGCTC CAATACCACCCTTTAATACTCTCCTGAGATGTGAAGGCTGGAAATGAGAATGCCATATTATTGTTACTTG CAAACGATTAGTGTATCTGGGACATCCAAAAGAAGTAACTGAAAATTTATTTCTTTAAAAACAAAAAAAA CCATTACAGTGCTTTTGTAAAAACATTAATATTTAGAAGTACGTAGTGGTAATAAAAGGAAAATAGTTGT AAGACCTTCATTAAAAAGAAAAACCTAAAAAAAAAAACAAAACAAAACTCTGGATACAGGTGTATGATTT ACCTAACCAGACATAGCTTTCTTTTGGATAAAAAAAAAAAAAAAAAAAAAGCTCAGAAGTGCAGAACTGT ACAGATGTCCCTAAATCTATTAATTCAATGCTAAACGAAATAATCTCTTAACATGATAAAATTACACCAA ACTTCATCTGGAAAAATAAACACGTAATAATGAAAAAAGTTAGCCACTCCCACCTCCCCACTTAAAAAAG ACAAATGAAGAAATACTAGTCCAAGGCCAGGTGTGGTGGCTCACATCTGTAATCCCAACACTTTGAGAGG CTGAGGTGGGAGGACTGCTTGAACCCAGGAGTTCAAGACCAGCCTAGGCATCATGGCAAAACCCCATCTC TACAAAAAATACCAAAATAAAAAGAATTAGCTGGGCATGGTGGCACATACCTGTAGTCCCAGCTACTTGG GAGGCTGAGGTGAGAGGATCACTTGAGCCCGGAAGATCAAGGCGACAGTAAGCCATGATGGCACCACTGC ACTCCAGCCTGGGTGACAGAATGAAACCCTGTCTCAAAAAACAAACAAACAAAAACCAAACAAATTATAG GAAAATCAACATTTTAAACCAAAGAAGAGAAGGAGAAAGAAGGGAAGGGAAGCCATAAAAGTGTCTTTTT CAAATAGATCATGGGGGAAAAAAAAAAAAAGTATGACTTGGAATAGAGACAGCCTTACAAGCAGGATCTA AAACTCAGAATCCATTTTTTTAAATTGTGATAAATTTGACTATAGAAAAATGTAAACTTTGGATACAAAA GTACCATATTTAAAGTAAATAAGCTACAACTATTACATGACAGAGAAAATGTCCTCAAACTTCTAAGGAA CTTCTAACAAGTAGAAAAAAAACACACACAACCCCAAAGCAAACACCAATAGTCAATAAATATATGAAAG TGTTCAATGTTACTCATAATAAAGGCATACAAATCAAACCA ITGA11, NP_001004439.1 integrin alpha-11 precursor; AA; Homo sapiens (SEQ ID NO:20) MDLPRGLVVAWALSLWPGFTDTFNMDTRKPRVIPGSRTAFFGYTVQQHDISGNKWLVVGAPLETNGYQKT GDVYKCPVIHGNCTKLNLGRVTLSNVSERKDNMRLGLSLATNPKDNSFLACSPLWSHECGSSYYTTGMCS 134Patent Atty. Dkt. No.150-35-PCT RVNSNFRFSKTVAPALQRCQTYMDIVIVLDGSNSIYPWVEVQHFLINILKKFYIGPGQIQVGVVQYGEDV VHEFHLNDYRSVKDVVEAASHIEQRGGTETRTAFGIEFARSEAFQKGGRKGAKKVMIVITDGESHDSPDL EKVIQQSERDNVTRYAVAVLGYYNRRGINPETFLNEIKYIASDPDDKHFFNVTDEAALKDIVDALGDRIF SLEGTNKNETSFGLEMSQTGFSSHVVEDGVLLGAVGAYDWNGAVLKETSAGKVIPLRESYLKEFPEELKN HGAYLGYTVTSVVSSRQGRVYVAGAPRFNHTGKVILFTMHNNRSLTIHQAMRGQQIGSYFGSEITSVDID GDGVTDVLLVGAPMYFNEGRERGKVYVYELRQNLFVYNGTLKDSHSYQNARFGSSIASVRDLNQDSYNDV VVGAPLEDNHAGAIYIFHGFRGSILKTPKQRITASELATGLQYFGCSIHGQLDLNEDGLIDLAVGALGNA VILWSRPVVQINASLHFEPSKINIFHRDCKRSGRDATCLAAFLCFTPIFLAPHFQTTTVGIRYNATMDER RYTPRAHLDEGGDRFTNRAVLLSSGQELCERINFHVLDTADYVKPVTFSVEYSLEDPDHGPMLDDGWPTT LRVSVPFWNGCNEDEHCVPDLVLDARSDLPTAMEYCQRVLRKPAQDCSAYTLSFDTTVFIIESTRQRVAV EATLENRGENAYSTVLNISQSANLQFASLIQKEDSDGSIECVNEERRLQKQVCNVSYPFFRAKAKVAFRL DFEFSKSIFLHHLEIELAAGSDSNERDSTKEDNVAPLRFHLKYEADVLFTRSSSLSHYEVKPNSSLERYD GIGPPFSCIFRIQNLGLFPIHGMMMKITIPIATRSGNRLLKLRDFLTDEANTSCNIWGNSTEYRPTPVEE DLRRAPQLNHSNSDVVSINCNIRLVPNQEINFHLLGNLWLRSLKALKYKSMKIMVNAALQRQFHSPFIFR EEDPSRQIVFEISKQEDWQVPIWIIVGSTLGGLLLLALLVLALWKLGFFRSARRRREPGLDPTPKVLE KIAA1217, NM_019590.5 Homo sapiens KIAA1217 (KIAA1217), transcript variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:21) AGAACTGCGCTCTGAAGTTTCCAGAGAGCGAGGAGCTTTTGCGGCAGGCAGAGACAATGGAAGAAAATGA AAGCCAGAAATGTGAGCCGTGCCTTCCTTACTCAGCAGACAGAAGACAGATGCAGGAACAAGGCAAAGGC AATCTGCATGTAACATCACCAGAAGATGCAGAATGCCGCAGAACCAAGGAACGCCTTTCTAATGGAAACA GTCGTGGTTCAGTTTCCAAGTCTTCCCGCAATATCCCAAGGAGACACACCCTAGGGGGGCCCCGAAGTTC CAAGGAAATACTGGGAATGCAAACATCTGAGATGGATCGGAAGAGAGAAGCGTTCCTAGAACATCTGAAG CAGAAGTACCCCCACCACGCCTCTGCAATCATGGGTCACCAAGAGAGGCTGAGAGACCAGACAAGGAGCC CCAAACTGTCTCACAGTCCTCAACCACCCAGTCTGGGTGACCCGGTCGAGCATTTATCAGAGACGTCCGC TGATTCTTTGGAAGCCATGTCTGAGGGGGATGCTCCAACCCCTTTTTCCAGAGGCAGCCGGACTCGTGCG AGCCTTCCTGTGGTGAGGTCAACCAACCAGACGAAAGAAAGATCTCTGGGGGTTCTCTATCTCCAGTATG GAGATGAAACCAAGCAGCTCAGGATGCCGAATGAAATCACAAGTGCAGACACAATCCGTGCTCTCTTCGT AAGTGCCTTTCCACAGCAGCTCACCATGAAAATGCTGGAATCGCCCAGTGTCGCCATTTACATCAAAGAT GAAAGCAGAAATGTCTATTATGAATTAAATGATGTAAGGAACATTCAAGACAGATCACTCCTCAAAGTGT ACAACAAGGATCCTGCACATGCGTTTAATCACACACCAAAAACTATGAATGGAGACATGAGGATGCAGAG AGAACTTGTTTATGCAAGAGGAGATGGCCCTGGGGCCCCTCGCCCCGGATCTACTGCTCATCCACCCCAT GCGATTCCAAATTCCCCACCGTCTACTCCAGTGCCCCATTCCATGCCCCCCTCCCCGTCCAGAATTCCTT ATGGGGGCACCCGCTCCATGGTTGTTCCTGGCAATGCCACCATCCCCAGGGACAGAATCTCCAGCCTGCC AGTCTCCAGACCCATCTCTCCAAGCCCAAGCGCCATTTTAGAAAGAAGAGATGTCAAGCCTGATGAAGAC ATGAGTGGCAAAAACATTGCAATGTACAGAAATGAGGGTTTCTATGCTGATCCTTACCTTTATCACGAGG GACGGATGAGCATAGCCTCATCCCATGGTGGACACCCACTGGATGTCCCCGACCACATCATTGCATATCA CCGCACCGCCATCCGGTCAGCGAGTGCTTATTGTAACCCCTCAATGCAAGCGGAAATGCATATGGAACAA TCACTGTACAGACAGAAATCAAGGAAATATCCGGATAGCCATTTGCCTACACTGGGCTCCAAAACACCCC CTGCCTCTCCTCACAGAGTCAGTGACCTGAGGATGATAGACATGCACGCTCACTATAATGCCCACGGCCC CCCTCACACCATGCAGCCAGACCGGGCCTCTCCGAGCCGCCAGGCCTTTAAAAAGGAGCCAGGCACCTTG GTGTATATAGAAAAGCCACGGAGCGCTGCAGGATTATCCAGCCTTGTAGACCTCGGCCCTCCTCTAATGG AGAAGCAAGTTTTTGCCTACAGCACGGCGACAATACCCAAAGACAGAGAGACCAGAGAGAGGATGCAAGC CATGGAGAAACAGATTGCCAGTTTAACTGGCCTTGTTCAGTCTGCGCTTTTTAAAGGGCCCATTACAAGT TATAGCAAAGATGCGTCTAGCGAGAAAATGATGAAAACCACAGCCAACAGGAACCACACAGATAGTGCAG GAACGCCCCATGTGTCTGGTGGGAAGATGCTCAGTGCTCTGGAGTCCACGGTGCCTCCCAGCCAGCCTCC ACCTGTGGGCACCTCAGCCATCCACATGAGCCTGCTTGAGATGAGGCGGAGCGTGGCGGAACTCAGGCTC CAGCTCCAGCAGATGCGGCAGCTCCAGCTGCAGAACCAGGAGTTGCTGAGGGCAATGATGAAGAAGGCCG AGCTGGAAATCAGTGGCAAAGTGATGGAAACAATGAAGAGACTGGAGGATCCCGTGCAGCGACAGCGCGT CCTAGTGGAGCAAGAGAGACAAAAATATCTTCATGAGGAAGAGAAGATCGTCAAGAAGTTGTGCGAGTTG GAAGACTTTGTTGAAGACTTGAAGAAGGACTCCACGGCAGCCAGCCGATTGGTTACTCTGAAAGACGTGG AAGACGGGGCTTTCCTCCTGCGTCAAGTGGGAGAGGCTGTAGCTACCCTGAAAGGAGAATTTCCAACCTT ACAAAACAAGATGCGAGCCATCCTGCGCATAGAAGTGGAGGCCGTGCGGTTTCTGAAGGAGGAGCCACAC AAGCTGGACAGTCTCCTGAAGCGTGTGCGCAGCATGACAGACGTCCTGACCATGCTGCGGAGACATGTCA CTGATGGGCTCCTGAAAGGCACGGACGCAGCCCAAGCCGCACAGTACATGGCTATGGAAAAGGCCACAGC CGCAGAAGTCCTGAAGAGTCAGGAGGAGGCAGCCCACACCTCCGGCCAGCCCTTCCACAGCACAGGTGCC CCTGGCGATGCGAAGTCGGAAGTGGTGCCTTTGTCCGGCATGATGGTTCGCCACGCGCAGAGCTCCCCTG TGGTCATCCAGCCCTCCCAGCACTCCGTGGCCCTGCTGAACCCTGCTCAGAACTTGCCTCACGTGGCCAG CTCCCCAGCCGTCCCCCAGGAAGCAACCTCCACTCTGCAGATGTCGCAGGCTCCGCAGTCCCCACAGATA CCCATGAATGGGTCTGCCATGCAGAGCTTGTTCATTGAAGAAATCCACAGTGTGAGTGCCAAGAACAGGG CAGTGTCTATCGAGAAAGCAGAAAAGAAATGGGAGGAAAAAAGGCAAAATCTGGATCACTATAATGGGAA AGAGTTTGAGAAGCTCCTAGAAGAAGCTCAGGCCAATATCATGAAGTCAATACCAAATCTGGAGATGCCG CCAGCCACAGGCCCACTGCCAAGGGGAGATGCCCCAGTGGACAAGGTGGAACTTTCAGAAGATTCTCCAA 135Patent Atty. Dkt. No.150-35-PCT ATTCGGAACAGGACTTGGAAAAGCTGGGGGGAAAGTCGCCCCCTCCTCCTCCGCCACCTCCTCGTCGAAG CTACCTGCCAGGATCGGGACTCACCACCACGAGGTCAGGCGATGTGGTCTACACCGGCAGAAAGGAGAAC ATCACCGCTAAGGCAAGCAGTGAAGATGCTGGACCAAGCCCACAGACCAGAGCTACAAAATATCCAGCAG AGGAGCCTGCTTCAGCCTGGACCCCATCCCCACCGCCTGTCACCACCTCCTCCTCAAAGGATGAGGAGGA AGAAGAAGAAGAAGGAGACAAAATAATGGCAGAACTCCAGGCATTCCAGAAGTGTTCCTTTATGGATGTA AATTCAAACAGTCATGCTGAGCCATCCCGGGCTGACAGTCACGTTAAAGACACTAGGTCGGGCGCCACAG TGCCACCCAAGGAGAAGAAGAATTTGGAATTTTTCCATGAAGATGTACGGAAATCTGATGTTGAATATGA AAATGGCCCCCAAATGGAATTCCAAAAGGTTACCACAGGGGCTGTAAGACCTAGTGACCCTCCTAAGTGG GAAAGAGGAATGGAGAATAGTATTTCTGATGCATCAAGAACATCAGAATATAAAACTGAGATCATAATGA AGGAAAATTCCATATCCAATATGAGTTTACTCAGAGACAGTAGAAACTATTCCCAGGAAACTGTGCCTAA GGCCAGTTTCGGTTTCTCTGGCATTAGTCCATTAGAAGATGAAATAAACAAAGGGTCTAAAATCTCAGGC CTGCAATACTCTATACCTGACACCGAGAACCAGACGCTGAATTACGGAAAGACAAAGGAGATGGAAAAGC AAAATACGGATAAGTGTCACGTTTCCTCTCACACTAGACTAACAGAATCAAGCGTGCATGATTTTAAAAC AGAAGATCAAGAGGTTATCACGACAGATTTTGGCCAAGTTGTTCTAAGACCCAAGGAGGCAAGGCATGCT AACGTGAACCCTAATGAGGATGGAGAATCAAGTTCAAGTTCTCCCACTGAAGAAAATGCAGCCACTGACA ATATTGCCTTCATGATTACCGAAACCACTGTCCAGGTTCTTTCCAGTGGGGAGGTGCATGATATTGTTAG CCAAAAGGGAGAAGACATACAGACGGTTAATATCGATGCCAGAAAAGAGATGACCCCCCGACAAGAAGGG ACTGACAATGAGGATCCAGTCGTGTGCCTGGACAAGAAACCAGTGATCATCATTTTCGATGAGCCCATGG ACATCCGGTCTGCCTATAAGAGACTTTCAACTATCTTTGAGGAATGTGATGAGGAATTAGAGAGAATGAT GATGGAGGAAAAGATAGAGGAGGAGGAAGAGGAGGAAAATGGGGATTCTGTAGTCCAGAATAATAACACT TCCCAGATGTCTCATAAGAAGGTGGCCCCAGGCAATCTTAGAACCGGACAACAGGTGGAAACAAAGTCAC AGCCACACTCCCTGGCCACAGAGACCAGAAACCCAGGAGGACAGGAAATGAACAGAACGGAGCTGAACAA GTTCAGCCACGTGGATTCTCCAAATTCGGAATGCAAGGGTGAGGACGCGACCGATGACCAGTTTGAAAGC CCCAAGAAAAAGTTTAAATTCAAATTCCCTAAGAAGCAACTCGCCGCTCTCACTCAAGCCATTCGCACCG GAACTAAAACAGGGAAGAAGACTTTGCAAGTGGTAGTCTATGAAGAAGAGGAAGAGGATGGCACCCTGAA ACAGCACAAAGAAGCCAAGCGCTTCGAAATCGCTAGGTCTCAACCTGAAGACACCCCTGAAAACACAGTG AGGAGGCAAGAGCAGCCCAGCATCGAGAGTACATCTCCGATTTCAAGAACTGATGAAATTAGAAAAAACA CCTACAGAACATTGGATAGCCTGGAGCAGACCATTAAACAGCTCGAAAATACAATCAGTGAAATGAGTCC CAAAGCCCTAGTTGATACCTCATGTTCTTCCAACAGAGATTCTGTTGCAAGTTCATCCCACATAGCCCAA GAGGCCTCTCCCCGACCCTTGCTAGTTCCGGATGAAGGTCCCACTGCCCTAGAGCCCCCTACGTCGATAC CTTCAGCTTCACGTAAGGGCTCCAGCGGGGCCCCACAGACGAGCAGGATGCCTGTCCCCATGAGTGCCAA GAACAGACCCGGAACCCTGGACAAACCCGGCAAGCAGTCCAAACTGCAGGATCCCCGCCAATATCGTCAG GCTAATGGAAGTGCTAAGAAATCTGGTGGGGACTTTAAGCCTACTTCCCCCTCCTTACCTGCTTCTAAGA TTCCAGCCCTTTCTCCCAGCTCTGGGAAAAGCAGTTCTCTGCCCTCTTCTAGTGGTGACAGCTCTAACCT CCCTAATCCACCTGCTACTAAACCATCGATTGCTTCTAACCCTCTCAGCCCCCAAACAGGACCACCTGCT CACTCTGCCTCCCTCATCCCTTCTGTCTCTAATGGCTCTTTGAAGTTTCAGAGCCTCACTCATACAGGTA AAGGTCACCATCTTTCATTCTCACCGCAGAGTCAAAATGGCCGAGCACCCCCTCCTTTGTCATTTTCCTC CTCCCCTCCTTCTCCTGCCTCCTCCGTCTCACTGAATCAAGGTGCCAAGGGCACCAGGACCATCCATACT CCCAGCCTCACCAGCTACAAGGCACAGAATGGAAGTTCAAGCAAAGCCACCCCATCCACAGCAAAAGAAA CCTCTTAAAGGTCAAATCCTATTAGGCACAAGTCGGAGTTACATTTAAAAAAAATTAACAGTCTACAACA ACTGTTTTCACAAGAGAATGTAACATATTGCTGTATCGTTTGAGGCTTAATGCTAAATATGTGCTAAATA CTGGATTAATAGATTTCAGTAAAGCTCGTTCGTTTTGTTTGGTTTTCTTTTTACCTAGTTGCTATAGTGT CTACAGTCTATACTCAATACCTATAAAATGCAGTAAGCATGTGTTACAGAAAGAGGTTCTGGTGGGAGAG AAAGGTGCGTGTGAGACAGGAGAATTGTCTTAAGCATATAAAACATGTATGATTCCAGAATTTTAGTATG TTTTGTATAAAACTATTTTTCATTACGGAGACTAGAAGTGAACAGAGAATTACACAAGTGTGACTATACA AATTGTAAAACAGATACTATAATATTTCCTTTTATTTTAGTGTTATTTAGCTTTATTACAGATTTCTATT TTTGTCAAAACTTCATGGTTCCTTTCAAGATCTTTTTTGCCAAAACATTTTGATACTATAGCATTGTACA TTTGAAAGTAGTGTTCTAGACTATAAAACCAATGAACTTCTACATGAGCCCTACAGACAGGCATGTGTAG AAGGCAATTTATCAAACCTATTGCACTGCCATGAAAAGTGTGTATAATAATTTGCTAGCCCAAGCAAGCT AGTTTTCTTTGCTTGCTTCTTTTCTTTCTTTTTTCCTTCCTTTTTTTTTTTTTTTTCTTTTTTAACATGT TGAGATTCTCTAGTTGTTTTCTTTGGCGTATCTAACCCCTTCTTTTGTTTTCTGAGACCTGGTAACCCAC GCTCTTGCATTGTGGATTTTAAAATGTATACTCTGTACGGTTCTGTAAACCGAAAAACTTTTGTAAATAT ATAAATATACATAGACATAAAAATACTGTATGTGACAGCACATAGAGTAGTTTTCCCACACCAAAGTTAA TTTTTATGCATGCTTTAAAAGTATATATCGGGACCGGCAGAAATGGAAGTATCCATACATTTTTAAAAAG CAACAAGTTTGCACAGCTAGAGTGTTTTTGTAAATAAATGTATTTGTATAACACAGTCATGTAATATACA GAACTATAAGCAGAGACTTTGCAAAACTAAATAAAGGGCTGCATGCTTATTATTTTTTGTACCTTGTCAC TATAACTACTTCCTAGTCAAAGAACGAAATGTAACTGTTACCGAGTTAAATGTTTTTCCGCTTTGAGGGA TGTAACCACATCCACTCAGAGGACACTACTTTTCTGAAAGCTCTGGGGTGACTAATGATGAGTTCCTAAT AAATTAATTGCAAGTGTGGTGCCTTGGATGTGGCCTGTTGGCTCGCTTTCTTCTCTGTGGCTTATCAAGG TGTAGATGACAGAAAGCAAACCTGGATACAGAGTTTCCACCCTCAGTTCCTGGAGGGGCTCTTATTATTT TCTCTCTTTTTAAAAAACTTCCAGTAGAAGTAAAGTGGAAATAAAATGTCTTTATCA 136Patent Atty. Dkt. No.150-35-PCT KIAA1217, NP_062536.2 sickle tail protein homolog isoform 1; AA; Homo sapiens(SEQ ID NO:22) MEENESQKCEPCLPYSADRRQMQEQGKGNLHVTSPEDAECRRTKERLSNGNSRGSVSKSSRNIPRRHTLG GPRSSKEILGMQTSEMDRKREAFLEHLKQKYPHHASAIMGHQERLRDQTRSPKLSHSPQPPSLGDPVEHL SETSADSLEAMSEGDAPTPFSRGSRTRASLPVVRSTNQTKERSLGVLYLQYGDETKQLRMPNEITSADTI RALFVSAFPQQLTMKMLESPSVAIYIKDESRNVYYELNDVRNIQDRSLLKVYNKDPAHAFNHTPKTMNGD MRMQRELVYARGDGPGAPRPGSTAHPPHAIPNSPPSTPVPHSMPPSPSRIPYGGTRSMVVPGNATIPRDR ISSLPVSRPISPSPSAILERRDVKPDEDMSGKNIAMYRNEGFYADPYLYHEGRMSIASSHGGHPLDVPDH IIAYHRTAIRSASAYCNPSMQAEMHMEQSLYRQKSRKYPDSHLPTLGSKTPPASPHRVSDLRMIDMHAHY NAHGPPHTMQPDRASPSRQAFKKEPGTLVYIEKPRSAAGLSSLVDLGPPLMEKQVFAYSTATIPKDRETR ERMQAMEKQIASLTGLVQSALFKGPITSYSKDASSEKMMKTTANRNHTDSAGTPHVSGGKMLSALESTVP PSQPPPVGTSAIHMSLLEMRRSVAELRLQLQQMRQLQLQNQELLRAMMKKAELEISGKVMETMKRLEDPV QRQRVLVEQERQKYLHEEEKIVKKLCELEDFVEDLKKDSTAASRLVTLKDVEDGAFLLRQVGEAVATLKG EFPTLQNKMRAILRIEVEAVRFLKEEPHKLDSLLKRVRSMTDVLTMLRRHVTDGLLKGTDAAQAAQYMAM EKATAAEVLKSQEEAAHTSGQPFHSTGAPGDAKSEVVPLSGMMVRHAQSSPVVIQPSQHSVALLNPAQNL PHVASSPAVPQEATSTLQMSQAPQSPQIPMNGSAMQSLFIEEIHSVSAKNRAVSIEKAEKKWEEKRQNLD HYNGKEFEKLLEEAQANIMKSIPNLEMPPATGPLPRGDAPVDKVELSEDSPNSEQDLEKLGGKSPPPPPP PPRRSYLPGSGLTTTRSGDVVYTGRKENITAKASSEDAGPSPQTRATKYPAEEPASAWTPSPPPVTTSSS KDEEEEEEEGDKIMAELQAFQKCSFMDVNSNSHAEPSRADSHVKDTRSGATVPPKEKKNLEFFHEDVRKS DVEYENGPQMEFQKVTTGAVRPSDPPKWERGMENSISDASRTSEYKTEIIMKENSISNMSLLRDSRNYSQ ETVPKASFGFSGISPLEDEINKGSKISGLQYSIPDTENQTLNYGKTKEMEKQNTDKCHVSSHTRLTESSV HDFKTEDQEVITTDFGQVVLRPKEARHANVNPNEDGESSSSSPTEENAATDNIAFMITETTVQVLSSGEV HDIVSQKGEDIQTVNIDARKEMTPRQEGTDNEDPVVCLDKKPVIIIFDEPMDIRSAYKRLSTIFEECDEE LERMMMEEKIEEEEEEENGDSVVQNNNTSQMSHKKVAPGNLRTGQQVETKSQPHSLATETRNPGGQEMNR TELNKFSHVDSPNSECKGEDATDDQFESPKKKFKFKFPKKQLAALTQAIRTGTKTGKKTLQVVVYEEEEE DGTLKQHKEAKRFEIARSQPEDTPENTVRRQEQPSIESTSPISRTDEIRKNTYRTLDSLEQTIKQLENTI SEMSPKALVDTSCSSNRDSVASSSHIAQEASPRPLLVPDEGPTALEPPTSIPSASRKGSSGAPQTSRMPV PMSAKNRPGTLDKPGKQSKLQDPRQYRQANGSAKKSGGDFKPTSPSLPASKIPALSPSSGKSSSLPSSSG DSSNLPNPPATKPSIASNPLSPQTGPPAHSASLIPSVSNGSLKFQSLTHTGKGHHLSFSPQSQNGRAPPP LSFSSSPPSPASSVSLNQGAKGTRTIHTPSLTSYKAQNGSSSKATPSTAKETS NOX4, NM_016931.5 Homo sapiens NADPH oxidase 4 (NOX4), transcript variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:23) ACTCAGTCTTTGACCCTCGGTCCTCGCTCAGCGGCCCGGCAGGCCGCACAACTGTAACCGCTGCCCCGGC CGCCGCCCGCTCCTTCTCGGTCCGGCGGGCACAGAGCGCAGCGCGGCGGGGCCGGCGGCATGGCTGTGTC CTGGAGGAGCTGGCTCGCCAACGAAGGGGTTAAACACCTCTGCCTGTTCATCTGGCTCTCCATGAATGTC CTGCTTTTCTGGAAAACCTTCTTGCTGTATAACCAAGGGCCAGAGTATCACTACCTCCACCAGATGTTGG GGCTAGGATTGTGTCTAAGCAGAGCCTCAGCATCTGTTCTTAACCTCAACTGCAGCCTTATCCTTTTACC CATGTGCCGAACACTCTTGGCTTACCTCCGAGGATCACAGAAGGTTCCAAGCAGGAGAACCAGGAGATTG TTGGATAAAAGCAGAACATTCCATATTACCTGTGGTGTTACTATCTGTATTTTCTCAGGCGTGCATGTGG CTGCCCATCTGGTGAATGCCCTCAACTTCTCAGTGAATTACAGTGAAGACTTTGTTGAACTGAATGCAGC AAGATACCGAGATGAGGATCCTAGAAAACTTCTCTTCACAACTGTTCCTGGCCTGACAGGGGTCTGCATG GTGGTGGTGCTATTCCTCATGATCACAGCCTCTACATATGCAATAAGAGTTTCTAACTATGATATCTTCT GGTATACTCATAACCTCTTCTTTGTCTTCTACATGCTGCTGACGTTGCATGTTTCAGGAGGGCTGCTGAA GTATCAAACTAATTTAGATACCCACCCTCCCGGCTGCATCAGTCTTAACCGAACCAGCTCTCAGAATATT TCCTTACCAGAGTATTTCTCAGAACATTTTCATGAACCTTTCCCTGAAGGATTTTCAAAACCGGCAGAGT TTACCCAGCACAAATTTGTGAAGATTTGTATGGAAGAGCCCAGATTCCAAGCTAATTTTCCACAGACTTG GCTTTGGATTTCTGGACCTTTGTGCCTGTACTGTGCCGAAAGACTTTACAGGTATATCCGGAGCAATAAG CCAGTCACCATCATTTCGGTCATGAGTCATCCCTCAGATGTCATGGAAATCCGAATGGTCAAAGAAAATT TTAAAGCAAGACCTGGTCAGTATATTACTCTACATTGTCCCAGTGTATCTGCATTAGAAAATCATCCATT TACCCTCACAATGTGTCCAACTGAAACCAAAGCAACATTTGGGGTTCATCTTAAAATAGTAGGAGACTGG ACAGAACGATTTCGAGATTTACTACTGCCTCCATCTAGTCAAGACTCCGAAATTCTGCCCTTCATTCAAT CTAGAAATTATCCCAAGCTGTATATTGATGGTCCTTTTGGAAGTCCATTTGAGGAATCACTGAACTATGA GGTCAGCCTCTGCGTGGCTGGAGGCATTGGAGTAACTCCATTTGCATCAATACTCAACACCCTGTTGGAT GACTGGAAACCATACAAGCTTAGAAGACTATACTTTATTTGGGTATGCAGAGATATCCAGTCCTTCCGTT GGTTTGCAGATTTACTCTGTATGTTGCATAACAAGTTTTGGCAAGAGAACAGACCTGACTATGTCAACAT CCAGCTGTACCTCAGTCAAACAGATGGGATACAGAAGATAATTGGAGAAAAATATCATGCACTGAATTCA AGACTGTTTATAGGACGTCCTCGGTGGAAACTTTTGTTTGATGAAATAGCAAAATATAACAGAGGAAAAA CAGTTGGTGTTTTCTGTTGTGGACCCAATTCACTATCCAAGACTCTTCATAAACTGAGTAACCAGAACAA CTCATATGGGACAAGATTTGAATACAATAAAGAGTCTTTCAGCTGAAAACTTTTGCCATGAAGCAGGACT CTAAAGAAGGAATGAGTGCAATTTCTAAGACTTTGAAACTCAGCGGAATCAATCAGCTGTGTTATGCCAA AGAATAGTAAGGTTTTCTTATTTATGATTATTTAAAATGGAAATGTGAGAATGTGGCAAGATGACCGTCA CATTACATGTTTAATCTGGAAACCAAAGAGACCCTGAAGAATATTTGATGTGATGATTCACTTTTCAGTT 137Patent Atty. Dkt. No.150-35-PCT CTCAAATTAAAAGAAAACTGTTAGATGCACACTGTTGATTTTCATGGTGGATTCAAGAACTCCCTAGTGA GGAGCTGAACTTGCTCAATCTAAGGCTGATTGTCGTGTTCCTCTTTAAATTGTTTTTGGTTGAACAAATG CAAGATTGAACAAAATTAAAAATTCATTGAAGCTGAAATTCCATTTTCTGTGTTGTGTATAAACAGAGTA GCTTTAATTTGCAAGCACTCCAGGCAAATATATTAGATGTTTGAAAACACAGCACAAGACTCTGTATTGA TACGGGTACTTTGTGTCAATATCTAATCGTCTCCACTACTTATGCTAATACCTCTATTTGATATCTGAAG ACTATATGCTAACTGAACCTTCCTCAAATGTTGTTATAGTATCTATTTTTATATATTTTTTTCTTTTTAT TCCTCTCTCTAGGGAAATATGCCTTCCCTTAGCATGCATTAGACATAATGATTTAATAGGTCCCTTTCAT CTTCATTTAAATCTATCACTATTGCATGGTAATGAAAATATTCCTACTATAAATTATAAAGGGATATATA TATATGGATATATATATGTATATACACATATATATATACACACACACACACATATATATATATATATATA TATATACACATATACTAATAACTTTTCCCTTTTTTCAGCATTTTTGTCTCTATTATTATTATTGTTTTTT TCCCAGGTAGGGTTTGTCTTAGGCTGTAGCCTCTAAGGATAGTTAGTTAATTTGCACTTTGAGACCAAAG GACATCATGTGTGTCAGTAGGGACTGAATATAAGATTTATCTCCTTTGCCACACATTGGTTTATGATGGA GACATTGAAAGTCTAGTCATATTCCTGAACAGTAAAACCTGTATTTTACCTTTTAAGTAAGAGGAAATAT GATATTCTTATTCAAACTTAAGTTTAGAATCCAGAATATTACTGTCGCACTTTTTGGTATCCTGAGTTTC CATAGGGAACTATTGGGTTTAAAGTCACCGTTGGAACTACACTGTGTGATCTTATAAACTTATGTTCCCT GGCTATCATATTCTTGGCTCAGAACAATATTTCCCATTACTATCTTAAGAATTAAGGCATTCATGGCTCA CGCCTGTAATCCCGGCACTTTGGGAGGCCAAGGCAGGTGGATCACGAGGTCAGAGTTCAAGACCAGCCTG ACCAAGTTGGTGAAACCCCATCGCTACTAAAAATACAAATATTAGGCGGGTGTGGTGGCGGGTGCCTATA ATCCCAACTACTCGGGAGACTGAGGCAAAGAATCGCTTGAACCCGGTGGGCGGAGGTTGCAGTGAGCCAA GATTGCACCACTGCACTCCAGCCTGGGTGACAGAGCAAGATTCCATCTCAAAAAAAAAAAAAAAAAAAAA AAAAAAGAATTAAAGCATTCATACAGTTTAGTGATTTTGTTTAGTAGTCGGCTATCAATTGCTATCAAAT ATAACACTGCTGAAATCAGCAGTGTGACTTACCTTGCCATTGTTAAAATGTTACATAAAACATAACATGA TAGATGCTAAGGCCTTTTTTTGCTATAATTCACCAATAGCAATCAAGCATGCTAACCCATACTGAATGAT ATTTACTTGTAGATATTTCTTCCTTTCCTTGAAATTCTCCTTTCTATGGAAAGAAGATGAACCCAAAAAA GTGATAGGAAATGTGGAATGCTCATGCAGATTTAGCTCTGAAGGCATATTTAATAACTAGTATGTCTTGA CAACAGTCTTTAGATTAAAAAGAATTTTCATGGAAACATTTAACAGAAAGAACTAGTAAAAAGACACTTT GAGTTAGTCCAGGCTTAATGTGCAATACTGACTCTATACTGATCATAATTTATTTATGCGATCATATTAA TAGACCTAATTTCATTAAAACAGGTAGAAGATTTTTCAAAAGAAAGATGATGTTTCAAAGCTGGTCTGCC ATTCTAGATGAGCCTCCTTGCTTATTTAAGTTCCAGTAGGTGTTCAAATGTTAAATGTTAAACATAGGTC ATCTTTGCTTCTGCAGGGCTTCATCTTGCATGTTTAAGAGAACTTTGTTTTATTTTGAGGGATTATTTCT CTGGGGATCATTCTTATAATACAAGCCTTAAATCACTAATTTTAGTAGCAATAAATGTTAAAATTGAAA NOX4, NP_058627.2 NADPH oxidase 4 isoform a; AA; Homo sapiens (SEQ ID NO:24) MAVSWRSWLANEGVKHLCLFIWLSMNVLLFWKTFLLYNQGPEYHYLHQMLGLGLCLSRASASVLNLNCSL ILLPMCRTLLAYLRGSQKVPSRRTRRLLDKSRTFHITCGVTICIFSGVHVAAHLVNALNFSVNYSEDFVE LNAARYRDEDPRKLLFTTVPGLTGVCMVVVLFLMITASTYAIRVSNYDIFWYTHNLFFVFYMLLTLHVSG GLLKYQTNLDTHPPGCISLNRTSSQNISLPEYFSEHFHEPFPEGFSKPAEFTQHKFVKICMEEPRFQANF PQTWLWISGPLCLYCAERLYRYIRSNKPVTIISVMSHPSDVMEIRMVKENFKARPGQYITLHCPSVSALE NHPFTLTMCPTETKATFGVHLKIVGDWTERFRDLLLPPSSQDSEILPFIQSRNYPKLYIDGPFGSPFEES LNYEVSLCVAGGIGVTPFASILNTLLDDWKPYKLRRLYFIWVCRDIQSFRWFADLLCMLHNKFWQENRPD YVNIQLYLSQTDGIQKIIGEKYHALNSRLFIGRPRWKLLFDEIAKYNRGKTVGVFCCGPNSLSKTLHKLS NQNNSYGTRFEYNKESFS NPR3, NM_001204375.2 Homo sapiens natriuretic peptide receptor 3 (NPR3), transcript variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:25) GGCGCGAATCAATGAGATCAAATGCGAGGGAGATGCACCGTCAATTACAAACACTTGGACAAGTCTAACT TTTTTTTTCTTCTACAAAAACGCTTTCAAAAGCAACCTTAGCAACGCCCAAATAAGAAGCCACCTCTAAG CAAAATAGTATATGTATAAACGGAGGGCGAATATATACAAGTATATATATATGTATATTACAGACGCACA GGTTTACACCCGGTGAACTTTTTCTTTTTCTTTTTCTTTTTTTTTTAAGAAAAACTAGTGACATTGCAGA GAAGGACGCTTCCTCTCTATCTTTTGGCGCATTAGTGAAGGGGGTATTCTATTTTGTTAAAGCGCCCAAG GGGGCGCAGGGACCTTGGAGAGAAGAGTGGGGAGGAAAGAGGAAGGGTGGGTGGGGGGCAGAGGGCGAGT CGGCGGCGGCGAGGGCAAGCTCTTTCTTGCGGCACGATGCCGTCTCTGCTGGTGCTCACTTTCTCCCCGT GCGTACTACTCGGCTGGGCGTTGCTGGCCGGCGGCACCGGTGGCGGTGGCGTTGGCGGCGGCGGCGGTGG CGCGGGCATAGGCGGCGGACGCCAGGAGAGAGAGGCGCTGCCGCCACAGAAGATCGAGGTGCTGGTGTTA CTGCCCCAGGATGACTCGTACTTGTTTTCACTCACCCGGGTGCGGCCGGCCATCGAGTATGCTCTGCGCA GCGTGGAGGGCAACGGGACTGGGAGGCGGCTTCTGCCGCCGGGCACTCGCTTCCAGGTGGCTTACGAGGA TTCAGACTGTGGGAACCGTGCGCTCTTCAGCTTGGTGGACCGCGTGGCGGCGGCGCGGGGCGCCAAGCCA GACCTTATCCTGGGGCCAGTGTGCGAGTATGCAGCAGCGCCAGTGGCCCGGCTTGCATCGCACTGGGACC TGCCCATGCTGTCGGCTGGGGCGCTGGCCGCTGGCTTCCAGCACAAGGACTCTGAGTACTCGCACCTCAC GCGCGTGGCGCCCGCCTACGCCAAGATGGGCGAGATGATGCTCGCCCTGTTCCGCCACCACCACTGGAGC CGCGCTGCACTGGTCTACAGCGACGACAAGCTGGAGCGGAACTGCTACTTCACCCTCGAGGGGGTCCACG AGGTCTTCCAGGAGGAGGGTTTGCACACGTCCATCTACAGTTTCGACGAGACCAAAGACTTGGATCTGGA AGACATCGTGCGCAATATCCAGGCCAGTGAGAGAGTGGTGATCATGTGTGCGAGCAGTGACACCATCCGG 138Patent Atty. Dkt. No.150-35-PCT AGCATCATGCTGGTGGCGCACAGGCATGGCATGACCAGTGGAGACTACGCCTTCTTCAACATTGAGCTCT TCAACAGCTCTTCCTATGGAGATGGCTCATGGAAGAGAGGAGACAAACACGACTTTGAAGCTAAGCAAGC ATACTCGTCCCTCCAGACAGTCACTCTACTGAGGACAGTGAAACCTGAGTTTGAGAAGTTTTCCATGGAG GTGAAAAGTTCAGTTGAGAAACAAGGGCTCAATATGGAGGATTACGTTAACATGTTTGTTGAAGGATTCC ACGATGCCATCCTCCTCTACGTCTTGGCTCTACATGAAGTACTCAGAGCTGGTTACAGCAAAAAGGATGG AGGGAAAATTATACAGCAGACTTGGAACAGAACATTTGAAGGTATCGCCGGGCAGGTGTCCATAGATGCC AACGGAGACCGATATGGGGATTTCTCTGTGATTGCCATGACTGATGTGGAGGCGGGCACCCAGGAGGTTA TTGGTGATTATTTTGGAAAAGAAGGTCGTTTTGAAATGCGGCCGAATGTCAAATATCCTTGGGGCCCTTT AAAACTGAGAATAGATGAAAACCGAATTGTAGAGCATACAAACAGCTCTCCCTGCAAATCATCAGGTGGC CTAGAAGAATCGGCAGTGACAGGAATTGTCGTGGGGGCTTTACTAGGAGCTGGCTTGCTAATGGCCTTCT ACTTTTTCAGGAAGAAATACAGAATAACCATTGAGAGGCGAACCCAGCAAGAAGAAAGTAACCTTGGAAA ACATCGGGAATTACGGGAAGATTCCATCAGATCCCATTTTTCAGTAGCTTAAAGGAAGCCCCCCACTTTT TTTTTTTCTGCCTGAGATTCTTTAAGGAGATAGACGGGTTGAAAGACATCAATGAAACAGAAGGGGCGTT CTTGAAGAATTCATAATTTTAAGCAGTTAGTAATTTCATTTTAAAATTTCTGTAGAAGCTCAGGAATTAT GATTAATCACCATCTGCCTCCAGGCCTTTCATCTCATGACAAACAAATATAATAATGATATCGTGTCACT CTGTTAAATGTTCATACTGTTTCAAGCCCATATGATTAGATTTATGTTTTTAAAATCTGTTGTCTCCATA TCTTGATGGCTTTTGGGAGCATTTCACACAAGGATATAAAATGCGGTTTTCTTAAATGAAATGTTTTGTA GCTAGAATAAAATCATTTTTACAAGTACAGCATTCTTGGAAAGAATTTAACACCCAAAAAGGGGAAAATG TAATGAAAAATCTCAAGGTTGGAAATACAGCCTTACTCTCTCTAGAGCTGGAGGACAGGTTTGTGGTTGA GGACTTCTCTGTCCGATGTCTACATTCAGGTTCTGACTTCATATCTTGAAAAAGGATTTCCTCCCTGTCT TTTTCAGTGTCTCATAAACGCTACTCTGGATTGTTGTAAATATTAGTGAGATGGGAGGATTTACAGAAGA AAAGCAAGTCAAAAATATTTCCTTTTTGATGTAAAAAAAAAAAGCCCTATTTCGCACTAACATTTTATTT TACAAGTATTTTAATCTTATATTTTGGTATTAGAAAAATTTGTCTATTTTTTCATTTTGAAGATTAAATG TTGCTTACATTTTAAAAGCATGGGTGAAGTGTACAACAAACCAATAATGATAAAAAATACTTCTCTTTTT CTCCCTGTTTCCCTTTTTCCCTTGGCCACAGCCAAATGCTAATTGCTGCTTTAATTACAGAGATGTGTAA ATGTATTCAGATTACAAACTCTACAGGAATACATCAACATTTTAACTCTTTTGCGTTTTTACTGTTTAAC TGTTTTAAATGCAAGTTATTTTAGGGTGACACTCCTTCCAGTTCTGGCCAGATCATGAGTTTCAAGATCA AGAGTAAAAAGTTATTAGAATTAAACAGTTTTATAAAGGGAGGCAGCCCTTTTCCCTCAAGAACAACTTT GTTGAGAGTTACTACTTGACAGCAAGCACAGAAATGACAAATTTAAAACTTTTACACATGGCATTTACCA AAATTCCCAGTGATTATTTTGTTTAAAAGAGGGAACCTAAATATCTACTCTATTCCCTTTCAGTTAACTC CACAGAACTTTGTAGGCATCCATGAATACCTGTAATAGTGGGTTAGGTGTGGAGATAAGGAATTTGGACA AAGTTGAGTAAGTTTTTACTGGGTATCTGCTTTGCACCCAGTAGTCTGCAACATGAGTTTAAACTCAGGT TACTACTTTCACTTATACTTTATGGAGAAGATAGACAGTGAGGGAGGAATGGGAAGCTGTCATGAGAGTG CACCGTCTTGGAATTACATAACTGGGGTCTTTCCTCAATAACATTTTGAGCATCTGAAAAATAGTTTAAA AAATTGTCTTAATATCTATTAAAAGGCATGTCTAGTGAGGAAACAGGAGAGTCTGAGCAATCCCTTGGTG GCGATGAAGGTGGTAGTTCACACAAGTAACAGTGGAGGCAAAGGTAAGCGCAAGCTGCCTGTCCCAGATG CTGGCCCATGTGTGAGTGCTTCCCTGGAGAAGTCCGCTTCTGTTGCTCCCACCTGAGTCACAGTTAACAG ATTATTTCTGTGTGAGGCACATTTCCCTTCTGTTGTTTAAGAAATGGGAGCTGGGAGGCAGCTGAGAGGG CGTGATAAAAGAATTAAGTGTGATCAACTGAAACAACTATGTTGTAGTTCTCCATGCTGGATGCAAAGGA AAAAGTGTCGAATTCCAAAAAGGATGGAAGAAGAAGGCAAGAAGGGCAAACTCCAGAAGTTCTAGTGCAG GAAGAGAGTTTGAGAAGTAAAATCCAGGCAAGCAAAGCGTTGTACCACTTGGGACTCCCCAAAGTGAAAC AGCAAGGAAGGATTGTGTCCATCTTACTTACTTGAATTGGAGAGCTTGTTTCTCTCTCATTTTTATTTTT CAATGATGTTTTCTTTATATTTTAGAGATATTCATTTTCTCTTATCTTGTGCTTGTAAAAAGCATTTACA TTTCAAGTCTATGTGCTTATTACAGGGGAAAAATAATCTACCTGGTTGCAGTCTTTGAGTATAAACATTT CTAACCTTTTTAAAACTTCTATAGCAGCCCATTAACACTAACATTTTTAGAGCAAATATATTCTATTTTA ACTTCAGGTAGAGGAATAGTCCTAAACTTAATATGATAGCTCTAGATAAGATCTTAGAGATAAGTGAGCA TTTAGTATTCTAAAAGTGGCAGAACAAATCATGAGGTTTCTGGATGCTATACCAATTTAAAATCAATTCT TATGTTAATATTGATTGCTTATTTACATGTCAGTCATCTACTTTTTTTCTTTGAAATCTGCATATGGGTT ACAAAAACTCTGTTAGGTTTTGAAAATTCCATTAAGTTGGAAACCTTGGTTAAAAATGTAGGTGCCTGGC CCATGGTTACCCTGGATTCAGGTCTCTCATGATTATATTTGGGGATTTACGTTCCTAACTGCTAAGCAAC ATCTTTGACAACTAGTAATTCATACTCTACTAGTAGTCACATGTCATATAGTAAAATAAATAGGGCTTTA GTTCTTAAGTAATTCTATAGGATTTTACCCTGAAATCCAGGGTGTTCAGATTTCAAAAAGGATAATTTAT CAGTATTTTCTCATCCAGTCAAACTTCAGCTGACATTGATACAGGTCAAAATGCGTAGATGCTTTTTGGT GTTGGAAATAAGTGTCTGTCTTATGGTCATCATTGTCTTCTTAGATTTTTGGGTAGGGGGGCCAGGTAGG GGGAGACTCAGAAATAAAAGCGTTCCCCAGATAACTTCAATCTGGAAAGAATTTTTTGTATAGAGTCCAT CTCTCCCTCAAGACTGACCACAGGTTTCATGAGAAGGTCCCTGAAAACATCACATTTCTCTGAAGAACCA TCAACTTGTCTTTTCTTGAACCACAGGAATGGTTCTACAGACCCTACTATAATTCTTCACATTTCAGAAC CCATGTTTAATGGAGGGAAGAGAGAAATGCATGGGAAAAGAACACCTCCTTTTCTCCTTTCTCTTAAATT CAAAGACGTTTGCTTTGGAATGCCCTCACTTCTCCCTATTCACAGGCTTCTAAAATCATTAATTTACTCA AGGCACATGTGCCTTCTTTGCCCCAAATGCATCACTTTCCTTTTAGTTATGGCTGATTTTGGGTGTGTGT GTGTAAGACATGCAGTCAACAATGAGATGAAGGCCATTGCATAGATCTCATGCAGATAGTGATGGATTCA GAAAGTAGGTTCCAGTGGCGTCACTACCTTCTTGTAAGCCAGTATACACTGGCTATTTGTGGAAATCTCT 139Patent Atty. Dkt. No.150-35-PCT TTGGGAGATCAAATAGAGTATTATGCCACTGTGAGTGTTTATAAACTGGAAGGAACAAGTACCTGTGTTT CTTGGGACACAAAGCACTCAGATCCTGAGTGGATGCAGACATGAGAGTAAATGTCAGCCCAAATTAGGCC CCTCGACCTACAGACATTTCATGGGTTTTATTTAATCACACCCCATGGTTTGGGGCTACATGAGGAAGTT GGTAATGAGCTGAATTTCTTATTCAGTGGAAAAAACTGAAACTGTCTAAAAACACGGGATATATTTTAGA GGCAATTGTGGAAGCGGAGAGAATGAGATGATGGTGTTCAGAGGGACCAGCTTCTTTTTCAGTTGTCTTT AGAACTCAAGAATAATCAATAATTTAGTGCCCCTTCAACAGCCATACTCAGCAAGAAGAATCAGAAGCTT GATCCTCTAACAGAAATAGAAGAGGGTAGCTTTGCCCATTGCCACTGTCTTTACTGCCCCTTCTGCCCCT CCACCCACATCCACATTCAGCATCACTCCAAGGATGTGTCAGCATCTTGCCCATGCAGGTAGAAATTTGT GAGTAGGCCTCCATACTTCCTCGGGGGAAGAAAGAGAAACTAGTGCTGGTTTTAAGAATGTAGCTGGCTT TTCATCAGAACCCTTATGCTAACCTGACCACACTTGCTCTCGGGGAAGTTCAAGCCTGTGATGTGCATAA ACTCCAACAAGCCTGGCTTTGGTGTTCAGCATGCACATTCCATAAATATCTCTTGCAGGCATACCCCACA GCTAGACTGCAGGATTAAAATAACTTCCAAAAGGTGCTGGATTGGAGTTTGTTCAAATTTCTCATTAACC ACTAATGTTAATTCATACCAAATGCAAAGTATTCTAAACCAGCTGATGCTGTCAGTGTTCAAGTTTTAAG TGACTTCAAACACAATGGAAGTGTTTCAATGGGAGCCAGATCTCATGAGTAAAAATCCATTTTATAATAG CTCTGTGATATATCAGTGGGAGATGATTCATAGGGGAGAGATTTGAACAAGCAGAATTAAGTGTTAGCAA AAATGCTGCATTGCTTTGATTCATGTTTAAAGACCTAAATTTCTATGCACAAGGAATAAAGGGCCTACTT ACCAAGTGTAAATCACAACATAGGCTACCAAAATATTTCTTATTTGCTAGGAGAACAAAGCTGTCACGGT GCATGATAGTTGGACAGAGATGGCTAAAAAAGAGGCAAATTCAGATTTGGAAACAGGGTGGCCTCTTCAT TATTTATTGCCAAGATCTGAAAATCTTCAACATCTTATAAGACAACAATGAAGTAGCCCCTGAACAGCAT GGAGTTGCTGTGAGTTTGTTCGTTGCAGACCTTTGTGTTGGGTCCTGGGAATCTGAGCTTTGTTCCCTGT GCATGGTGGATAATTGAAACCAAGAGGACATGGGATAGACCTTGTGACAGACCAATTCTGTGACCCCTGT CTTCTGGGTCACATTATTCATTGTTGATTTAAATACAGGACTACCAAACAGTACAAATCTATCATGAGTC TGGTAGAAAAGTAAAAGTAAAAGCTGCACACGTTACATACTGTTTATTGTTCTAATGTACAACTAACTAT TTGCATATAATGTGATTTAATTTATTGCTGTTTTGTGTAGAAAAGGAGAACTAATGACTGTGGATATAAC CCATGTTTTGTATAATATATTTTATTTCTTGTGCGAACTGGTCATTTAAAATATCTACTTCATTTGATGT TTGGATATAAATGTGTATGTGTCCTTGTAAATGTTTCTATCAAGCAAGAATGCCACGTACTCAGAGTATA ACAATGTGTTCTCATTAAAAAATACATCCCACGGAAA NPR3, NP_001191304.1 atrial natriuretic peptide receptor 3 isoform 1 precursor; AA; Homo sapiens(SEQ ID NO:26) MPSLLVLTFSPCVLLGWALLAGGTGGGGVGGGGGGAGIGGGRQEREALPPQKIEVLVLLPQDDSYLFSLT RVRPAIEYALRSVEGNGTGRRLLPPGTRFQVAYEDSDCGNRALFSLVDRVAAARGAKPDLILGPVCEYAA APVARLASHWDLPMLSAGALAAGFQHKDSEYSHLTRVAPAYAKMGEMMLALFRHHHWSRAALVYSDDKLE RNCYFTLEGVHEVFQEEGLHTSIYSFDETKDLDLEDIVRNIQASERVVIMCASSDTIRSIMLVAHRHGMT SGDYAFFNIELFNSSSYGDGSWKRGDKHDFEAKQAYSSLQTVTLLRTVKPEFEKFSMEVKSSVEKQGLNM EDYVNMFVEGFHDAILLYVLALHEVLRAGYSKKDGGKIIQQTWNRTFEGIAGQVSIDANGDRYGDFSVIA MTDVEAGTQEVIGDYFGKEGRFEMRPNVKYPWGPLKLRIDENRIVEHTNSSPCKSSGGLEESAVTGIVVG ALLGAGLLMAFYFFRKKYRITIERRTQQEESNLGKHRELREDSIRSHFSVA OGN, NM_033014.4 Homo sapiens osteoglycin (OGN), transcript variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:27) ATTCACCCTCCCACTTGGGGCTAATGCACAGACATGAACATCTATTGAGGAAAACCACAAAAAACTTCAA AACAGCTACAACGGTATCCTAAGAATATTTCAATTAAATATTAGTATGTCTGCTGAAGGCACTTAATTAT TAAGAAACTTAAAATTATCAATCTTTCTTGAATTTCTGATAGAGAAGTAAAACTATTTTCCAAAACTATT TTTCAGAATGTTCACTGATACATAAAAACTGCTAGCATCTAATTAAAGATCACTAAGGGTTAAATACTGT TCTCTGGCCCTTACTGCGCACACCCTGCCAAAACATCCTCTAAGCTTTTAAATATTGCTTCGATGGTCTG AATTTTTATTTCCAGGGAAAAAGAGAGTTTTGTCCCACAGTCAGCAGGCCACTAGTTTATTAACTTCCAG TCACCTTGATTTTTGCTAAAATGAAGACTCTGCAGTCTACACTTCTCCTGTTACTGCTTGTGCCTCTGAT AAAGCCAGCACCACCAACCCAGCAGGACTCACGCATTATCTATGATTATGGAACAGATAATTTTGAAGAA TCCATATTTAGCCAAGATTATGAGGATAAATACCTGGATGGAAAAAATATTAAGGAAAAAGAAACTGTGA TAATACCCAATGAGAAAAGTCTTCAATTACAAAAAGATGAGGCAATAACACCATTACCTCCCAAGAAAGA AAATGATGAAATGCCCACGTGTCTGCTGTGTGTTTGTTTAAGTGGCTCTGTATACTGTGAAGAAGTTGAC ATTGATGCTGTACCACCCTTACCAAAGGAATCAGCCTATCTTTACGCACGATTCAACAAAATTAAAAAGC TGACTGCCAAAGATTTTGCAGACATACCTAACTTAAGAAGACTCGATTTTACAGGAAATTTGATAGAAGA TATAGAAGATGGTACTTTTTCAAAACTTTCTCTGTTAGAAGAACTTTCACTTGCTGAAAATCAACTACTA AAACTTCCAGTTCTTCCTCCCAAGCTCACTTTATTTAATGCAAAATACAACAAAATCAAGAGTAGGGGAA TCAAAGCAAATGCATTCAAAAAACTGAATAACCTCACCTTCCTCTACTTGGACCATAATGCCCTGGAATC CGTGCCTCTTAATTTACCAGAAAGTCTACGTGTAATTCATCTTCAGTTCAACAACATAGCTTCAATTACA GATGACACATTCTGCAAGGCTAATGACACCAGTTACATCCGGGACCGCATTGAAGAGATACGCCTGGAGG GCAATCCAATCGTCCTGGGAAAGCATCCAAACAGTTTTATTTGCTTAAAAAGATTACCGATAGGGTCATA CTTTTAACCTCTATTGGTACAACATATAAATGAAAGTACACCTACACTAATAGTCTGTCTCAACAATGAG TAAAGGAACTTAAGTATTGGTTTAATATTAACCTTGTATCTCATTTTGAAGGAATTTAATATTTTAAGCA AGGATGTTCAAAATCTTACATATAATAAGTAAAAAGTAAGACTGAATGTCTACGTTCGAAACAAAGTAAT ATGAAAATATTTAAACAGCATTACAAAATCCTAGTTTATACTAGACTACCATTTAAAAATCATGTTTTTA 140Patent Atty. Dkt. No.150-35-PCT TATAAATGCCCAAATTTGAGATGCATTATTCCTATTACTAATGATGTAAGTACGAGGATAAATCCAAGAA ACTTTCAACTCTTTGCCTTTCCTGGCCTTTACTGGATCCCAAAAGCATTTAAGGTACATGTTCCAAAAAC TTTGAAAAGCTAAATGTTTCCCATGATCGCTCATTCTTCTTTTATGATTCATACGTTATTCCTTATAAAG TAAGAACTTTGTTTTCCTCCTATCAAGGCAGCTATTTTATTAAATTTTTCACTTAGTCTGAGAAATAGCA GATAGTCTCATATTTAGGAAAACTTTCCAAATAAAATAAATGTTATTCTCTGATAAAGAGCTAATACAGA AATGTTCAAGTTATTTTACTTTCTGGTAATGTCTTCAGTAAAATATTTTCTTTATCTAAATATTAACATT CTAAGTCTACCAAAAAAAGTTTTAAACTCAAGCAGGCCAAAACCAATATGCTTATAAGAAATAATGAAAA GTTCATCCATTTCTGATAAAGTTCTCTATGGCAAAGTCTTTCAAATACGAGATAACTGCAAAATATTTTC CTTTTATACTACAGAAATGAGAATCTCATCAATAAATTAGTTCAAGCATAAGATGAAAACAGAATATTCT GTGGTGCCAGTGCACACTACCTTCCCACCCATACACATCCATGTTCACTGTAACAAACTGAATATTCACA ATAAAGCTTCTGAGTAACACTTTCTGATTACTCATGATAAACTGACATGGCTAACTGCAAGAATTAAATC TTCTATCTGAGAGTAATAATTTATGATGACTCAGTGGTGCCAGAGTAAAGTTTCTAAAATAACATTCCTC TCACTTGTACCCCACTAAAAGTATTAGACTACACATTACATTGAAGTTAAACACAAAATTATCAGTGTTT TAGAAACATGAGTCCGGACTGTGTAAGTAAAAGTACAAACATTATTTCCACCATAAAGTATGTATTGAAA TCAAGTTGTCTCTGTGTACAGAATACATACTTATTCCCATTTTTAAGCATTTGCTTCTGTTTTCCCTACC TAGAATGTCAGATGTTTTTCAGTTATCTCCCCATTTGTCAAAGTTGACCTCAAGATAACATTTTTCATTA AAGCATCTGAGATCTAAGAACACAATTATTATTCTAACAATGATTATTAGCTCATTCACTTATTTTGATA ACTAATGATCACAGCTATTATACTACTTTCTCGTTATTTTGTGTGCATGCCTCATTTCCCTGACTTAAAC CTCACTGAGAGCGCAAAATGCAGCTTTATACTTTTTACTTTCAATTGCCTAGCACAATAGTGAGTACATT TGAATTGAATATATAATAAATATTGCAAAATAAAATCCATCTAAATAGAAGGGTTCTGTTTTATTTGGAA AAATTGAATCTTTAAACTATCATAATCTTGAATGACTGTCATCTTTCTAGTTTTCAGAAAAATAATGTAT TCCTATATTATTTTTATGATAAAACTTATGGAGCAAAACACCATCAAATAACTCTCAAATTAAGAAAAAA TTCAAAAGTCAGTAGTTTTAGATAAGATAATGATAAGGGAGAAAGAACATTGGTAAAAGGTATGAATTCC AGAATTAAAGAAATAATTTGGGGATTTCTAGATAAGAGGATATATATGAACATGCATACCTTACACCTTC ATATACACAACCTTAAATCACAAATAAAACAAAATAAACAATACAAATTATACCACCAAGATTCAGAAGA TATCAGACGAAATAATTAGAGAAAGTAAAAATATGCTGTCTCCATTATATTCATAATGTTTCATTCTTGA CACTAATAATTAGAGGCTTTAAATTTTTAAATGATTTACTTTTTACTAACATTGCTGAAAAAAACTAAAG ACATACATAAATGGAAAGATGTCTTGTGTTTATGGATGGTAAGATTTAATGTTGTTAAGACAACAATACT ATCCAATATGATATGCAGACTGAACACAGTTGCCATCAAAATCTCAATGATGCTTTCACACAAATAAAAT GGAACTTCAAGAGACCCCCAAATAAAGAGAAGAATCTTGAAAATAAGAA OGN, NP_148935.1 mimecan isoform 2 precursor; AA; Homo sapiens (SEQ ID NO:28) MKTLQSTLLLLLLVPLIKPAPPTQQDSRIIYDYGTDNFEESIFSQDYEDKYLDGKNIKEKETVIIPNEKS LQLQKDEAITPLPPKKENDEMPTCLLCVCLSGSVYCEEVDIDAVPPLPKESAYLYARFNKIKKLTAKDFA DIPNLRRLDFTGNLIEDIEDGTFSKLSLLEELSLAENQLLKLPVLPPKLTLFNAKYNKIKSRGIKANAFK KLNNLTFLYLDHNALESVPLNLPESLRVIHLQFNNIASITDDTFCKANDTSYIRDRIEEIRLEGNPIVLG KHPNSFICLKRLPIGSYF PI16, NM_153370.3 Homo sapiens peptidase inhibitor 16 (PI16), transcript variant 1, mRNA; DNA; Homo sapiens(SEQ ID NO:29) AGAAGGAGAGACGGCTGGCCACCATGCACGGCTCCTGCAGTTTCCTGATGCTTCTGCTGCCGCTACTGCT ACTGCTGGTGGCCACCACAGGCCCCGTTGGAGCCCTCACAGATGAGGAGAAACGTTTGATGGTGGAGCTG CACAACCTCTACCGGGCCCAGGTATCCCCGACGGCCTCAGACATGCTGCACATGA...

Claims

Patent Atty. Dkt. No.150-35-PCT CLAIMS 1. A method for determining a permissive cancer-associated fibroblast (permCAF) subtype or a restraining cancer-associated fibroblast (restCAF) subtype of a tumor in a biological sample, the method comprising: (a) obtaining gene expression levels for each of the following genes in the biological sample, ABCA8, ANK2, BICD1, CHRDL1, CNIH3, COL11A1, ETV1, FBLN5, IGFL2, ITGA11, KIAA1217, NOX4, NPR3, OGN, PI16, SCARA5, TGFBR3, and VSNL1; (b) performing a pair-wise comparison of the gene expression levels for each permCAF and restCAF pair in a row as follows: permCAF restCAF Coefficient(c) calculating a Top Scoring Pair (TSP) Score for the biological sample, wherein the calculating comprises: (i) assigning a value of 1 for each pair for which a permCAF gene of the pair has a higher expression level than a restCAF gene of the pair, and a value of 0 for each pair for which the permCAF gene of the pair has a lower expression level than the restCAF gene of each pair; 146Patent Atty. Dkt. No.150-35-PCT (ii) multiplying each assigned value by the coefficient listed above corresponding to each pair to calculate nine individual pair scores; and (iii) summing the nine individual pair scores together along with a baseline effect (intercept = -8.4) to calculate the TSP Score for the biological sample; and (d) converting the TSP Score to a subtype probability using the inverse-logit transformation subtype probability = expTSP Score / (1 + expTSP Score), wherein if the subtype probability is greater than or equal to 0.5, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.5, the tumor subtype is determined to be a restCAF subtype.

2. The method of claim 1, wherein the tumor is a pancreatic ductal adenocarcinoma (PDAC), a mesothelioma, a urothelial carcinoma, or a renal cell carcinoma tumor.

3. The method of claim 1, wherein the biological sample comprises a fresh sample, a frozen sample, or a formalin fixed paraffin-embedded sample.

4. The method of claim 1, wherein the gene expression levels are obtained by microarray analysis, RNAseq, quantitative RT-PCR, next-gen sequencing, multiplexed direct digital counting, or a combination thereof.

5. A method of determining a prognosis for a subject with a cancer, the method comprising: (a) determining if a tumor in a biological sample from the subject with cancer is a permissive cancer-associated fibroblast (permCAF) subtype or a restraining cancer-associated fibroblast (restCAF) subtype by obtaining gene expression levels for each of the following genes in the biological sample ABCA8, ANK2, BICD1, CHRDL1, CNIH3, COL11A1, ETV1, FBLN5, IGFL2, ITGA11, KIAA1217, NOX4, NPR3, OGN, PI16, SCARA5, TGFBR3, and VSNL1; (b) performing a pair-wise comparison of the gene expression levels for each permCAF and restCAF pair in a row as follows: permCAF restCAF Coefficient147Patent Atty. Dkt. No.150-35-PCT IGFL2 CHRDL1 1.94 NOX4 OGN 230(c) calculating a Top Scoring Pair (TSP) Score for the biological sample, wherein the calculating comprises: (i) assigning a value of 1 for each pair for which a permCAF gene of the pair has a higher expression level than a restCAF gene of the pair, and a value of 0 for each pair for which the permCAF gene of the pair has a lower expression level than the restCAF gene of each pair; (ii) multiplying each assigned value by the coefficient listed above corresponding to each pair to calculate nine individual pair scores; and (iii) summing the nine individual pair scores together along with a baseline effect (intercept = -8.4) to calculate the TSP Score for the biological sample; (d) converting the TSP Score to a subtype probability using the inverse-logit transformation subtype probability = expTSP Score / (1 + expTSP Score), wherein if the subtype probability is greater than or equal to 0.5, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.5, the tumor subtype is determined to be a restCAF subtype; and 148Patent Atty. Dkt. No.150-35-PCT (e) if the tumor subtype is found to be a permCAF subtype, determining the prognosis for the subject to be poor.

6. The method of claim 5, wherein the cancer is a pancreatic ductal adenocarcinoma (PDAC), a mesothelioma, a urothelial carcinoma, or a renal cell carcinoma.

7. The method of claim 5, wherein the biological sample comprises a fresh sample, a frozen sample, or a formalin fixed paraffin-embedded (FFPE) sample.

8. The method of claim 5, wherein the gene expression levels are obtained by microarray analysis, RNAseq, quantitative RT-PCR, next-gen sequencing, multiplexed direct digital counting, or a combination thereof.

9. A method for identifying a differential treatment strategy for a subject diagnosed with cancer, the method comprising: (a) determining if a tumor in a biological sample from the subject with cancer is a permissive cancer-associated fibroblast (permCAF) subtype or a restraining cancer-associated fibroblast (restCAF) subtype by obtaining gene expression levels for each of the following genes in the biological sample ABCA8, ANK2 , BICD1, CHRDL1, CNIH3, COL11A1, ETV1, FBLN5, IGFL2, ITGA11, KIAA1217, NOX4, NPR3, OGN, PI16, SCARA5, TGFBR3, and VSNL1; (b) performing a pair-wise comparison of the gene expression levels for each permCAF and restCAF pair in a row as follows: permCAF restCAF CoefficientPatent Atty. Dkt. No.150-35-PCT ITGA11 FBLN5 1.56 CNIH3 SCARA5 187(c) ca cuat ng a op Scor ng a r ( S ) Score or t e biological sample, wherein the calculating comprises: (i) assigning a value of 1 for each pair for which a permCAF gene of the pair has a higher expression level than a restCAF gene of the pair, and a value of 0 for each pair for which the permCAF gene of the pair has a lower expression level than the restCAF gene of each pair; (ii) multiplying each assigned value by the coefficient listed above corresponding to each pair to calculate nine individual pair scores; and (iii) summing the nine individual pair scores together along with a baseline effect (intercept = -8.4) to calculate the TSP Score for the biological sample; and (d) converting the TSP Score to a subtype probability using the inverse-logit transformation subtype probability = expTSP Score / (1 + expTSP Score), wherein if the subtype probability is greater than or equal to 0.5, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.5, the tumor subtype is determined to be a restCAF subtype; and (e) identifying a differential treatment strategy for the subject based on the subtype assignment.

10. The method of claim 9, wherein the cancer is a pancreatic ductal adenocarcinoma (PDAC), a mesothelioma, a urothelial carcinoma, or a renal cell carcinoma.

11. The method of claim 9, wherein the biological sample comprises a fresh sample, a frozen sample, or a formalin fixed paraffin-embedded (FFPE) sample. 150Patent Atty. Dkt. No.150-35-PCT 12. The method of claim 9, wherein the gene expression levels are obtained by microarray analysis, RNAseq, quantitative RT-PCR, next-gen sequencing, multiplexed direct digital counting, or a combination thereof.

13. The method of claim 9, wherein if the tumor is identified as the restCAF subtype, the differential treatment comprises a treatment targeting a cancer expressing the restCAF subtype.

14. The method of claim 13, wherein the treatment targeting the restCAF subtype comprises an anti-PD-L1 immunotherapy in combination with chemotherapy.

15. The method of claim 14, wherein the chemotherapy is a VEGF signaling pathway blocker.

16. The method of claim 9, wherein if the tumor is identified as the permCAF subtype, the differential treatment comprises a treatment targeting a cancer expressing the permCAF subtype.

17. The method of claim 16, wherein the treatment targeting the permCAF subtype comprises CCR2 immunotherapy in combination with chemotherapy.

18. The method of claim 17, wherein the chemotherapy is FOLFIRINOX.

19. The method of claim 16, wherein the treatment targeting the permCAF subtype comprises an extracellular matrix (ECM) modulating agent.

20. The method of claim 19, wherein the ECM modulating agent is a pegylated human hyaluronidase.

21. A method for treating a subject diagnosed with cancer, the method comprising: (a) determining if a tumor in a biological sample from the subject with cancer is a permissive cancer associate fibroblast (permCAF) subtype or a restraining cancer associate fibroblast (restCAF) subtype by obtaining gene expression levels for each of the following genes in the biological sample ABCA8, ANK2 , BICD1, CHRDL1, CNIH3, COL11A1, ETV1, FBLN5, IGFL2, ITGA11, KIAA1217, NOX4, NPR3, OGN, PI16, SCARA5, TGFBR3, and VSNL1; (b) performing a pair-wise comparison of the gene expression levels for each permCAF and restCAF pair as follows: 151Patent Atty. Dkt. No.150-35-PCT permCAF restCAF Coefficient IGFL2 CHRDL1 194(c) calculating a Top Scoring Pair (TSP) Score for the biological sample, wherein the calculating comprises: (i) assigning a value of 1 for each pair for which a permCAF gene of the pair has a higher expression level than a restCAF gene of the pair, and a value of 0 for each pair for which the permCAF gene of the pair has a lower expression level than the restCAF gene of each pair; (ii) multiplying each assigned value by the coefficient listed above corresponding to each pair to calculate nine individual pair scores; and (iii) summing the nine individual pair scores together along with a baseline effect (intercept = -8.4) to calculate the TSP Score for the biological sample; (d) converting the TSP Score to a subtype probability using the inverse-logit transformation subtype probability = expTSP Score / (1 + expTSP Score), wherein if the subtype probability is greater than or equal to 0.5, the tumor subtype is determined to be a permCAF subtype and if the subtype probability if less than 0.5, the tumor subtype is determined to be a restCAF subtype; and 152Patent Atty. Dkt. No.150-35-PCT (e) treating the subject based on the subtype assignment.

22. The method of claim 21, wherein the cancer is a pancreatic ductal adenocarcinoma (PDAC), a mesothelioma, a urothelial carcinoma, or a renal cell carcinoma.

23. The method of claim 21, wherein the biological sample comprises a fresh sample, a frozen sample, or a formalin fixed paraffin-embedded (FFPE) sample.

24. The method of claim 21, wherein the gene expression levels are obtained by microarray analysis, RNAseq, quantitative RT-PCR, next-gen sequencing, multiplexed direct digital counting, or a combination thereof.

25. The method of claim 21, wherein if the tumor is identified as the restCAF subtype, the differential treatment comprises a treatment targeting a cancer expressing the restCAF subtype.

26. The method of claim 25, wherein the treatment targeting the restCAF subtype comprises an anti-PD-L1 immunotherapy in combination with chemotherapy.

27. The method of claim 26, wherein the chemotherapy is a VEGF signaling pathway blocker.

28. The method of claim 21, wherein if the tumor is identified as the permCAF subtype, the differential treatment comprises a treatment targeting a cancer expressing the permCAF subtype.

29. The method of claim 28, wherein the treatment targeting the permCAF subtype comprises CCR2 immunotherapy in combination with chemotherapy.

30. The method of claim 27, wherein the chemotherapy is FOLFIRINOX.

31. The method of claim 28, wherein the treatment targeting the permCAF subtype comprises an extracellular matrix (ECM) modulating agent.

32. The method of claim 31, wherein the ECM modulating agent is a pegylated human hyaluronidase. 153

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