Biomarkers that guide clinical decisions in triple negative breast cancer therapies

Abstract

The invention relates to methods of assessing the treatment outcome of a subject suffering from triple negative breast cancer (TNBC) by receiving measured biomarkers from the subject and correlating differentially expressed levels of the biomarkers to a treatment outcome for TNBC. The invention also relates to systems for assessing the treatment outcome of a subject suffering from triple negative breast cancer.

Description

PCT Application Attorney Docket No. AF44111.P046WOBLG Ref. No. 22-002TITLEBIOMARKERS THAT GUIDE CLINICAL DECISIONS IN TRIPLE NEGATIVE BREAST CANCER THERAPIESCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This patent application claims priority from, and incorporates by reference the entire disclosure of, U.S. Provisional Patent Application No. 63 / 726,182, filed on November 27, 2024, and U.S. Provisional Patent Application No. 63 / 745,748, filed on January 15. 2025.BACKGROUND

[0002] A need exists for the identification of predictive biomarkers to assess treatment outcome in triple negative breast cancer patients. Numerous embodiments of the present disclosure aim to address the aforementioned need.SUMMARY OF THE INVENTION

[0003] In some embodiments, the present disclosure pertains to methods of assessing the treatment outcome of a subject suffering from triple negative breast cancer (TNBC). In some embodiments, the methods of the present disclosure include: (1) receiving measured biomarkers from the subject; and (2) correlating differentially expressed levels of the biomarkers to a treatment outcome for TNBC. In some embodiments, the methods of the present disclosure also include a step of implementing a treatment decision based on the assessment. In some embodiments, the methods of the present disclosure are repeated after implementing the treatment decision.

[0004] Additional embodiments of the present disclosure pertain to systems for assessing the treatment outcome of a subject suffering from triple negative breast cancer. In some embodiments, the system includes one or more computer-readable storage mediums having a program code embodied therewith. In some embodiments, the program code includes programming instructions for: (1) receiving measured biomarkers from the subject; and (2) correlating differentially expressed levels of the biomarkers to a treatment outcome. In some embodiments, the program code also includes programming instructions for (3) recommending a treatment decision based on the assessment.DESCRIPTION OF THE DRAWINGSPCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0005] FIG. 1A illustrates a method of assessing the treatment outcome of a subject suffering from triple negative breast cancer in accordance with various embodiments of the present disclosure.

[0006] FIG. IB illustrates a system for assessing the treatment outcome of a subject suffering from triple negative breast cancer in accordance with various embodiments of the present disclosure.

[0007] FIGS. 2A1-2B demonstrate that the combination of carboplatin and docetaxel is largely ineffective at generating enhanced responses over the best single agent in triple negative breast cancer (TNBC) patient-derived xenografts (PDXs). FIGS. 2A1-2A2 (top panel) shows quantitative tumor responses to chemotherapy in 50 TNBC PDX models comprising the “chemotherapy response cohort”. A general linear model for each PDX was generated to estimate mean log2 fold change (FC) in tumor volume at Day 28 vs Day 0 (baseline) and its associated 95% confidence interval (CI) for each treatment within a PDX (n > 3 per treatment arm). Response was also qualitatively assessed based on modified RECIST 1.1 classification (PD, Progressive Disease: SD, Stable Disease; PR. Partial Response; CR, Complete Response). FIGS. 2A1-2A2 (middle panel) shows annotation of PDXs harboring pathogenic variants of TP53, BRCA1, BRCA2, or PALB2. FIG. 2A1-2A2 (bottom panel) show annotations depicting sample stratification for analyses to address four key questions (QI to Q4) asked in this study. FIG. 2B shows that, for PDXs with response to all treatment arms, boxplots depict quantitative chemotherapy responses for each PDX to single agent carboplatin (blue) and docetaxel (green), the best response to either single agent carboplatin OR docetaxel (yellow), and to the combination (red). These results suggest that combination treatment does not enhance tumor shrinkage over the best single-agent in TNBC PDXs. Boxes depict the interquartile range (IQR) of the scores with horizontal lines depicting the median. Whiskers extend to 1.5 x IQR from QI (25th percentile) and Q3 (75thpercentile), respectively. P- values derived from paired Wilcoxon signed-rank tests.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0008] FIGS. 3A-3H show molecular associates of carboplatin, docetaxel, and combination treatment. FIG. 3A shows Venn diagrams depicting overlap of treatment-associated genes (p < 0.01) by data type. FIG. 3B shows a Venn diagram depicting overlap of treatment-associated genes (p < 0.01) by any data type. FIG. 3C shows Venn diagrams depicting overlap of significant (p < 0.01) molecular associations by treatment type. FIGS. 3D-3F show plots summarizing treatment associated consensus gene sets derived from this study along with external datasets for (FIG. 3D) platinum, (FIG. 3E) taxane, or (FIG. 3F) combination. Genes that are significant in this study’s PDX dataset and also in at least two additional datasets are shown. Genes are also annotated according to a drug target tier system Applicant developed to inform actionable insights and also annotated as a dark, understudied gene. FIG. 3G is a Venn diagram depicting overlap of genes from consensus gene sets. FIG. 3H is a heatmap showing normalized enrichment scores (NES) from GSEA analysis with Hallmark gene sets using RNA-Seq and proteomics data. Asterisks indicate enrichment FDR < 0.05. Outlined cells indicate significant pathways (FDR < 0.05) also found in external datasets.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0009] FIGS. 4A-4K demonstrate the prediction of chemotherapy responses. FIGS. 4A, 4D, and 4G show area under the receiver operating curve (AUROC) performance in the set-aside cross-validation data repeated 25X of trained logistic regression models using ProMS feature selection (5-10 features) for predicting complete response (CR) / pathologic complete response (pCR) or complete response plus partial response (CR / PR) as indicated from combined RNA datasets for single agent platinum (FIG. 4A), single-agent taxane (FIG. 4D), and platinum + taxane combination (FIG. 4G). Numbers indicate average AUROC. The number of selected markers giving the highest average AUROC for the CR / pCR (solid) or CR / PR (dashed) predictors were used to generate final, fully trained models. FIGS. 4B, 4E, and 4H show ProMS features selected features giving the highest average cross-validation AUROC from FIGS. 4A, 4D and 4G. A multi-omics, protein-facilitated RNA marker selection method (ProMSmo) was also examined in FIG. 4H with 10 features which was based on the number of markers with the highest cross-validation AUROC in FIG. 4G. FIGS. 4C, 4F, and 41 show performance of fully trained logistic regression (LR) models using markers selected by ProMS / ProMSmo in FIGS. 4B, 4E, and 4H, respectively to predict chemo response in independent test data. *For FIG. 4C, dataset 03 was not used for training the CR / PR platinum predictor. FIGS. 4K-4L show performance of composite platinum and taxane predictors trained on all existing data assessed using independent test datasets from PDX models to predict response to single agent platinum (FIG. 4J) or taxane (FIG. 4K).

[0010] FIGS. 5A1-5B show molecular features at baseline discriminate best response to single agent carboplatin or docetaxel. FIGS. 5A1-5A2 shows GSEA analysis with Gene Ontology: Biological Processes (GO: BP), Reactome, and Wikipathway geneset collections using signed (indicating positive or negative sign of correlation coefficient) -log 10 p-values from RNA-Seq and proteomics data. Normalized enrichment scores of significant genesets (FDR < 0.05) are shown after applying weighted set cover to reduce geneset redundancy. Genesets were further categorized into categories by manual curation guided by leading edge genes in each geneset. FIG. 5B shows heatmaps depicting AUROC of genes found to be significantly higher by RNA-Seq data in PDXs whose response was better to either single-agent carboplatin or docetaxel that were tested to discriminate CR / pCR from others by AUROC analysis in clinical neoadjuvant TNBC datasets.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0011] FIGS. 6A-6E show that actin dynamics, trafficking, and OXPHOS metabolism may underlie positive and negative interactions between single agents. FIG. 6A shows workflow describing multigroup comparison using Kruskal-Wallis test followed by Dunn’s post-hoc test to identify differences between groups performed separately with RNA-Seq and proteomics data. Meta-p-values were generated by Stouffer’s method (sumz) using post-hoc test-derived pvalues from RNA-Seq and proteomics to find multi-omic support for genes associated with PDXs where combination was beneficial vs single agents or associated with PDXs where combination was worse vs best single agent. FIGS. 6B-6C show boxplots showing all significant genes from FIG. 6A. Genes associated with combination benefit vs. single agents included genes with roles in regulating actin dynamics and trafficking (FIG. 6B) while genes with roles in homeostasis and metabolism associated with PDXs where combination was worse vs. best single agent. Boxes depict the interquartile range (IQR) of the scores with horizontal lines depicting the median. Whiskers extend to 1.5 x IQR from QI (25th percentile) and Q3 (75th percentile), respectively. Meta-P-values derived as described in (FIG. 6A). FIGS. 6D-6E show data from a complementary sample stratification and statistical approach. GSEA enrichment results (FDR < 0.05) are shown from GO: BP, Reactome, and Wikipathway gene collections using signed (indicating directionality of fold change) -log 10 meta-p-values derived from RNA-Seq and proteomics data together. Association with cytoskeleton and homeostasis pathways support gene level results found in FIGS. 6A-6C.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0012] FIGS. 7A1-7F show that KRT5 is a chemotherapy response marker for carboplatin, docetaxel, and their combination. FIGS. 7A1-7A2 shows GSEA analysis with Gene Ontology: Biological Process (GO: BP), Reactome, and Wikipathway geneset collections using signed (indicating positive or negative sign of correlation coefficient) -log 10 p- values from RNASeq and proteomics data. Normalized enrichment scores of significant genesets (FDR < 0.05) are shown after applying weighted set cover to reduce geneset redundancy. Genesets were further categorized into categories by manual curation guided by leading edge genes in each geneset. FIG. 7B shows boxplots depicting selected genes that were supported by both RNA-Seq and proteomics data with roles in metabolism that are higher in PDXs resistant to all treatment arms (carboplatin, docetaxel, and the combination) compared to PDXs responsive to any treatment. FIG. 7C is similar to FIG. 7B except it shows basal marker genes that are higher in PDXs responsive to any treatment vs PDXs resistant to all treatments. For FIGS. 7A1-7B, boxes depict the interquartile range (IQR) of the scores with horizontal lines depicting the median. Whiskers extend to 1.5 x IQR from QI (25thpercentile) and Q3 (75th percentile), respectively. P- values derived from Wilcoxon rank-sum tests. FIG. 7D shows representative images of KRT5 IHC in baseline PDX tumors prior to treatment. Scale bar = 10 pm. FIG. 7E shows a plot showing Allred IHC scores for KRT5 quantified from IHC images. FIG. 7F shows AUROC using KRT5 Allred scores in predicting response to any chemotherapy treatment arm for TNBC PDXs in this study.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0013] FIGS. 8A-8L show that targeted agents can enhance chemotherapy responses. FIG. 8A shows quantitative responses (log2 fold change in tumor volume at day 28 vs day 0) for PDXs enrolled in the SPORE / U54 PDXNet preclinical trial where PDXs were treated with 7 targeted agents alone and in combination with carboplatin. Green boxes indicate PDX-drug pairs where response to the targeted agent + carboplatin combination was statistically better than carboplatin alone while red boxes indicate PDX-drug pairs where response to the targeted agent + carboplatin combination was statistically worse than carboplatin alone. FIG. 8B shows that, for each of the three responsive PDXs to single agent treatment, the top 20% of CPTAC breast tumors most similar to each PDX were considered querylike tumors, and their proteomic profiles were compared to those from the remaining tumors using a / -test to identify quantifiable, significantly up-regulated, druggable proteins as putative targets. These targets were then ranked from highest (most significantly upregulated) to lowest and the targets from agents in FIG. 8A were plotted. FIG. 8C shows plots showing tumor volumes of untreated controls and indicated targeted single agent treatment arms. Data shown are averages from 3-6 mice per treatment arm + SEM. FIG. 8D shows a plot showing tumor volumes of BCM-0046 for control and indicated treatment arms. Data shown are averages from 3-6 mice per treatment group + SEM. FIG. 8E is a heatmap depicting protein abundance of romidepsin’s designated targets HDAC1, HDAC2, and HDAC3 in PDX tumors. Numerals in heatmap indicate protein rank (lower value means higher abundance) for the indicated protein across all quantified PDXs. FIGS. 8F-8L are plots depicting quantitative response from FIG. 8A to carboplatin alone, the indicated targeted agent alone, and in combination with carboplatin. Green and red PDX annotations indicate response to the targeted agent + carboplatin combination was statistically better or worse than carboplatin alone, respectively

[0014] FIGS. 9A-9D illustrate predicting objective response, complete response and pathologic complete response. FIG. 9A is a Venn diagram showing overlapping features of regression genes, WGCNA / CTD, ProMS, and CR / PR-associated genes for predicting objective response (CR / PR response). FIG. 9B is an AUROC performance on independent test data of logistic regression models trained to predict CR / PR using features selected by different feature selection methods as indicated or using pooled features. FIG. 9C is the same as FIG. 9A but used for predicting complete / pathologic complete response. FIG. 9D is the same as in FIG. 9B except showing AUROC performance on independent test data of models trained to predict complete / pathologic complete response.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0015] FIGS. 10A-10C show optimizing chemotherapy complete / pathologic complete response predictors. FIG. 10A is a Venn diagram showing overlap of features selected by ProMS, WGCNA / CTD, and consensus genes for CR / pCR predictors using all possible datasets. FIG. 10B is a mean Monte-Carlo cross validation AUROC performance on held-out dataset of composite logistic regression models trained to predict complete / pathologic complete response (n=50 times) using features selected by different feature selection methods as indicated or using pooled features. FIG. 10C (top panel) shows AUROC curves showing performance of composite models trained on pooled features when applied to datasets used for training. The bottom panel of FIG. 10C shows AUROC curves showing performance on individual datasets not used for training that includes PDX models and external patient cohorts.

[0016] FIGS. 11A-11I show single- and Multi-omic predictors of chemotherapy response.DETAILED DESCRIPTION

[0017] It is to be understood that both the foregoing general description and the following detailed description are illustrative and explanatory, and are not restrictive of the subject matter, as claimed. In this application, the use of the singular includes the plural, the word “a” or “an” means “at least one”, and the use of “or” means “and / or”, unless specifically stated otherwise. Furthermore, the use of the term “including”, as well as other forms, such as “includes” and “included”, is not limiting. Also, terms such as “element” or “component” encompass both elements or components comprising one unit and elements or components that include more than one unit unless specifically stated otherwise.

[0018] The section headings used herein are for organizational purposes and are not to be construed as limiting the subject matter described. All documents, or portions of documents, cited in this application, including, but not limited to. patents, patent applications, articles, books, and treatises, are hereby expressly incorporated herein by reference in their entirety for any purpose. In the event that one or more of the incorporated literature and similar materials defines a term in a manner that contradicts the definition of that term in this application, this application controls.

[0019] Breast cancer is a leading cause of cancer-related deaths worldwide. For instance, triplenegative breast cancer (TNBC) is characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and low / no expression of HER2. Consequently, there is a lack of effective molecularly targeted therapeutics and chemotherapy remains the mainstay of systemic therapy.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0020] In the neoadjuvant setting, taxanes (paclitaxel, docetaxel), anthracyclines (doxorubicin, epirubicin), cyclophosphamide, and platinums (cisplatin, carboplatin) are used, often in series and / or in combination. Identifying patients who will respond to chemotherapy, and finding optimal chemotherapy regimens to treat TNBC, is an area of intense investigation. Recently, approved immune checkpoint blockade inhibitors are now available for TNBC patients. Additionally, PARP inhibition has also been approved as adjuvant therapy for the -15% of TNBC patients harboring deleterious BRCA1 / 2 mutations.

[0021] The addition of taxane to adriamycin / cyclophosphamide (AC)-based regimens improved outcomes, and was the standard-of-care to treat breast tumors for many years. The discovery that a subset of TNBC may be sensitive to DNA damaging agents prompted the investigation of platinum derivatives for TNBC. Most recently, taxane / platinum combinations with or without AC have proven promising as they improve pathologic responses above historic single-agent rates.

[0022] Although the exact treatment regimen was different among clinical trials such as GeparSixto, BrighTNess, and CALGB, TNBC patients enrolled in treatment arms receiving combination platinum and taxane achieved pCR rates of over 50%, which was significantly higher than the pCR rate of patients in arms receiving either drug as a single agent. Because platinum-based agents can increase the frequency of adverse events, more current studies such as NeoCART9, and two TNBC clinical trials (NCT02547987 and NCT02124902), analyzed by the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC), have investigated less intensive neoadjuvant regimens for TNBC patients consisting of platinum + taxane and excluding anthracyclines. However, in -50% of cases, pCR is not achieved, and these individuals experience dramatically shorter relapse- free and overall survival.

[0023] Furthermore, it is unclear whether the two drugs interact to enhance responses beyond an additive effect. Results from the KEYNOTE-52212 TNBC trial led to approval of adding an immune checkpoint inhibitor, pembrolizumab, to an already intensive chemotherapy backbone of carboplatin + paclitaxel followed by AC. However, addition of pembrolizumab improved the pCR rate by only -7% compared to the control arm.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0024] As such, a need exists for the identification of predictive biomarkers to assess treatment outcome in triple negative breast cancer patients. In particular, a need exists for the identification of predictive biomarkers for assessing the efficacy of individual drugs to enhance treatment response rates and to optimize and individualize treatments. Numerous embodiments of the present disclosure aim to address the aforementioned need.

[0025] In some embodiments, the present disclosure pertains to methods of assessing the treatment outcome of a subject suffering from triple negative breast cancer (TNBC). In some embodiments illustrated in FIG. 1A, the methods of the present disclosure include: receiving measured biomarkers from the subject (step 10): and correlating differentially expressed levels of the biomarkers to a treatment outcome for TNBC (step 12). In some embodiments, the methods of the present disclosure also include a step of implementing a treatment decision based on the assessment (step 14). In some embodiments, the treatment decision includes monitoring the course of the triple negative breast cancer (step 16), removing a tumor from the subject (step 18), administering a therapeutic agent to the subject (step 20), modifying a pre-existing treatment regimen (step 22), or combinations thereof. In some embodiments, the methods of the present disclosure are repeated after implementing the treatment decision (step 24).

[0026] Additional embodiments of the present disclosure pertain to systems for assessing the treatment outcome of a subject suffering from triple negative breast cancer. In some embodiments, the system includes one or more computer-readable storage mediums having a program code embodied therewith. In some embodiments, the program code includes programming instructions for: (1 ) receiving measured biomarkers from the subject; and (2) correlating differentially expressed levels of the biomarkers to a treatment outcome. In some embodiments, the program code also includes programming instructions for (3) recommending a treatment decision based on the assessment.

[0027] As set forth in more detail herein, the methods and systems of the present disclosure can have numerous embodiments.

[0028] Treatment outcomes and biomarkersPCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0029] The methods and systems of the present disclosure may correlate differentially expressed levels of biomarkers to various treatment outcomes. For instance, in some embodiments, the treatment outcome is determined by tumor shrinkage. In some embodiments, the treatment outcome includes a likelihood of a success of a treatment plan. In some embodiments, the treatment plan includes, without limitation, treatment through chemotherapeutic agents, carboplatin, cisplatin, taxane chemotherapeutic agents, docetaxel, paclitaxel, or combinations thereof.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0030] The methods and systems of the present disclosure may correlate differentially expressed levels of various biomarkers to treatment outcomes. For instance, in some embodiments, the biomarkers include, without limitation, PRKX, TMEM135, MRPL32, VASH1, PTBP2, RAB1B, NCOA2, SLC25A35. COMMD7. CDC25A, CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, NCAPG, LGALS1, GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11, KIF2C, CDK19; LGALS3BP, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469, SUV39H1, TP53INP2, LCAT, THEM6, IRS2, ARL4D, STUB1, ITM2B, HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1, CCDC91, IPO5, SUMF1, KRT5, ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA. TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, TULP3, TSSC4, ARMC7, FANCI, TRPV4, NDUFA2, USP49, SSX2IP, C3orf38, KNK2, SLC39A4, MFSD3, TSTA3, AEBP1, MYH10, PRSS8, LAD1, PKP3, LRP6, RGMA, ZNF462, COL27A1, APEH, BTG2, DEGS1, EBPL, EIF2D. FAM174A, FUT3, GALE, GNPNAT1, HIBCH, LAP3, LRRC8E, METTL1, PGD, PSCA, RNASEH2C, SPRYD7, GLTP, ENDOD1, AQP1, ARHGAP33, ASAP2, ATAD2B, ATAD5, BICD1, CDH24, CHICI, CNOT4, CNTLN, DEK, DMC1, DMXL2, EFNB3, EZH2, FAM168A, FIZ1, FOXN3, GPR19. GXYLT1, HAUS5, HELLS, HES6. IRF2BPL, ITPKB. KLHL25, MSANTD2, N4BP2L1, PDE4DIP, PLEKHG2, POLH, PPM1D, PRKAB2, SLC4A7, SMC6, SOWAHC, STARD13, TM2D3, TRAM1L1, USP1, UTRN, WHAMM. ZNF160, ZNF184, ZNF212, ZNF367, ZNF566, ZNF573, ZNF620, ZNF654, ZSCAN5A, BYSL, USP37, EXO5, HIC2, ZNF197, BCAR1, METRN, ZDHHC7, SLC22A18, PLXND1, SGCE, ATP7B, PHLDA3, CMBL, ALDH1A1, ASF1A, ECHDC1, ZNF100. ZNF493, ZNF85, KCNF1, KCTD17, PCOLCE2, DNAJC24. SAV1, TMEM 126B, POGZ, SRSF7, TMPO, POLE, FAM83H, RPL8, ATP8B2, C 1 orf 1 16, AKAP7, SIMC1 , FGD1, DHRS7, HIBADH, LRTOMT, NTN4, PFKFB2, SNX13, TAX1BP1, ZBTB3, CCDC61, TSPAN31, TMEM150A. ADCY1, ARRB2. ASH1L, CLK2, CPSF6, DNA2, DNAJC9, GPR63, HACE1, HYI, KCTD15, LYSMD1, MRPL9, PRPF3, RPRD2, TOE1, UCK1, ZNF189, ZNF510, ZNF740, ZWINT, GOPC, TRIP13, RHOBTB1, SPAG5, SRRD, NCOA7. STIL, COPS3, HSPA13, DONSON. CCDC117, CHAF1A, SUZ12, WNK3, TK2. PPP2R3A, ZNF17, SMAD4. MCOLN2, MSI1, FCHSD2, C2CD3, MAD2L1, TPBG, SRRT, MEX3C, PTK6, ZNF22, MDM1, SAR1B, VPS28, FOXM1, CAP2, FAM126A, MRPL2, MRPS10, MTHFSD, OAZ2, RAB3IL1, SLC25A17, SLC29A1, SNAP29, SPRTN, TM9SF4, TPMT, YWHAH, ZNF75A, ZYX, SPATA7, TLE2, KLHL7, ZNF133, NR1H2, ISCA1, NDUFA3, EFNA5, ERLEC1, GPR157, RELL1, BLMH, HIVEP1,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002ARID1B. TCHP, BRAP, RFC5, EWSR1, ZMAT5. TCEA1. KLK5, RAB6B, FAXC, RPS12, STX7, BCL2L10, GOLGA8A, FGF11, IL18R1, ANKRD6, ZNF483, EPHX4, FBN3, OVOL2, PCDH1, ANGPTL4, QSOX1, INPP5A, ADCY9, Cllorf24, RIN2, RAB2A, BCKDK, ABCC2, NAA60, HDLBP, SPARC, MGRN1, TRIOBP, TGM2, SERINC5, PMM2, POR, GMPPA. GNAI1, RAB11FIP5, FLYWCH1, FARP2, SYNC, TMEM214, STRN3, SFXN3, CERCAM, SEMA4B, USP40, TRPC4AP, ABLIM3, COMT, ZHX3, UBN1, ENG, HHLA3, YBX2, FITM2, PLCB3, ANKS3, WNT9A, MPP2, PGBD1, CCDC17, CC2D2A, EPM2A, ICA1L, KANSL1L, LRP2BP, LYPD1, MAP2, MYOID, NHSL1, PGAP1, PLEKHM3, PYGB, RSPH3, ZBTB44, ZNF431, ZNF708, PDSS2, AKIRIN2, SYNCRIP, FAM221A. MDK, CD83, RNGTT, JPH2, KIAA0556, MSRB3, SAMD9L, DHX38, ZNF81, PTTG1, SP110, IFIT1, DDX60, XAF1, IFI44, OAS2, GBP4, STATE ACTG2, KRT6B, AZGP1, ZG16B, STAC2, KLK7, KRT15, CDKN2A, IFI27, COL5A2, PXDN, ACTA2. TF, NTRK2, AGT. S100A1, CRYAB, EDN2, PCP4L1, ANGPT1, PTX3, INHBB, TIMP3, SIX1, RERG, FKBP10, SMOC2, COL6A2, SNAI2, COL8A1, PXDNL, CASP14, SOD3, PIK3C2G, PCOLCE, NMU, PI15, TACSTD2, BGN, SYNM, SLITRK6, MMP2, PRELP, ADM, TBX1, IGFBP5, BATF2, AKR1C1. IFITM1, C15orf48. FBXO2, ASPHD1. RCN3, TAGLN, MXRA8, MX2, AKR1C3, PPP1R3C, FN1, XYLT1, IL32, TPM2, MYL9, NDUFA4L2, SKAP1, TMEM47, ADCY2, GPRC5C, KIAA1549L, SMARCA1, IFIT2, DHX58, SEMA3C, SCUBE2, COL17A1, MFGE8, RTN4RL1, SRPX, NR2F1, ATP13A5, NDRG1, GXYLT2, TNC, KCNK5, GAS6, ARSJ, MAOA, SLC24A3, FHOD3, FST, DDIT4L, OSR1, CCND1, SERPINE2, SUSD2, GPT, MALL, SCUBE3, OAS1, CA12, COL7A1, EGLN3, SLC6A17, LAMB1, SCN4B. ESRRG, RBI, FAM83A, DDR2, ANKRD22, COPZ2, DAPP1, A4GALT, OPRK1, KLHL13, CNTN1, MYLK, BMPR1B, RGS 11 , CITED4, LAG3, SCNN1B, NDP, TSPYL5, PID1, ALDH3B2, ADORA1, GLB1L2. SORBS2. B4GALNT2, LCK, MEGF10, IGFBP3, STC1, TMEM200B, LOXL2, APLN, DKK3, PKDCC, TLR3, FGFR1, CAV1, FAT4, VIM, ZNF365, CADM1, ATP13A4, RAB3B, NFIA, TACR1, NRP1, FSTL4, LYPD3, AKR1E2, BOC, KCNMB4, FNDC4, LAMA4, ETV7, NGEF, SUSD3, EFR3B, MMP15, VSIG10L. MATN3, ENPP3, EFCAB6, SH3RF2. GHR, PMP22, LOX, SORCS2, RDH10, C1QTNF2, SCNN1G, RNF165, SDC2, SLC12A2, INHBA, SLC13A3, PLCB1, CX3CL1. HYDIN, GLT8D2, RNF43. FEZ1, RNF152, MPV17L, ANOL CDK6, CILP2, PDGFD, HOXC11, EPHB3, DDX58, PLTP, SERPINE1, SLC2A10, KHDRBS3, TRIM9. CORO1A, B3GALT5, EVA1A, PDE6B, GPR176, EFEMP2, NPR2, GLRB, CTF1, CD8A, PMAIP1, ALDOC,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002PDGFA, TGFB2, LIMS2, FBLN7, TPST1. EMP1, UBASH3B. ADAMTS15, ISG20, SHOX2, VWDE, PROCR, HSH2D, CLCN4, FAM189A2, MAP1B, NOX5, GPC1, TBX3, PRSS27, GYG2, FAM83F, F3, PGF, PRSS23, ITGA5, COL18A1, SHANK2, SHANK3, ATP1B1, RASGRP3, PTGES, FRY. NOTUM, EIDE SLC27A2, WBP2NL, JAG1, PRRT2, RNF180, SCD5. PLLP, BEAN1, FERMT2, TPPP3, FUT9, ASRGL1, NPTXR, HCST, MPZL2, C6orfl41, PLK2, EFHC2, COL16A1, ADORA2B, FBLN1, ZNF501, CACNA1D, AFAP1L1, ATP8A1, DOC2A, MMEL1, CD6, ARHGEF25, PCSK6, SPATA6, TLR1, L3MBTL1, ADHFE1, GPX8, CES4A, TRPC1, CNIH3, MCAM, PCDHB13, ROR1, MEIS3, SNTB1, AK7, AHRR, NDRG4, GPR39, IGFBP6, SERTAD4, SPTBN5. NQO1, IL20RB, INHA, ZNF471, PNCK, ADAM12, MAPK15. MAML3, SHROOM2, GROT, RHOBTB3, SEC14L5, SGSM1, DUSP5, TNFRSF11A, MEGF6, NKD1, C1QTNF6, USP18, DMGDH, EPS8, EML1, MRAS, PNPLA7, ANKRD34A, PDGFC, VEGFA, FZD4, LAMA3, PDK3, EPASE CDH26, THRB, BRSK1, RIBC2, HSPG2, EGFR. GGT7, MYOM1, PPP1R36, HAS3, PDGFB, WNT2B, PPFIA4, HOXC13, CHST3, STU, THBS1, FIGN, HLX, GAL3ST4, RFTN1, Clorfll5, HSPA12A, SLC29A4, RPS6KA2, PHLDB2, PNPLA4, CDHR3, ST3GAL4, ITGB5, CRIP2. ULBPE PTPRG, ZNF717, SCN1B. SH3RF3, ADAMTSE PKD1LE ATP2A1. ACOT4, SLC22A17, MAML2, CYBRD1, ZBTB20, CENPW, ARHGAP5, ARHGEF17, BCO2, C14orf28, CACNB1, CD59, CDIPT, CES2, CNNM2, CTNNAL1, CTSS, ENGASE, GLIS2. HM13, JMJD8, KLHL26, L3MBTL2, MORN4, NR4A1, PLOD3, RNF40, SIDT2, SLC25A42, SLC39A13, SOCS5, TBC1D20, TECPR2, TMEM184B, TTC23, WWP2, ARTN, CADM4, CARD14, CNBD2, DBNDD1, ENPP4, EPB41L5, EXD3, FHL2. KIFC3, KRT83, PLA2R1, PRR3, SIAE, SLC12A8, TBC1D7, TMEM217, TOM E TRNP1 , TXNRD2, VLDLR, ZDHHC1 , PGBD5, ANK2, SRPX2, MAP1A, COL1A1, SLC2A12, SLC6A11, ADAMTS12, CCDC80, COL14A1, COL1A2, COL3A1, COL5A1, COL6A3, EXOG, INPP4B, KLF6, LDLR, MAST4. MTMR11. OLFML2A. PDE4A. PHKGE RARB, UTP23, MAT2B, SET, TPM3, ARMCX3, DECR1, DYSF, EXOC1, STAM2, KDELR2, AP1B1, VRK3, INTS8, PRRC1, PDE6D, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, ACBD5, AIG1, DTWDE ELP2, PAQR6. PIK3C3. RARS2. SF3B5, SHPRH, ZC3HAV1L, ORC1, EIF4A3, CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERI1, CDCA7, PRKAB1, NUP210, POP5, TNFAIP2, PARD6A, RHEBL1, FBL, MFHAS1, PRIME PINX1, C12orf43, PCBP2, CHAF1B, E2F7, MED12L, DDX23, WDR76, MCM2, HAUS1, IFI44L, DNAJC3, DSTYK, KPNA3, PEX2, SLC35B3, STX12, SUGT1, TMEM106B, TWISTNB, UBE2W, VPS36, ZNF12, ZNF623, NFKB2, NUP37, RELB,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002GOLGA5, DUSP18, EHBP1L1, TRIP11, FOXRED2, ZNF70, PES1. D2HGDH, RNF185, MORC2, MPV17, HSCB, ATP6V0E1, EHD1, PHF20, SERINC3, FLVCR2, HPS4, VPS37C, RBKS, PRKCD, JKAMP, ANKRD46, ATP6AP1L, BTBD3, C2orf76, CLHC1, COA5, CRCP, DBT, DCUN1D4, DHRS12, DPH5, DPY19L4, DYNC1LI2, EFNA3, INTS6. KIF3A. KRIT1. LAMTOR3, MFF, NEURL2, PCGF3, PEX6, PSTK, RAB11FIP2, RAD50, SAR1A, SENP8, SMARCAD1, TIGD6, TMEM67, WDPCP, ZKSCAN1, ZRANB1, GPHN, MACROD2, YLPM1, UNC119B, ZNF787, ZNF287, APOLD1, MEST, TNKS, RUVBL2, UBR7, COX 14, PPP3CC, RARRES1, CCAR1, IGF2BP2, AKAP5, LXN, ACP2, ALAS1, ANKRD33B, ANXA11, C1R, CC2D1B, CD274, CYTH1, DRAM1, EGLN2. ELF4, FBXO6, GRB2, IFIH1, IKBKG, IL18BP. JMJD6, KLHDC7B, LAMP3, MX1, MYD88, OAS3, OASL, PARP12, PIK3CD, RAB35, RBM42, REC8, RNF213, RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM14. PTGER4. PPM1A, RBFOX2, BRWD1, IRF1, FEN1, TOMM40, PARPBP, AURKB, AURKA, BTN3A3, PLSCR1, IRF9 , UBE2L6, GBP1, BST2, PARP14, SP100, B2M, SAMD9, IFI6, PSMB9, IFIT3, HERC5, ISG15, RSAD2, PSME1, PSMB10, IFI35, PARP9, HERC6, NMI, GLI4, ZNF696. ZNF517, ARHGEF37. GRHL2. SPINT2, ACO2, CLTCL1, CXCL14, GDF9, HECTD1, HMGXB4, MAPK1, MPP6, NAA30, NR3C2, PHF7, PIGH, PLA2G6, POLI, PPARGC1A, RHBDD3, RNF215, SLC23A2, SLC30A9, TTLL1, WIPF2, ZFP28. ARMC10, PTCD3, PUM2, RABGGTB, SRSF11, ZNF644, DZANK1, ACPI, E2F6, TXLNB, ATP6V0A4, LTF, ARPC1B, CYBA, DDX60L, or combinations thereof.

[0031] In some embodiments, the biomarkers include, without limitation, PRKX, TMEM135, MRPL32, VASH1, PTBP2, RAB1B, NCOA2, SLC25A35, COMMD7, CDC25A, CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, NCAPG, LGALS1, GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11, KIF2C, CDK19; LGALS3BP, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469, SUV39H1, TP53INP2, LCAT, THEM6, IRS2, ARL4D, STUB1, ITM2B, HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1, CCDC91, IPO5, SUMF1, KRT5, or combinations thereof.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0032] In some embodiments, the measured biomarkers include PRKX, TMEM135, MRPL32, VASH1, PTBP2, RAB1B, NCOA2, SLC25A35, COMMD7, and CDC25A. In some embodiments, the measured biomarkers include LCAT, THEM6, IRS2, ARL4D, STUB1, and ITM2B. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered as a single agent. In some embodiments, the platinum chemotherapeutic agents include, without limitation, carboplatin, cisplatin, or combinations thereof.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0033] In some embodiments, the measured biomarkers include one or more of the following measured biomarkers: (1) ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, or combinations thereof; (2) TULP3, TSSC4, ARMC7, FANCI, TRPV4, NDUFA2, USP49, SSX2IP, C3orf38. KNK2, or combinations thereof; (3) SLC39A4, MFSD3, TSTA3, AEBP1, TGFB1I1, RAB9B, MYH10, PRSS8, LAD1, PKP3, LRP6, RGMA, ZNF462, COL27A1, or combinations thereof; (4) APEH, BTG2, DEGS1, EBPL, EIF2D, ESRRA, FAM174A, FUT3, GALE, GNPNAT1, HIBCH, ITM2B, LAP3, LRRC8E, METTL1, PGD, PSCA, RNASEH2C, SLC39A4, SPRYD7, TSTA3, GLTP, ENDOD1, AEBP1, AQP1, ARHGAP33. ASAP2, ATAD2B, ATAD5, BICD1. CDH24, CHICI, CNOT4, CNTLN, DEK, DMC1, DMXL2, EFNB3, EZH2, FAM168A, FIZ1, FOXN3, GPR19, GXYLT1, HAUS5, HELLS, HES6, IRF2BPL, ITPKB, KLHL25, MSANTD2, N4BP2L1, PDE4DIP, PLEKHG2, POLH, POTI, PPM1D, PRKAB2, SLC4A7. SMC6, SOWAHC, STARD13. TM2D3, TMEM98, TRAM1L1, USP1, UTRN, WHAMM, ZFP37, ZNF160, ZNF184, ZNF212, ZNF367, ZNF566, ZNF573, ZNF620, ZNF654, ZSCAN5A, BYSL, USP37, EXO5, HIC2, ZNF197, or combinations thereof; (5) ACSS2, ESRRA. CCL5, POTI, ZFP37, ZNF256, ZNF394. SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, TULP3, TSSC4, ARMC7, FANCI, TRPV4, NDUFA2, USP49, SSX2IP, C3orf38, KNK2, SLC39A4, MFSD3, TSTA3, AEBP1, MYH10, PRSS8, LAD1, PKP3, LRP6, RGMA, ZNF462, COL27A1, APEH, BTG2, DEGS1, EBPL, EIF2D, FAM174A, FUT3, GALE, GNPNAT1, HIBCH, ITM2B, LAP3, LRRC8E, METTL1, PGD, PSCA. RNASEH2C. SPRYD7. GLTP, ENDOD1, AQP1. ARHGAP33, ASAP2. ATAD2B, ATAD5, BICD1 , CDH24, CHIC I , CNOT4, CNTLN, DEK, DMC 1 , DMXL2, EFNB3, EZH2, FAM168A, FIZ1, FOXN3, GPR19, GXYLT1, HAUS5, HELLS, HES6, IRF2BPL, ITPKB, KLHL25, MSANTD2, N4BP2L1, PDE4DIP. PLEKHG2, POLH, PPM ID. PRKAB2, SLC4A7, SMC6, SOWAHC, STARD13, TM2D3, TRAM1L1, USP1, UTRN, WHAMM, ZNF160, ZNF184, ZNF212, ZNF367, ZNF566, ZNF573, ZNF620, ZNF654, ZSCAN5A. BYSL, USP37, EXO5. HIC2, ZNF197, or combinations thereof; or (6) combinations thereof. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeuticPCT Application Attorney Docket No. AF44111.P046WOBLG 22-002 agents administered as a single agent. In some embodiments, the platinum chemotherapeutic agents include, without limitation, carboplatin, cisplatin, or combinations thereof.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0034] In some embodiments, the measured biomarkers include one or more of the following measured biomarkers: (1) ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, or combinations thereof; (2) POGZ. COMMD7, SRSF7, TMPO. POLE, or combinations thereof; (3) MFSD3, FAM83H, RPL8, ATP8B2, AEBP1, Clorfl l6, AKAP7, SIMC1, MYH10, FGD1, or combinations thereof; (4) DHRS7, HIBADH, LRTOMT, NTN4, PFKFB2, SNX13, TAX1BP1, ZBTB3, CCDC61, TSPAN31, TMEM150A, ADCY1, ARRB2, ASH1L, CLK2, CPSF6, DNA2, DNAJC9, EZH2, GPR63, HACE1, HYI, KCTD15, LYSMD1, MRPL9, PRPF3, RPRD2, SIMC1, TOE1, UCK1, ZNF189, ZNF510, ZNF740, ZWINT, GOPC, TRIP13, RHOBTB1, SPAG5, TULP3, SRRD, NCOA7, STIL, COPS3, HSPA13, DONSON, CCDC117, CHAF1A, HIC2, ATAD5, SUZ12, WNK3, or combinations thereof; (5) ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A. BRIP1, MSH6, RND2. RAB9B, TGFB1I1, POGZ, COMMD7, SRSF7, TMPO, POLE, MFSD3, FAM83H, RPL8, ATP8B2, AEBP1, Clorfl l6, AKAP7, SIMC1, MYH10, FGD1, DHRS7, HIBADH, LRTOMT, NTN4, PFKFB2, SNX13, TAX1BP1, ZBTB3, CCDC61, TSPAN31. TMEM150A, ADCY1, ARRB2, ASH1L, CLK2, CPSF6, DNA2, DNAJC9, EZH2, GPR63, HACE1, HYI, KCTD15, LYSMD1, MRPL9, PRPF3, RPRD2, TOE1, UCK1, ZNF189, ZNF510, ZNF740, ZWINT, GOPC, TRIP13, RHOBTB1, SPAG5, TULP3, SRRD, NCOA7, STIL, COPS3, HSPA13, DONSON, CCDC117, CHAF1A, HIC2, ATAD5, SUZ12, WNK3, or combinations thereof; (6) TK2, ACSS2, ESRRA, CCL5, PPP2R3A, POTI, ZFP37, ZNF256, ZNF394, SPICEL ZNF17. CUL4A, PIK3CA, SMAD4, TMEM98, TOP3A, BRIP1, MCOLN2, MSH6, RND2, RAB9B, CNTLN, TGFB1 I1 , MSI1 , FCHSD2, C2CD3, or combinations thereof; (7) MAD2L1, TPBG, SRRT, MEX3C, PTK6, ZNF22, MDM1, SAR1B, or combinations thereof; (8) VPS28. FOXM1, or combinations thereof; (9) CAP2, DHRS7, FAM126A, HIBADH, LRTOMT, MRPL2, MRPS10, MTHFSD, NTN4, OAZ2, PFKFB2, RAB3IL1, SLC25A17, SLC29A1, SNAP29, SNX13, SPRTN, TAX1BP1, TM9SF4, TPMT, YWHAH, ZBTB3, ZNF75A, ZYX, SPATA7, TLE2, CCDC61, KLHL7, ZNF133. NR1H2, ISCA1. TSPAN31, TK2. TMEM150A. NDUFA3, EFNA5, ZNF17, ERLEC1, GPR157, MFSD3, RELL1, BLMH, SPAG5, LYSMD1, HIVEP1, SIMC1, ZNF510, PRPF3, MCOLN2, ARID1B, RPRD2, ATAD5. ARRB2, ADCY1. CNTLN, ZNF740, TCHP, MSH, EZH2, DNA2, HACE1, BRAP, RFC5, RHOBTB1, TULP3, GPR63, TOE1, DONSON, HIC2, EWSR1, ASH1L, TRIP13, CCDC117, ZNF189, ZWINT, or combinations thereof; (10) TK2,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002ACSS2, ESRRA, CCL5, PPP2R3A, POTI, ZFP37, ZNF256, ZNF394, SPICE1, ZNF17. CUL4A, PIK3CA, SMAD4, TMEM98, TOP3A, BRIP1, MCOLN2, MSH6, RND2, RAB9B, CNTLN, TGFB1I1, MSI1, FCHSD2, C2CD3, MAD2L1, TPBG, SRRT, MEX3C, PTK6, ZNF22, MDM1, SAR1B, VPS28, FOXM1, CAP2. DHRS7, FAM126A, HIBADH, LRTOMT. MRPL2, MRPS10, MTHFSD, NTN4, OAZ2, PFKFB2, RAB3IL1, SLC25A17, SLC29A1, SNAP29, SNX13, SPRTN, TAX1BP1, TM9SF4, TPMT, YWHAH, ZBTB3, ZNF75A, ZYX, SPATA7, TLE2, CCDC61, KLHL7, ZNF133, NR1H2, ISCA1, TSPAN31, TMEM150A, NDUFA3, EFNA5, ERLEC1, GPR157, MFSD3, RELL1, BLMH, SPAG5, LYSMD1, HIVEP1, SIMC1, ZNF510, PRPF3, ARID1B, RPRD2, ATAD5, ARRB2, ADCY1, ZNF740, TCHP, EZH2, DNA2, HACE1, BRAP, RFC5, RHOBTB1, TULP3, GPR63, TOE1, DONSON, HIC2, EWSR1, ASH1L, TRIP13, CCDC117, ZNF189, ZWINT, or combinations thereof; or (11) combinations thereof. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered as a single agent. In some embodiments, the platinum chemotherapeutic agents include, without limitation, carboplatin, cisplatin, or combinations thereof.

[0035] In some embodiments, the measured biomarkers include CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, and NCAPG. In some embodiments, the measured biomarkers include HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1, CCDC91, IPO5, and SUMF1. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by taxane chemotherapeutic agents administered. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by taxane chemotherapeutic agents administered as a single agent. In some embodiments, the taxane chemotherapeutic agents include, without limitation, docetaxel, paclitaxel, or combinations thereof. In some embodiments, the taxane chemotherapeutic agent includes docetaxel.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0036] In some embodiments, the measured biomarkers include one or more of the following measured biomarkers: (1) BCAR1, METRN, ZDHHC7, SLC22A18, PLXND1, SGCE, ATP7B, PHLDA3, CMBL, ALDH1A1, ASF1A, ECHDC1, or combinations thereof; (2) HINT3, PTDSS2, XPO6, ZNF322. ZNF669, TPCN1, CCDC91, IPO5, SUMF1. or combinations thereof; (3) ZNF100, ZNF493, ZNF85, or combinations thereof; (4) KCNF1, KCTD17, PCOLCE2, PLXND1, DNAJC24, ECHDC1, SAVE TMEM126B, or combinations thereof; (5) BCAR1, METRN, ZDHHC7, SLC22A18, PLXND1, SGCE, ATP7B, PHLDA3, CMBL, ALDH1A1, ASF1A, ECHDC1, HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1, CCDC91, IPO5, SUMF1, ZNF100, ZNF493, ZNF85, KCNF1, KCTD17, PCOLCE2, DNAJC24, SAV1, TMEM126B, or combinations thereof; or (6) combinations thereof. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by taxane chemotherapeutic agents administered as a single agent. In some embodiments, the taxane chemotherapeutic agents include, without limitation, docetaxel, paclitaxel, or combinations thereof. In some embodiments, the taxane chemotherapeutic agent includes docetaxel.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0037] In some embodiments, the measured biomarkers include one or more of the following measured biomarkers: (1) ZMAT5, TCEA1, KLK5, RAB6B, FAXC, RPS12, STX7, BCL2L10, GOLGA8A, FGF11, IL18R1, ANKRD6, ZNF483, EPHX4, FBN3, or combinations thereof; (2) CCNE2, MTMR3, TMEM219. HMGN4, MLYCD, NCAPG. or combinations thereof; (3) OVOL2, PCDH1, or combinations thereof; (4) ANGPTL4, QSOX1, STX7, or combinations thereof; (5) ZMAT5, TCEA1, KLK5, RAB6B, FAXC, RPS12, STX7. BCL2L10, GOLGA8A, FGF11, IL18R1, ANKRD6, ZNF483, EPHX4, FBN3, CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, NCAPG, OVOL2, PCDH1, ANGPTL4, QSOX1, or combinations thereof; (6) INPP5A, ADCY9, BCAR1, METRN, Cllorf24, RIN2, RAB2A, BCKDK, ABCC2, NAA60, HDLBP. ZMAT5, SPARC, MGRN1, TRIOBP, TGM2, SERINC5, TCEA1, PMM2, POR, GMPPA, GNAI1, RAB11FIP5, FLYWCH1, FARP2, SPRYD7, SYNC, TMEM214, STRN3, SFXN3, CERCAM, SEMA4B, USP40, ATP7B, TRPC4AP, ABLIM3, COMT, ZHX3, UBN1, ENG. HHLA3, YBX2, FITM2, PLCB3, ANKS3, CMBL, WNT9A, MPP2, ANKRD6, BCL2L10, EPHX4, FAXC, FBN3, FGF11, GOLGA8A, KLK5, RAB6B, PGBD1. CCDC17, CC2D2A, EPM2A, ICA1L, KANSL1L, LRP2BP, LYPD1, MAP2, MYOID, NCOA7. NHSL1, PGAP1, PLEKHM3, PYGB. RSPH3, ZBTB44, ZNF431, ZNF708, RPS12, PDSS2, AKIRIN2, STX7, SYNCRIP, FAM221A, MDK, CD83, RNGTT, IL18R1, ZNF483, or combinations thereof; (7) JPH2, KIAA0556, NCAPG, MSRB3, SAMD9L, DHX38, ZNF81, PTTG1, or combinations thereof; (8) SP110, IFIT1, DDX60, XAF1, IFI44, OAS2, SAMD9L, GBP4, STAT1, ACTG2, KRT6B, AZGP1, ZG16B, STAC2, KLK7, KRT15, CDKN2A, IFI27. SPARC, COL5A2. PXDN, ACTA2, TF. NTRK2, AGT, S100A1, CRYAB, EDN2, PCP4L1, ANGPT1, PTX3, ANGPTL4, INHBB, TIMP3, SIX1, RERG, FKBP10, SMOC2, COL6A2, SNAI2, COL8A1, PXDNL, CASP14, SOD3, PIK3C2G, PCOLCE, NMU, PI15, TACSTD2, BGN, SYNM, SLITRK6, MMP2, PRELP. ADM. TBX1. IGFBP5, BATF2, AKR1C1. IFITM1, C15orf48, FBXO2, ASPHD1, RCN3, TAGLN, MXRA8, MX2, AKR1C3, PPP1R3C, FN1, XYLT1, IL32, TPM2, MYL9, NDUFA4L2, SKAP1. TMEM47, MSRB3. ADCY2, GPRC5C, KIAA1549L, SMARCA1, IFIT2, DHX58, SEMA3C, SCUBE2, COL17A1. MFGE8, RTN4RL1, SRPX. NR2F1, ATP13A5. NDRG1, GXYLT2, TNC, KCNK5, GAS6, ARSJ, MAOA, SLC24A3, FHOD3, FST, DDIT4L, OSR1, CCND1, SERPINE2, SUSD2, GPT, MALL, SCUBE3, OAS1, CA12, COL7A1, EGLN3, SLC6A17, METRN, LAMB1, SCN4B, ESRRG, RBI, FAM83A, DDR2, ANKRD22, COPZ2, DAPP1, A4GALT, TLE2, OPRK1, KLHL13, PRSS8, CNTN1, MYLK, BMPR1B, RGS11, CITED4, LAG3, ZNF469,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002SCNN1B, NDP. TSPYL5, PID1, ALDH3B2, ADORA1. GLB1L2, SORBS2, B4GALNT2, LCK, MEGF10, TGFB1I1, IGFBP3, STC1, TMEM200B, LOXL2, APLN, DKK3, PKDCC, TLR3, FGFR1, CAV1, FAT4, VIM, ZNF365, CADM1, ATP13A4, RAB3B, TGM2, NFIA, TACR1, NRP1, FSTL4, LYPD3, AKR1E2, BOC. KCNMB4, FNDC4, LAMA4, ETV7, NGEF. SUSD3. EFR3B. MMP15, VSIG10L, MATN3, ENPP3, EFCAB6, SH3RF2, CMBL, GHR, PMP22, LOX, SORCS2, RDH10, C1QTNF2, SCNN1G, RNF165, SDC2, SLC12A2, INHBA, SLC13A3, PLCB1, CX3CL1, HYDIN, GLT8D2, MDK, RNF43, FEZ1, RNF152, MPV17L, ANO1, CDK6, CILP2, JPH2, PDGFD, HOXC11, EPHB3, DDX58, PLTP, SERPINE1, SLC2A10, KHDRBS3, TRIM9, NTN4, CORO1A, B3GALT5. EVA1A, PDE6B, GPR176, EFEMP2, NPR2. GLRB, DMC1, CTF1, CD8A, PMAIP1, ALDOC, PDGFA, TGFB2, LIMS2, FBLN7, TPST1, EMP1, UBASH3B, ADAMTS15, ISG20, ECHDC1, LYPD1, SHOX2, VWDE, PROCR, HSH2D, CLCN4, FAM189A2, MAP1B, NOX5, GPC1, TBX3. PRSS27, GYG2, FAM83F, F3, PGF. PRSS23, ITGA5, COL18A1, SHANK2, SHANK3, ATP1B1, RASGRP3, PTGES, SGCE, FRY, NOTUM, ENG, EID1, SLC27A2, WBP2NL, JAG1, PRRT2, RNF180, SCD5, PLLP, BEAN1. FERMT2, TPPP3, FUT9, ASRGL1, NPTXR, HCST, MPZL2, C6orfl41. PLK2, EFHC2, COL16A1, ADORA2B. FBLN1, ZNF501, CACNA1D, AFAP1L1, ATP8A1, DOC2A, MMEL1, CD6, ARHGEF25, PCSK6, SPATA6, TLR1, L3MBTL1, ADHFE1, GPX8, ABLIM3, CES4A, TRPC1. CNIH3, MCAM, PCDHB13, ROR1, MEIS3, SNTB1, AK7, AHRR, ABCC2, NDRG4, GPR39, IGFBP6, SERTAD4, SPTBN5, NQO1, IL20RB, INHA, ZNF471, PNCK, ADAM12, MAPK15, MAML3, SHROOM2, FAM221A, CROT, RHOBTB3, SEC14L5, SGSM1, DUSP5, TNFRSF11A, MAP2, MEGF6, NKD1. C1QTNF6, USP18, DMGDH, EPS8, EML1 , MRAS, PNPLA7, ANKRD34A, PDGFC, VEGFA, FZD4, LAMA3, CD83, PDK3, EPAS1, CDH26, THRB, BRSK1, RIBC2, HSPG2, EGFR, GGT7, MYOMI, PPP1R36, HAS3, PDGFB, WNT2B, PPFIA4, HOXC13, CHST3, STU, THBS1, FIGN, HLX, GAL3ST4, RFTN1, Clorfl l5, HSPA12A, SLC29A4, RPS6KA2, PHLDB2, PNPLA4, CDHR3, ST3GAL4, ITGB5, CRIP2, ULBP1, PTPRG, ZNF717, SCN1B, SH3RF3, ADAMTS1, PKD1L1, ATP2A1, ACOT4, SLC22A17, MAML2. CYBRD1. ZBTB20, CENPW. LGALS1, or combinations thereof; (9) ADCY9, ANGPTL4, ANKS3, ARHGAP5, ARHGEF17, ATP7B, BCAR1, BCO2, C14orf28, CACNB1, CD59, CDIPT. CES2, CMBL, CNNM2, COPZ2, CTNNAL1, CTSS, DDR2, ENGASE, EPAS1, FGFR1, FLYWCH1, GHR, GLIS2, GMPPA, GNAI1, HM13, JMJD8, KLHL26, L3MBTL2, MAOA, MORN4, NR4A1, NTRK2, PCSK6, PLOD3, PPP1R3C, QSOX1, RNF40, SHANK2, SIDT2,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002SLC25A42, SLC39A13, SOCS5, TBC1D20. TECPR2, TIMP3, TMEM184B, TMEM214, TTC23, USP40, WWP2, ZNF81, ADCY2, ADM, ANKRD6, ARTN, CADM4, CARD 14, CNBD2, CRIP2, DBNDD1, EMP1, ENPP4, EPB41L5, EXD3, FAM189A2, FBN3, FGF11, FHL2, FSTL4, GPC1, JPH2. KIFC3. KLK5, KRT83, MFGE8, NDRG1. PLA2R1. PPFIA4, PRR3, PRSS27, PXDN, RNF180, SCNN1G, SIAE, SLC12A8, SLC24A3, SLC6A17, STC1, TBC1D7, TLE2, TMEM217, TOMI, TRNP1, TXNRD2, VEGFA, VLDLR, ZDHHC1, ZNF469, ZNF717, PGBD5, ANK2, SRPX2, MAP1A, COL1A1, SLC2A12, SLC6A11, ADAMTS12, ATP8B2, CCDC80, COL14A1, COL1A2, COL3A1, COL5A1, COL6A3, EXOG, INPP4B, KLF6, LDLR, MAST4, MTMR11, OLFML2A, PDE4A, PHKG1, RARB, UTP23, UTRN, AKIRIN2, STX7, SYNCRIP, FAM221A, RNGTT, CD8A, MAT2B, SLC27A2, STAT1, SET, TPM3, or combinations thereof; (10) INPP5A, ADCY9, BCAR1, METRN, Cl lorf24, RIN2, RAB2A, BCKDK, ABCC2, NAA60, HDLBP, ZMAT5, SPARC, MGRN1, TRIOBP. TGM2, SERINC5, TCEA1, PMM2, POR. GMPPA, GNAI1, RAB11FIP5, FLYWCH1, FARP2, SPRYD7, SYNC, TMEM214, STRN3, SFXN3, CERCAM, SEMA4B, USP40, ATP7B, TRPC4AP. ABLIM3, COMT, ZHX3, UBN1, ENG, HHLA3, YBX2, FITM2. PLCB3. ANKS3, CMBL. WNT9A, MPP2. ANKRD6, BCL2L10, EPHX4, FAXC, FBN3, FGF11, GOLGA8A, KLK5, RAB6B, PGBD1, CCDC17, CC2D2A, EPM2A, ICA1L, KANSL1L, LRP2BP, LYPD1, MAP2, MYOID, NCOA7, NHSL1, PGAP1, PLEKHM3, PYGB, RSPH3, ZBTB44, ZNF431, ZNF708, RPS12, PDSS2, AKIRIN2, STX7, SYNCRIP, FAM221A, MDK, CD83, RNGTT, IL18R1, ZNF483, JPH2, KIAA0556, NCAPG, MSRB3, SAMD9L, DHX38, ZNF81, PTTG1, SP110, IFIT1, DDX60, XAF1, IFI44, OAS2, GBP4, STAT1, ACTG2, KRT6B, AZGP1, ZG16B, STAC2, KLK7, KRT15, CDKN2A, IFI27, COL5A2, PXDN, ACTA2, TF, NTRK2, AGT, S100A1, CRYAB, EDN2, PCP4L1, ANGPT1, PTX3, ANGPTL4, INHBB, TIMP3, SIX1, RERG, FKBP10. SMOC2, COL6A2, SNAI2, COL8A1, PXDNL, CASP14, SOD3, PIK3C2G, PCOLCE, NMU, PI15, TACSTD2, BGN, SYNM, SLITRK6, MMP2, PRELP, ADM, TBX1, IGFBP5, BATF2, AKR1C1, IFITM1, C15orf48, FBXO2, ASPHD1, RCN3, TAGLN, MXRA8, MX2, AKR1C3, PPP1R3C, FN1, XYLT1, IL32. TPM2, MYL9, NDUFA4L2, SKAP1. TMEM47, ADCY2, GPRC5C, KIAA1549L, SMARCA1, IFIT2, DHX58, SEMA3C, SCUBE2, COL17A1, MFGE8, RTN4RL1, SRPX, NR2F1, ATP13A5, NDRG1, GXYLT2, TNC. KCNK5, GAS6, ARSJ, MAOA, SLC24A3, FHOD3, FST, DDIT4L, OSR1, CCND1, SERPINE2, SUSD2, GPT, MALL, SCUBE3, OAS1, CA12, COL7A1, EGLN3, SLC6A17, LAMB1, SCN4B, ESRRG, RBI, FAM83A, DDR2, ANKRD22,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002COPZ2, DAPP1, A4GALT, TLE2, OPRK1, KLHL13, PRSS8, CNTN1, MYLK, BMPR1B, RGS11, CITED4, LAG3, ZNF469, SCNN1B, NDP, TSPYL5, PID1, ALDH3B2, ADORA1, GLB1L2, SORBS2, B4GALNT2, LCK, MEGF10, TGFB1I1, IGFBP3, STC1, TMEM200B, LOXL2, APLN, DKK3, PKDCC. TLR3. FGFR1, CAVE FAT4. VIM, ZNF365, CADM1. ATP13A4, RAB3B, NFIA, TACR1, NRP1, FSTL4, LYPD3, AKR1E2, BOC, KCNMB4, FNDC4, LAMA4, ETV7, NGEF, SUSD3, EFR3B, MMP15, VSIG10L, MATN3, ENPP3, EFCAB6, SH3RF2, GHR, PMP22, LOX, SORCS2, RDH10, C1QTNF2, SCNN1G, RNF165, SDC2, SLC12A2, INHBA, SLC13A3, PLCB1, CX3CL1, HYDIN, GLT8D2, RNF43, FEZ1, RNF152, MPV17L, ANO1, CDK6, CILP2, PDGFD, HOXC11, EPHB3, DDX58, PLTP, SERPINE1, SLC2A10, KHDRBS3, TRIM9, NTN4. CORO1A, B3GALT5, EVA1A, PDE6B, GPR176, EFEMP2, NPR2, GLRB, DMC1, CTF1, CD8A, PMAIP1, ALDOC, PDGFA, TGFB2, LIMS2, FBLN7, TPST1, EMP1, UBASH3B, ADAMTS15, ISG20, ECHDC1, SHOX2, VWDE, PROCR, HSH2D, CLCN4, FAM189A2, MAP1B. NOX5, GPC1, TBX3, PRSS27, GYG2, FAM83F, F3, PGF, PRSS23, ITGA5, COL18A1, SHANK2, SHANK3, ATP1B1, RASGRP3. PTGES, SGCE, FRY, NOTUM, EID1, SLC27A2, WBP2NL, JAG1, PRRT2, RNF180, SCD5, PLLP, BEAN1. FERMT2. TPPP3, FUT9. ASRGL1. NPTXR, HCST. MPZL2, C6orfl41, PLK2, EFHC2, COL16A1, ADORA2B, FBLN1, ZNF501, CACNA1D, AFAP1L1, ATP8A1, DOC2A, MMEL1, CD6, ARHGEF25, PCSK6, SPATA6, TLR1, L3MBTL1, ADHFE1, GPX8, CES4A, TRPC1, CNIH3, MCAM, PCDHB13, ROR1, MEIS3, SNTB1, AK7, AHRR, NDRG4, GPR39, IGFBP6, SERTAD4, SPTBN5, NQO1, IL20RB, INHA, ZNF471, PNCK, ADAM12, MAPK15, MAML3, SHROOM2, CROT, RHOBTB3, SEC14L5, SGSM1, DUSP5. TNFRSF11A, MEGF6, NKD1 , C 1QTNF6, USP18, DMGDH, EPS8, EML1 , MRAS, PNPLA7, ANKRD34A, PDGFC, VEGFA, FZD4, LAMA3, PDK3, EPAS1, CDH26, THRB, BRSK1, RIBC2, HSPG2, EGFR, GGT7, MYOMI, PPP1R36, HAS3, PDGFB. WNT2B, PPFIA4, HOXC13, CHST3, STM, THBS1, FIGN, HLX, GAL3ST4, RFTN1, Clorfll5, HSPA12A, SLC29A4, RPS6KA2, PHLDB2, PNPLA4, CDHR3, ST3GAL4, ITGB5, CRIP2, ULBP1, PTPRG, ZNF717, SCN1B, SH3RF3, ADAMTS1, PKD1L1. ATP2A1, ACOT4. SLC22A17, MAML2, CYBRD1. ZBTB20. CENPW. LGALS1, ARHGAP5, ARHGEF17, BCO2, C14orf28, CACNB1, CD59, CDIPT, CES2, CNNM2, CTNNAL1, CTSS, ENGASE, GLIS2, HM13, JMJD8, KLHL26, L3MBTL2, MORN4, NR4A1, PLOD3, QSOX1, RNF40, SIDT2, SLC25A42, SLC39A13, S0CS5, TBC1D20, TECPR2, TMEM184B, TTC23, WWP2, ARTN, CADM4, CARD 14, CNBD2, DBNDD1, ENPP4, EPB41L5, EXD3, FHL2, KIFC3,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002KRT83, PLA2R1, PRR3, SIAE, SLC12A8, TBC1D7, TMEM217, TOMI, TRNP1, TXNRD2, VLDLR, ZDHHC1, PGBD5, ANK2, SRPX2, MAP1A, COL1A1, SLC2A12, SLC6A11, ADAMTS12, ATP8B2, CCDC80, COL14A1, COL1A2, COL3A1, COL5A1, COL6A3, EXOG, INPP4B, KLF6, LDLR. MAST4, MTMR11, OLFML2A, PDE4A, PHKG1, RARB. UTP23, UTRN, MAT2B, SET, TPM3, or combinations thereof; or (11) combinations thereof. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by taxane chemotherapeutic agents administered as a single agent. In some embodiments, the taxane chemotherapeutic agents include, without limitation, docetaxel, paclitaxel, or combinations thereof. In some embodiments, the taxane chemotherapeutic agent includes docetaxel.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0038] In some embodiments, the measured biomarkers include one or more of the following measured biomarkers: (1) ACSS2, ARMCX3, RAB2A, WBP2NL, SLC22A18, DECR1, DYSF, EXOCI, STAM2, KDELR2, AP1B1, VRK3, METRN, INTS8, PRRC1, PDE6D, NCOA2, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, EIF2D, ACBD5, AIG1, DTWD1, ELP2, EPM2A. PAQR6, PIK3C3, RARS2, SF3B5, SHPRH, ZC3HAV1L, ORC1, EIF4A3, CSRP2, NUP85, CEBPB, MOB3B, MCM3. NCAPH2, ERI1, CDCA7, PRKAB1, NUP210, POP5, TNFAIP2, PARD6A, RHEBL1, FBL, HAUS5, MFHAS1, PRIM1, PINX1, C12orf43, PCBP2, CHAF1B, TMPO, E2F7, MED12L, CNTLN, DDX23, GATC, WDR76, MCM2, RFC5, HAUS1, or combinations thereof; (2) LGALS1, GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11, KIF2C, CDK19, or combinations thereof; (3) MAD2L1, OVOL2, OAS2, IFI44, IFI44L, OAS1, or combinations thereof; (4) ARMCX3, DNAJC3, DSTYK, EIF2D, KDELR2, KPNA3, METRN, PEX2, RAB2A, SLC35B3, STX12, SUGT1, TMEM106B, TWISTNB, UBE2W, VPS36, WBP2NL, ZNF12, ZNF623, ALYREF. C12orf43, EIF4A3, ERH, FBL, GATC, HAUS1, KIF2C, LGALS3BP, MCM2, NFKB2, NUP37, NUP85, ORC1, PCBP2. POP5, PRIM1, RELB, RFC5, TMPO, or combinations thereof; (5) ACSS2, ARMCX3, RAB2A, WBP2NL. SLC22A18, DECR1, DYSF, EXOCL STAM2, KDELR2, AP1B1, VRK3, METRN, INTS8, PRRC1, PDE6D, NCOA2, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, EIF2D, ACBD5, AIG1, DTWD1, ELP2, EPM2A, PAQR6, PIK3C3, RARS2. SF3B5, SHPRH, ZC3HAV1L, ORC1, EIF4A3, CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERH, CDCA7, PRKAB1, NUP210, POP5, TNFAIP2, PARD6A, RHEBL1, FBL, HAUS5, MFHAS1, PRIM1, PINX1, C12orf43, PCBP2. CHAF1B. TMPO, E2F7, MED12L, CNTLN, DDX23, GATC, WDR76, MCM2, RFC5, HAUS1 , LGALS1 , ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A1 1 , KIF2C, CDK19, MAD2L1, OVOL2, OAS2, IFI44, IFI44L, OAS1, DNAJC3, DSTYK, KPNA3, PEX2, SLC35B3, STX12. SUGT1. TMEM106B, TWISTNB, UBE2W, VPS36. ZNF12, ZNF623. LGALS3BP, NFKB2, NUP37, RELB, or combinations thereof; (6) LGALS1, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469, LGALS3BP, SUV39H1, TP53INP2, or combinations thereof; (7) GOLGA5, DUSP18, EHBP1L1. ACSS2. ARMCX3. TRIP11, RAB2A. WBP2NL, SLC22A18, FOXRED2. DECR1, DYSF, TOMI, ZNF70, EXOCI, PES1, D2HGDH, STAM2, KDELR2, AP1B1, TECPR2, RNF185, VRK3, METRN. MORC2, MPV17, INTS8, HSCB, PRRC1, ATP6V0E1, EHD1, PHF20. SERINC3, FLVCR2, PDE6D, HPS4, INPP5A, TM9SF4, NCOA2, VPS37C, RBKS, PRKCD, JKAMP, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, EIF2D, ACBD5, AIG1, ANKRD46, ATP6AP1L, BTBD3,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002C2orf76, CLHC1, COA5, CRCP, DBT, DCUN1D4, DHRS12, DPH5, DPY19L4, DTWD1, DYNC1LI2, EFNA3, ELP2, EPM2A, INTS6, KIF3A, KRIT1, LAMTOR3, MFF, NEURL2, PAQR6, PCGF3, PEX6, PIK3C3, PSTK, RAB11FIP2, RAD50, RARS2, SAR1A, SENP8, SF3B5, SHPRH, SLC2A11, SMARCADE TIGD6, TMEM67, WDPCP, ZC3HAV1L. ZKSCAN1, ZRANB1, GPHN, MACROD2, YLPM1, UNC119B, ZNF787, ZNF287, APOLD1, MEST, TNKS, RUVBL2, UBR7, COX14, ORC1, PPP3CC, EIF4A3, RARRES1, CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERI1, CDCA7, PRKAB1, NUP210, CCAR1, POP5, TNFAIP2, IGF2BP2, PARD6A, AKAP5, RHEBL1, FBL, HAUS5, CDKN2A, MFHAS1, PRIM1, PINX1, C12orf43, PCBP2, CHAF1B, TMPO, LXN, TLR1, E2F7, MED12L, CNTLN, ZNF483, DDX23, GATC, WDR76, MCM2, RFC5, HAUS1, ACP2, ALAS1, ANKRD22, ANKRD33B, ANXA11, C1R, CC2D1B, CD274, CYTH1, DRAM1, EGLN2, ELF4, FBXO6, GRB2, IFIH1, IKBKG, IL18BP, JMJD6, KLHDC7B, LAG3, LAMP3, LGALS3BP, MX1, MYD88, NFKB2, OAS2, OAS3, OASL, PARP12, PIK3CD, RAB35, RBM42, REC8, RELB, RNF213, RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM14, or combinations thereof; (8) PTGER4, PPM1A, RBFOX2, BRWD1. IRF1, FEN1, TOMM40, OAS2. or combinations thereof; (9) PARPBP, AURKB, AURKA, BTN3A3, TLR3, SAMD9L, PARP12, DDX60, IFIH1, PLSCR1, IFITM1, IRF9, OAS2, BATF2, STAT1, OAS3, IFI27, OAS1, UBE2L6, GBP4, ETV7, GBP1, BST2, XAF1, DDX60L, PARP14, OASL, DTX3L, SP100, B2M, SAMD9, IFI6, PSMB9, IFIT3, HERC5, ISG15, RSAD2, LAMP3, MX1, IRF1, PSME1, PSMB10, IFI35, IFI44, PARP9, IFIT1, IFIT2, HERC6, NMI, GLI4, ZNF696. ZNF517, ARHGEF37, GRHL2, SPINT2, or combinations thereof; (10) ACO2, ACSS2, ARMCX3, ATG2B, CADM1 , CLTCL1 , CXCL14, DNAJC3, DSTYK, DUSP18, EHBP1L1, EIF2D, FITM2, FOXRED2, GDF9, GLI4, HECTD1, HMGXB4. KDELR2, KPNA3, MAPK1, METRN, MORC2. MPP6, MPV17, NAA30, NR3C2, PEX2, PHF7, PIGH, PLA2G6, POLI, PPARGC1A, RAB2A, RHBDD3, RNF185, RNF215, SLC23A2, SLC29A4, SLC30A9, SLC35B3, SPRYD7, STX12, SUGT1, TMEM106B, TOMI, TRIP11, TTLL1, TWISTNB. UBE2W, VPS36. WBP2NL, WIPF2, ZFP28, ZNF12, ZNF471, ZNF623, ZNF70, ANKRD46, ARMC10, ATP6AP1L, BTBD3, C2orf76, CLHC1, COA5, CRCP, DBT, DCUN1D4, DHRS12, DPH5, DPY19L4, DYNC1LI2, EFNA3. ELP2, INTS6, ISCA1, KIF3A, KRIT1, LAMTOR3, MFF, NEURL2, PAQR6, PCGF3, PEX6, PIK3C3, PSTK, PTCD3, PUM2, RAB11FIP2, RABGGTB, RAD50, SAR1A, SENP8, SLC2A11, SMARCAD1, SRSF11, TIGD6,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002TMEM67, WDPCP, ZKSCAN1, ZNF644. ZRANB1, DZANK1, GPHN, ACPI, E2F6, YLPM1, ZNF787, MEST, RUVBL2, UBR7, ORC1, EIF4A3, NUP85, NUP210, POP5, IGF2BP2, FBL, PRIM1, C12orf43, PCBP2, TMPO, LXN, TLR1, ZNF483, GATC, MCM2, RFC5, HAUS1, ACP2, ALAS1, ALYREF, ANKRD22, ANKRD33B. ANXA11. C1R, CC2D1B. CD274, CYTH1, DRAM1, EGLN2, ELF4, ERH, FBXO6, GRB2, IFIH1, IKBKG, IL18BP, JMJD6, KIF2C, KLHDC7B, LAG3, LAMP3, LGALS3BP, MX1, MYD88, NFKB2, NUP37, OAS2, OAS3, OASL, PARP12, PIK3CD, RAB35, RBM42, REC8, RELB, RNF213, RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM14, TXLNB, C15orf48, ATP6V0A4, LTF. HERC5, ARPC1B, CYBA. or combinations thereof; (11) GOLGA5, DUSP18, EHBP1L1, ACSS2, ARMCX3, TRIP11, RAB2A, WBP2NL, SLC22A18, FOXRED2, DECR1, DYSF, TOMI, ZNF70, EXOCI, PES1, D2HGDH, STAM2, KDELR2, AP1B1, TECPR2, RNF185, VRK3, METRN. MORC2, MPV17, INTS8. HSCB, PRRC1, ATP6V0E1, EHD1, PHF20. SERINC3, FLVCR2, PDE6D, HPS4, INPP5A, TM9SF4, NCOA2, VPS37C, RBKS, PRKCD, JKAMP, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, EIF2D, ACBD5, AIG1, ANKRD46. ATP6AP1L, BTBD3, C2orf76, CLHC1, COA5, CRCP. DBT. DCUN1D4, DHRS12, DPH5, DPY19L4, DTWD1, DYNC1LI2, EFNA3, ELP2, EPM2A, INTS6, KIF3A, KRIT1, LAMTOR3, MFF, NEURL2, PAQR6, PCGF3, PEX6, PIK3C3, PSTK, RAB11FIP2, RAD50, RARS2, SAR1A, SENP8, SF3B5, SHPRH, SLC2A11, SMARCAD1, TIGD6, TMEM67, WDPCP, ZC3HAV1L, ZKSCAN1, ZRANB1, GPHN, MACROD2, YLPM1, UNC119B, ZNF787, ZNF287, APOLD1, MEST, TNKS, RUVBL2, UBR7, COX14, ORC1, PPP3CC, EIF4A3, RARRES1. CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERI1 , CDCA7, PRKAB 1 , NUP210, CCAR1 , POP5, TNFAIP2, IGF2BP2, PARD6A, AKAP5, RHEBL1, FBL, HAUS5, CDKN2A, MFHAS1, PRIM1, PINX1, C12orf43, PCBP2, CHAF1B, TMPO. LXN. TLR1, E2F7, MED12L, CNTLN. ZNF483, DDX23. GATC, WDR76, MCM2, RFC5, HAUS1, ACP2, ALAS1, ANKRD22, ANKRD33B, ANXA11, C1R, CC2D1B, CD274, CYTH1, DRAM1, EGLN2, ELF4, FBXO6, GRB2, IFIH1, IKBKG, IL18BP, JMJD6, KLHDC7B, LAG3, LAMP3. LGALS3BP, MX1. MYD88, NFKB2, OAS2, OAS3, OASL. PARP12, PIK3CD, RAB35, RBM42, REC8, RELB, RNF213, RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM14, PTGER4, PPM1A, RBFOX2, BRWD1, IRF1, FEN1, TOMM40, PARPBP, AURKB, AURKA, BTN3A3, TLR3, SAMD9L, DDX60, PLSCR1, IFITM1, IRF9, BATF2, STAT1, IFI27, OAS1, UBE2L6, GBP4,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002ETV7, GBP1, BST2, XAF1, DDX60L, PARP14, DTX3L. SP100, B2M, SAMD9, IFI6. PSMB9, IFIT3, HERC5, ISG15, RSAD2, PSME1, PSMB10, IFI35, IFI44, PARP9, IFIT1, IFIT2, HERC6, NMI, GLI4, ZNF696, ZNF517, ARHGEF37, GRHL2, SPINT2, ACO2, ATG2B, CADM1, CLTCL1, CXCL14, DNAJC3, DSTYK. FITM2. GDF9, HECTD1, HMGXB4, KPNA3, MAPK1, MPP6, NAA30, NR3C2, PEX2, PHF7, PIGH, PLA2G6, POLI, PPARGC1A, RHBDD3, RNF215, SLC23A2, SLC29A4, SLC30A9, SLC35B3, SPRYD7, STX12, SUGT1, TMEM106B, TTLL1, TWISTNB, UBE2W, VPS36, WIPF2, ZFP28, ZNF12, ZNF471, ZNF623, ARMC10, ISCA1, PTCD3, PUM2, RABGGTB, SRSF11, ZNF644, DZANK1, ACPI, E2F6, ALYREF, ERH, KIF2C, NUP37, TXLNB, C15orf48, ATP6V0A4, LTF, ARPC1B, CYBA, or combinations thereof; or (12) combinations thereof. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum and taxane chemotherapeutic agents administered in combination. In some embodiments, the platinum and taxane chemotherapeutic agents include carboplatin plus docetaxel, carboplatin plus paclitaxel, cisplatin plus docetaxel, or cisplatin plus paclitaxel.

[0039] In some embodiments, the measured biomarkers include LGALS1, GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11, KIF2C, CDK19, LGALS1, LGALS3BP, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469, SUV39H1, and TP53INP2. In some of such embodiments, differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum and taxane chemotherapeutic agents administered in combination. In some embodiments, the platinum and taxane chemotherapeutic agents include carboplatin plus docetaxel, carboplatin plus paclitaxel, cisplatin plus docetaxel, or cisplatin plus paclitaxel.

[0040] In some embodiments, the measured biomarkers include KRT5. In some of such embodiments, the differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents, taxane chemotherapeutic agents, or combinations thereof.

[0041] Measured biomarkers

[0042] In some embodiments, the methods of the present disclosure also include a step of measuring the biomarkers from a subject. In some embodiments, the biomarkers are measured based on gene expression, protein expression, or combinations thereof. In some embodiments, the biomarkers are measured based on gene expression.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0043] In some embodiments, the differentially expressed levels of the biomarkers correspond to increased levels of the biomarkers, decreased levels of the biomarkers, or combinations thereof. In some embodiments, the differentially expressed levels of the biomarkers correspond to increased levels of the biomarkers. In some embodiments, the differentially expressed levels of the biomarkers correspond to decreased levels of the biomarkers.

[0044] Triple negative breast cancer assessment

[0045] The methods and systems of the present disclosure may be utilized to assess triple negative breast cancer in subjects in various manners. For instance, in some embodiments, the assessment occurs manually. In some embodiments, the assessment occurs in real-time. In some embodiments, the assessment occurs continuously.

[0046] In some embodiments, the assessment occurs automatically through the utilization of an algorithm. In some embodiments, the systems of the present disclosure include the algorithm.

[0047] In some embodiments (e.g., for biomarker combinations), the algorithm is a machine learning algorithm. In some embodiments, the machine learning algorithm is comprised of an L2-regularized logistic regression algorithm. .

[0048] Machine learning algorithms may be trained in various manners. For instance, in some embodiments, the training includes: (1) feeding a first set of measured biomarker levels into a machine learning algorithm, where the first set of measured biomarker levels are from one or more subjects that have triple negative breast cancer; (2) feeding a second set of measured biomarker levels into the machine learning algorithm, where the second set of measured biomarker levels are from one or more subjects that do not have triple negative breast cancer; and (3) training the machine learning algorithm to assess the triple negative breast cancer by comparing the first set of measured biomarker levels with the second set of measured biomarker levels.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0049] Treatment decision

[0050] In some embodiments, the methods of the present disclosure also include a step of implementing a treatment decision based on the assessment. In some embodiments, the method is repeated after implementing the treatment decision. In some embodiments, the program codes of the systems of the present disclosure also include programming instructions for recommending a treatment decision based on the assessment.

[0051] The methods and systems of the present disclosure may implement or recommend various treatment decisions. For instance, in some embodiments, the treatment decision includes monitoring the course of the triple negative breast cancer, removing a tumor from the subject, administering a therapeutic agent to the subject, modifying a pre-existing treatment regimen, or combinations thereof.

[0052] In some embodiments, the treatment decision includes administering a therapeutic agent to the subject. In some embodiments, the therapeutic agent includes, without limitation, chemotherapeutic agents, carboplatin, cisplatin, taxane chemotherapeutic agents, docetaxel, paclitaxel, or combinations thereof.

[0053] Subjects

[0054] The assessment methods and systems of the present disclosure may be applied to various subjects. For instance, in some embodiments, the subject is a human being. In some embodiments, the subject is a non-human mammal, such as a mouse, dog, cat, and / or livestock.

[0055] Systems

[0056] The methods and systems of the present disclosure can be implemented through the utilization of various systems with various architectures. Similarly, the systems of the present disclosure can include various architectures.

[0057] For instance, in some embodiments, the systems of the present disclosure are in electrical communication with an algorithm of the present disclosure. In some embodiments, the systems of the present disclosure include a web-based program, an application-based program, or combinations thereof. In some embodiments, the step of receiving measured biomarkers includes entering the measured biomarkers into the system. In some embodiments, programming instructions for receiving the measured biomarkers include programming instructions for entering the measured biomarkers into the system.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0058] In some embodiments, the system includes a keyboard for a user to navigate and choose between different risk prediction functions. In some embodiments, the system further includes a display screen for displaying outputs from an algorithm.

[0059] The systems of the present disclosure can include various types of computer-readable storage mediums. In some embodiments, the computer-readable storage mediums can be a tangible device that can retain and store instructions for use by an instruction execution device. In some embodiments, the computer-readable storage medium may include, without limitation, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, and combinations thereof. A non-exhaustive list of more specific examples of suitable computer-readable storage medium includes, without limitation, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (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, and combinations thereof.

[0060] A computer-readable storage medium, as used herein, is not to be construed as being transitory signals per se. Such transitory signals may be represented by 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.

[0061] In some embodiments, 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, such as the Internet, a local area network, a wide area network and / or a wireless network. In some embodiments, the network may include copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. In some embodiments, 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.

[0062] In some embodiments, computer-readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002 machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, 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 Smalltalk, C++, or the like, and procedural programming languages, such as the "C" programming language or similar programming languages.

[0063] In some embodiments, the computer-readable program instructions may execute entirely 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 in some embodiments 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 (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 to perform aspects of the present disclosure.

[0064] Embodiments of the present disclosure as discussed herein may be implemented using a system illustrated in FIG. IB. Referring now to FIG. IB, FIG. IB illustrates an embodiment of the present disclosure of the hardware configuration of a system 30 represents a hardware environment for practicing various embodiments of the present disclosure.

[0065] System 30 has a processor 31 connected to various other components by system bus 32. An operating system 33 runs on processor 31 and provides control and coordinates the functions of the various components of FIG. IB. An application 34 in accordance with the principles of the present disclosure runs in conjunction with operating system 33 and provides calls to operating system 33, where the calls implement the various functions or services to be performed by application 34. Application 34 may include, for example, a program for assessing a triple negative breast cancer in a subject in accordance with various embodiments of the present disclosure.

[0066] Referring again to FIG. IB, read-only memory ("ROM") 35 is connected to system bus 32 and includes a basic input / output system ("BIOS") that controls certain basic functions of system 30. Random access memory ("RAM") 36 and disk adapter 37 are also connected to system bus 32. It should be noted that software components including operating system 33 and application 34 may bePCT Application Attorney Docket No. AF44111.P046WOBLG 22-002 loaded into RAM 36, which may be system’s 30 main memory for execution. Disk adapter 37 may be an integrated drive electronics ("IDE") adapter that communicates with a disk unit 38 (e.g., a disk drive). It is noted that the program for assessing a triple negative breast cancer in a subject in accordance with various embodiments of the present disclosure.

[0067] System 30 may further include a communications adapter 39 connected to bus 32. Communications adapter 39 interconnects bus 32 with an outside network (e.g., wide area network) to communicate with other devices.

[0068] Aspects of the present disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and systems according to embodiments of the disclosure. It will be understood that computer-readable program instructions can implement each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams.

[0069] These computer-readable program instructions may be provided to a processor of a 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 includes an article of manufacture including instructions which implement aspects of the function / act specified in the flowchart and / or block diagram block or blocks. The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices 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.

[0070] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and systems according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagramsPCT Application Attorney Docket No. AF44111.P046WOBLG 22-002 may represent a module, segment, or portion of instructions, which includes one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be accomplished as one step, executed concurrently, substantially concurrently, in a partially or wholly temporally overlapping manner, 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.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0071] Additional embodiments

[0072] Reference will now be made to more specific embodiments of the present disclosure and experimental results that provide support for such embodiments. However, Applicant notes that the disclosure below is for illustrative purposes only and is not intended to limit the scope of the claimed subject matter in any way.

[0073] Example 1. Patient-Derived Xenografts of Triple-Negative Breast Cancer Enable Deconvolution and Prediction of Chemotherapy Responses

[0074] In this Example, Applicant analyzed treatment response data to single agent carboplatin and docetaxel for a cohort of 50 triple negative breast cancer (TNBC) patient-derived xenografts (PDXs) derived from 46 different TNBC patients. Of these, Applicant also generated combination response data for 42 PDXs to carboplatin + docetaxel combination. Treatment response data were integrated with baseline proteogenomic (DNA / mRNA / protein) profiles to perform a set of unbiased analyses to address several key questions: 1) what are the molecular associates of and predictors of response and resistance to single agent and combination treatments, 2) what molecular features can inform the selection of a single agent for individual tumors, 3) for the few PDXs where combination was beneficial vs single agents, what features are associated with these tumors, and what features are associated with cases where the combination was worse than the best single agent, and 4) what are possible therapeutic options for tumors that lack treatment response to all chemotherapy regimens?

[0075] Applicant observed that combination responses were usually no better than the best single agent, with enhanced response in only -13% of PDX, and apparent antagonism in a comparable percentage. Single-omic comparisons showed largely non-overlapping results between genes associated with single agent and combination treatments that could be validated in independent patient cohorts. Multi-omic analyses of PDXs identified agent- specific biomarkers / biomarker combinations, nominating high Cytokeratin-5 (KRT5) as a general marker of responsiveness. Notably, integrating proteomic with transcriptomic data improved predictive modeling of pathologic complete response to combination chemotherapy.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0076] PDXs refractory to all treatments were enriched for signatures of dysregulated mitochondrial function. Targeting this process indirectly in a PDX with HD AC inhibition plus chemotherapy in vivo overcomes chemoresistance. These results suggest possible resistance mechanisms and therapeutic strategies in TNBC to overcome chemoresistance, and potentially allow optimization of chemotherapeutic regimens.

[0077] Example 1.1. Combination carboplatin and docetaxel is largely ineffective at generating enhanced responses over the best single agent in TNBC PDXs

[0078] TNBC patients frequently receive combination chemotherapy treatments based on clinical data suggesting improved response from combination chemotherapy compared with single-agent chemotherapy. However, averaging effects observed in group level data from clinical trials may not be applicable to individual patients. Further, in clinical investigations, it is impossible to assign one patient to more than one treatment arm to deconvolute response to individual agents versus combinations. Applicant hypothesized that this limitation can potentially be addressed through preclinical trials using PDX models.

[0079] To test this hypothesis, and to exploit this unique opportunity, Applicant leveraged a collection of data from 49 TNBC PDX models and one estrogen-independent, low estrogen receptor-expressing model (FCP699) (reported originally as a TNBC, and propagated without estrogen as such until ER immuno staining showed low levels of ER in some nuclei) aggregated from three separate preclinical trials. These trials included treatment arms consisting of control (no treatment) versus four weekly cycles of human-equivalent doses of carboplatin (50 mg / kg), docetaxel (20 mg / kg) or the combination at these doses. Treatment effects were evaluated by log2 fold-change in tumor volume after four weeks vs. baseline and compared using general linear models. Quantitative and qualitative best clinical responses (Methods) to each treatment were summarized for each PDX model (FIGS. 2A1- 2A2) and plotted as individual tumor volumes over time. All PDXs had treatment responses documented for single agent carboplatin and docetaxel, while 84% (42 / 50) of PDXs had combination response information.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0080] Among PDXs that had treatment response information for all arms (FIGS. 2A1-2A2, QI), 71% (30 / 42) were responsive (complete response [CR] or partially responsive [PR]) to any treatment arm, while 29% (12 / 42) were resistant (stable disease [SD] or progressive disease [PD]) to all treatment aims, according to Applicant’s modified RECIST criteria (mRECIST). When including the full cohort of 50 PDXs, 76% (38 / 50) were responsive to any treatment. When comparing quantitative tumor responses based on tumor volume change, single agent docetaxel led to stronger tumor shrinkage in a greater number of PDX models compared to carboplatin at the doses evaluated (n = 18 vs n - 11, respectively, FIGS. 2A1-2A2, Q2).

[0081] Overall average tumor shrinkage was significantly greater in the combination ami compared to either the carboplatin (Wilcoxon signed rank test p = 3.19e-06) or docetaxel arms (Wilcoxon signed rank test p= 0.02) (FIG. 2B). However, average shrinkage in the combination arm was generally comparable to the best single agent response for each PDX (p = 0.70) (FIG. 2B). This result was confirmed orthogonally with a Bliss independence model which showed no significant difference between expected and observed combination tumor responses (paired t-test p = 0.12 and Wilcoxon signed rank test p = 0.42), further supporting the observation that the increased efficacy of combination comes from an additive, not synergistic, benefit.

[0082] Individually, combination treatment generated significantly enhanced responses vs the best single agent in only 13% (4 / 30, p < 0.05) of PDXs (FIGS. 2A1-2A2, Q3). Interestingly, antagonism was also observed for combination treatment where combination response was significantly worse (p < 0.05) compared to the best single agent response in 12% (5 / 42) of PDXs (FIGS. 2A1-2A2, Q3). Moreover, in 97% (29 / 30) of PDXs that had a response to any of the three arms tested, combination treatment did not qualitatively improve response assessed by mRECIST compared to the best single agent treatment (FIGS. 2A1-2A2). These results strongly suggest that the standard-of-care for TNBC patients consisting of multiple chemotherapy agents can be optimized to reduce ineffective (unnecessary) treatment, as well as unwanted side effects, if patients could be matched to the best single agent treatment accurately.

[0083] Example 1.2, Molecular associates of chemotherapy responsePCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0084] To identify molecular correlates of treatment response and resistance that might provide mechanistic insight, Applicant examined associations between mutation, copy number, mRNA, and protein profiles in baseline PDX tumors with treatment responses. Molecular profiling by whole exome sequencing, RNA-Seq, and mass spectrometry-based proteomic profiling in these PDXs has been previously described. Significant associations were observed for 2 non-silent mutations, 429 mRNAs, and 81 proteins for carboplatin response; 5 non-silent mutations, 222 mRNAs, and 44 proteins for docetaxel response; and 8 non-silent mutations, 190 mRNAs, and 55 proteins for combination treatment response (p < 0.01, Methods, FIG. 3A). No significant associations were found with copy number data (p < 0.01).

[0085] At a more relaxed p < 0.05 threshold, high-level amplification events in 39 genes associated with carboplatin response, 22 genes associated with docetaxel resistance, and none were associated with combination response. Many genes found to be associated with carboplatin response were previously implicated in platinum resistance in cancer. Strikingly, molecular associates of response to individual treatment regimens had only limited overlap for individual data types (FIG. 3A). This was also the case when considering all omic platforms together (FIG. 3B), consistent with distinct molecular mechanisms underlying response to each treatment. As an example, deleterious BRCA2 variants were associated with increased carboplatin response but not to docetaxel, nor to the combination. Deleterious BRCA1 variants also showed this trend but were not significant in this analysis.

[0086] There were some associations that were shared between different treatments. For example, Glutamate Rich 6 (ERICH6) variants were associated with increased response to both single-agent carboplatin and docetaxel, but not the combination (FIG. 3B). For the same treatment, different types of molecular data identified distinct sets of associated genes (FIG. 3C), each contributing unique yet complementary information. This finding is not unexpected given that different types of molecular data are not fully correlated with one another. For example, the median gene- wise Spearman’s correlation between mRNA and protein was 0.46. highlighting the poor mRNA-protein correlation observed for many genes in this and other proteogenomic studies. This underscores the importance of multi-omic analyses to gain a comprehensive understanding on the genes that may underlie treatment response.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0087] To examine potential clinical relevance of genes associated with different treatment regimens at either mRNA or protein levels in the PDX analysis, Applicant next annotated genes identified in Applicant’s study using data from independent PDX and clinical trial datasets for TNBC samples that received similar treatments before response assessment. Applicant prioritized genes that were found to be associated in at least 3 or more datasets, including at least one of Applicant’s PDX-based datasets (FIGS. 3D-3F). Since concordant associations across multiple datasets reinforce each other, Applicant relaxed p-value thresholds from p < 0.01 to p < 0.05. Applicant also annotated these genes by drug target tier systems that may further nominate candidates for experimental follow-up or therapeutic development. In addition, Applicant annotated “functionally dark” genes that represent understudied (or unstudied) genes based on publication count.

[0088] Platinum treatment datasets included two PDX datasets with cisplatin (GSE 14276722 and Curie Institute), a cisplatin treatment arm from a clinical trial (GSE1886423 [DFCI]), and manually curated genes from the literature that have been associated with platinum resistance filtered to those with an association in xenograft or in patient specimens (FIG. 3D). Among the genes consistently higher in platinum-refractory samples was Glutathione Synthetase (GSS), a target of an approved nononcology drug. The impact of non-oncology drugs on cancer viability has recently come into focus and further investigation of how perturbation of GSS may augment platinum response could drive future drug repurposing efforts.

[0089] Lower level of Glucoside Xylosyltransferase 1 (GXYLT1), a “dark” gene, was consistently associated with platinum responsiveness. GXYLT1 is understudied in cancer and could potentially be a candidate for further study to better understand markers of tumor response to chemotherapy and to platinum agents in particular.

[0090] Taxane treatment datasets included a study with paclitaxel treated PDX tumors (GSE14276722), a paclitaxel containing arm from the LSPY2 trial25 (GSE194040) with tumor responses recorded after paclitaxel only before AC treatment, and from a paclitaxel arm from a previously completed clinical trial in which responses were also recorded before AC treatment (FIG. 3E).PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0091] Another “functionally dark” gene, C16orf72 was found to be associated with taxane resistance, which suggests another understudied gene for future studies to expand Applicant’s understanding of taxane resistance genes. Combination datasets were from a CPTAC study where TNBC patients were treated with carboplatin + docetaxel, and from the City of Hope (COH) National Medical Center where patients were treated with carboplatin + paclitaxel28 (FIG. 3F).

[0092] Applicant observed an understudied gene, FHF Complex Subunit HOOK Interacting Protein 2A (FAM160B1), that might have previously unknown roles in combination chemotherapy responses in TNBC. Among the genes consistently associated with chemotherapy response, only E2F Transcription Factor 7 (E2F7) was associated with more than one treatment type (FIG. 3G). This is consistent with Applicant’s above observation that distinct genes may regulate tumor responsiveness and resistance to different chemotherapy treatments. At the pathway level, RNA and protein data converged on upregulated metabolic pathways in PDXs resistant to all treatment types while upregulated E2F / G2M related pathways associated with PDXs responsive to all treatment types. Variable levels of MYC-related proliferation and interferon pathways were observed across different treatments, suggesting pathways that are common across, and unique to, different treatments (FIG.3H).

[0093] Example 1.3. Predicting chemotherapy responsePCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0094] Based on the observation that a limited number of gene sets were associated with response (FIG. 3H), machine learning models were employed to predict complete response / pathologic complete response (pCR) and complete response plus partial response (CR / PR) to chemotherapy, both clinically meaningful response cutoffs, using the Protein Marker Selection (ProMS) tool that Applicant recently developed. ProMS identifies a group of minimally redundant, and therefore complementary, markers associated with an attribute label, which for this study is chemotherapy response, where each marker represents a biological function or pathway defined by co-expressed genes. Although initially developed for protein marker selection using single or multi-omics data, ProMS can also be implemented for RNA marker selection, which is how it was applied in this study. Individual datasets from this study, and previously described external resources, were used to train separate logistic regression models using ProMS selected features to predict CR / pCR for platinum, taxane, and their combination, respectively, using transcriptomics profiling data. Due to the small sample size of each dataset, five features were selected for model training. For each treatment type, a clinical dataset, or the largest clinical dataset when more than one exists, was selected as the independent test data to evaluate fully trained model performance. Prediction performance of models trained using single datasets were highly variable and close to random (0.50) as measured by area under ROC curve (AUROC) in the set-aside cross-validation data from the same dataset. In particular, the taxane dataset 06 had a low AUROC of 0.35 and was omitted in subsequent analyses.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0095] Since models trained on individual datasets were unstable and not predictive, likely due to interpatient heterogeneity in chemotherapy resistance pathways, which cannot be fully captured by small sample sizes, datasets of the same treatment type were batch corrected and merged to increase sample size. Trained logistic regression models using up to 10 ProMS selected features (10% of training sample size) on the merged platinum training data, showed the best AUROC in the set-aside cross-validation merged data with 10 and 6 markers for the CR and CR / PR predictors, respectively. (FIGS. 4A-4B). The fully trained platinum CR and CR / PR predictors both achieved AUROCs of 0.59 on the independent test dataset 04 (FIG. 4C). A similar procedure was performed for the taxane CR and CR / PR (FIGS. 4D-4F) and platinum + taxane pCR (FIGS. 4G-4I) predictors, where logistic regression models with 6, 9, and 10 ProMS selected markers were found achieve the best crossvalidated performance, respectively (FIGS. 4D and 4G). Performance of fully trained taxane CR and CR / PR and platinum + taxane pCR logistic regression models with ProMS selected features achieved AUROCs of 0.67, 0.57 (FIG. 4F), and 0.74 (FIG. 41) on independent test data, respectively.

[0096] The ProMS method is unique for its ability to be extended to the multi-omics setting, leveraging multi-omic data for biomarker discovery within a single omic layer of interest. For the platinum + taxane predictor, both RNA and protein data were available for training datasets.

[0097] Since 10 biomarkers achieved the best cross-validated performance by using RNA data alone (FIG. 4G), merged RNA and protein data were used together to also select a group of 10 protein- informed, RNA biomarkers by running ProMS in multi-omics mode (ProMSmo). Interestingly, only one of these genes, LGALS1, overlapped with the RNA-only informed ProMS model (FIG. 4H). Performance of the platinum + taxane predictor trained with features selected by ProMSmo outperformed ProMS on independent test data, achieving an AUROC of 0.85 (FIG. 41). These results suggest protein data heavily impacts RNA marker selection and can enhance prediction performance when used together with RNA data. It is notable that the protein-informed model achieved a 0% false positive rate with close to 60% sensitivity, as revealed by the sharp initial climb in the AUROC curve, underscoring its high specificity in predicting pCR tumors in response to platinum + taxane chemotherapy.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0098] To generate predictive models that can be taken forward in future PDX-based studies and clinical trials, final, composite, logistic regression models for prediction of platinum, taxane, and platinum + taxane response were generated using all existing data. This contrasts with the models described above where a clinical dataset was withheld intentionally to use as an independent test dataset. These composite models represent “the best that can be done” until additional datasets become available. Logistic regression models were trained using ProMS selected features from FIGS. 4B, 4E and 4H, respectively with all existing data.

[0099] Average AUROC performance in the set-aside cross-validation for the composite CR / pCR predictors were 0.77, 0.68, and 0.78 for the platinum, taxane, and combination predictors, respectively while the platinum CR / PR and taxane CR / PR composite models achieved AUROCs of 0.69 and 0.63, respectively. All composite models outperformed respective non-composite models from FIGS. 4A, 4D, and 4G. Composite models were also less variable and therefore more stable across cross- validation repeat testing, especially for the taxane and combination models. The performance of these models was examined with additional independent datasets generated by Applicant’s group. Using RNA-Seq data and chemotherapy response for eight additional TNBC PDXs independent of the 50 reported in this study, the composite single agent platinum CR and CR / PR predictors achieved AUROCs of 0.57 and 0.80, respectively (FIG. 4J) while the single agent taxane CR and CR / PR predictors achieved AUROCs of 0.71 and 0.67, respectively (FIG. 4K).

[0100] In addition, Applicant analyzed RNA-Seq data from previously collected baseline TNBC tumors with neoadjuvant responses to single agent docetaxel where the composite taxane pCR predictor achieved an AUROC of 0.83 when applied to this dataset (FIG. 4K). Responsive models were very limited in these datasets which likely contributed towards variable performance. Robust performance of these composite predictors await further evaluation in datasets that may become available in the near future, including data from the BEAUTY31, TBCRC 03032, and RESPONSE (NCT05020860) clinical trials, or in future experimental settings using PDX / PDX-derived organoids. In sum, these results highlight the potential of using machine learning models, and the integration of protein data when available, to select TNBC tumors that may respond to either single agent carboplatin, docetaxel or their combination.

[0101] Example 1.4, Molecular features that discriminate best single agent response to either carboplatin or docetaxelPCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0102] To identify molecular features that discriminate single agent response to carboplatin or docetaxel directly, Applicant identified 11 models for which response to carboplatin was significantly better than docetaxel, and 18 models in which response to docetaxel was significantly better than carboplatin (FIGS. 2A1-2A2). Comparisons between the 11 and 18 models were performed using mutation, copy number, RNA, and protein data at the gene and pathway (FIGS. 5A1-5A2) levels. In PDXs where carboplatin response was better than docetaxel, molecular data, particularly RNA and protein, was associated with up-regulation of gene sets broadly related to transcriptional regulation and cell cycle, among others (FIGS. 5A1-5A2). Gene level changes reinforced geneset findings where individual genes were elevated in PDXs whose response to carboplatin was better than docetaxel such as Zinc Finger Protein 367 (ZNF367) (transcriptional regulation gene), and Anaphase Promoting Complex Subunit 5 (ANAPC5) (cell cycle gene). These genes at the RNA level were also associated individually with neoadjuvant cisplatin response in TNBC tumors from the DFCI cohort where the AUROC was the highest compared to AUROCs for the same genes in other neoadjuvant TNBC clinical datasets where patients received either single agent taxane or carboplatin + taxane before response assessment (FIG. 5B).

[0103] In contrast, in PDXs for which docetaxel response was better than carboplatin, both RNA and protein data associated higher levels of genes positively regulating the microtubule and actin cytoskeleton such as Rac Family Small GTPase 1 (RAC1), Peptidylprolyl Isomerase B (PPIB), Migration And Invasion Enhancer 1 (MIEN1), Coronin IB (CORO1B), and Cofilin 1 (CFL1), suggesting microtubule-actin coordination may impact responses to taxanes. hr addition, elevated levels of GSS were also observed in PDXs with better response to docetaxel vs carboplatin, corroborating earlier results that associated GSS with carboplatin resistance in multiple datasets (FIG. 3D). Several genes at the RNA level were also found to be most discriminatory in the MDA patient dataset where response was assessed after receiving single-agent paclitaxel neoadjuvant chemotherapy (FIG. 5B). A similar observation was made for genes found to be associated at the RNA level in addition to one or more omic profiling platforms. Discrepancies between the two taxane datasets may be due to differences in transcriptomic platforms as the MDA dataset was profiled by RNA-Seq while the ISPY2 was profiled by microarray.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0104] In sum, these results prioritize genes and pathways associated with response to individual agents with clinical relevance that can be further investigated to better understand the underlying biology behind different classes of chemotherapy treatment. Actin dynamics, protein trafficking, and mitochondrial function are correlated with positive and negative interactions between single agents. In addition to the few models that showed benefit from combination treatment, there were also a comparable number of PDXs where the combination response was worse than that to the best single agent (12% [5 / 42]) (FIGS. 2A1-2A2), a phenomenon observed previously in in vitro studies.

[0105] To examine molecular features associated with positive vs negative interaction between single agents, Applicant took two statistical approaches. Kruskall- Wallis testing using RNA or protein measurements for genes across four groups (FIGS. 2A1-2A2 and 6A): 1) PDXs for which the combination was better than single agents (n = 4), 2) PDXs for which the combination was worse than the best single agent (n = 5), 3) PDXs in which there was no enhanced response to the combination compared to the best single agent (n = 21), and 4) PDXs which were resistant to all treatments (n = 12).

[0106] Based on results from RNA and protein analyses, Applicant further computed meta-p- values for each gene by combining p-values from transcriptomic and proteomic analyses and corrected for multiple comparisons using the meta-p-values. Three genes (adjusted meta-p- values < 0.05) were associated by RNA and protein data with PDXs where the combination generated enhanced response vs single agents (FIG. 6B).PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0107] Coactosin Like F-Actin Binding Protein 1 (COTL1) and ELKS / RAB6- interacting / CAST Family Member (ERC1) were higher while Dynein Light Chain LC8-Type 2 (DYNLL2) was lower in PDXs where combination was beneficial vs all other groups. COTL1 has been shown to be a tumor suppressor in breast cancer by inhibiting non-canonical TGF-beta signaling while ERC1 is involved in trafficking, and DYNLL2 has been reported to regulate retrograde movement of cargo along microtubules. Three genes associated with PDXs where the combination was worse than the best single agent, including ATPase Plasma Membrane Ca2+Transporting 4 (ATP2B4), ETHE1 Persulfide Dioxygenase (ETHE1), and Fumarylacetoacetate Hydrolase (FAH) (FIG. 6C). ATP2B4 regulates calcium homeostasis, ETHE1 modulates hydrogen sulfide homeostasis in mitochondria, and FAH is involved in amino acid catabolism. Overall, these genes have roles in modulating actin dynamics, trafficking, and metabolism. Although understudied for their role in modulating combination chemotherapy responses in triple-negative breast cancer, Applicant’ s results prioritize these genes for further study as regulators of therapeutic efficacy.

[0108] In addition to multi-group comparisons. Applicant also examined group comparisons for PDXs where the combination was beneficial. RNA and protein data was also used for these group comparisons and then ranked by meta-p-values for each gene. Genes associated from the multi-group comparison analysis were also top-associated genes from this analysis, reinforcing the reliability of these associations.

[0109] Using meta-p-values of all genes from the analysis from group comparisons, pathway enrichment analysis showed multiple mitochondrial oxidative phosphorylation (OXPHOS)-related gene sets that were downregulated in PDXs where combo was beneficial (FIG. 6D). This is consistent with the finding that oxidative phosphorylation along with fatty acid metabolism were among the top significantly enriched pathways associated with carboplatin + docetaxel resistance in the CPTAC- TNBC cohort. In contrast, multiple gene sets related to chromatin regulation were up-regulated in PDXs where combo was worse than the best single agent (FIG. 6E). These results suggest that such processes may interfere with optimal efficacy of combination treatment.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0110] Applicant also found decreased MAPK signaling as well as decreased mitochondrial transcription and translation pathways in these PDXs (FIG. 6E). MAPK signaling is well-established for platinum- and taxane-induced apoptosis, as well as for decreased mitochondrial transcription and translation, consistent with a previous study where mitochondrial protein synthesis defects inhibited DNA-damaging agent chemotherapy-induced apoptosis due to lack of respiratory complex proteins.

[0111] These results await further validation but may suggest these processes may underlie both the positive and negative interactions between carboplatin and docetaxel.

[0112] Example 1.5. Molecular correlates to lack of response to any chemotherapy regimens evaluated

[0113] In PDXs that were treated with all 3 treatment arms, at least one treatment induced tumor shrinkage for most models, yet 29% (12 / 42) of PDXs were resistant to all chemotherapy regimens tested (FIGS. 2A1-2A2). To identify molecular associations with lack of any chemotherapy response vs response to any treatment, Applicant compared PDXs without a response to all treatment arms vs PDXs with tumor shrinkage due to any regimen using data generated across all omic platforms. In PDXs resistant to all treatments. RNA-Seq and protein data associated genesets broadly related cellular respiration and metabolism, including mitochondrial transcription and translation, OXPHOS, and fatty acid and amino acid metabolism to resistance (FIGS. 7A1-7A2). Of note, multiple proteostatic pathways related to protein folding, trafficking, and degradation along with unfolded protein response (UPR) pathways related to endoplasmic reticulum stress were heightened in PDXs resistant to all chemotherapy arms while chromatin regulation was downregulated in these PDXs. Both RNA and protein data supported various metabolism genes such as Ganglioside GM2 Activator (GM2A) involved in lipid metabolism, Galactose Mutarotase (GALM) involved in carbohydrate metabolism, and Carnitine O-Acetyltransferase (CRAT) involved in fatty acid homeostasis (FIG. 7B). Upregulation of CRAT was confirmed to be associated with tumors resistant to neoadjuvant carboplatin + docetaxel in the CPTAC-TNBC clinical trial where OXPHOS and fatty acid metabolism pathways were also found to be upregulated. Moreover, targeting fatty acid pathways and subsequent mitochondrial function has been shown to inhibit TNBC.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0114] KRT5 is a chemotherapy response marker for carboplatin, docetaxel, and their combination. In PDXs responsive to any treatment arm, basal marker proteins and structural components of cells, such as cytokeratins KRT5, KRT6B, and KRT17 were among the most significantly upregulated genes especially at the protein level (FIG. 7C). These gene level results support the finding that cytoskeletal / ECM gene sets were found to be lower in PDXs resistant to all treatment arms (and therefore higher in PDXs responsive to any treatment arm) (FIGS. 7A1-7A2). Since RNA and protein expression for these three markers was not significant (p > 0.05) using a traditional mean / median Wilcoxon test in human tumors from the CPTAC-TNBC clinical trial, Applicant performed the Anderson-Darling (AD) test in non-pCR vs pCR tumors to focus on gene levels in tail regions of the distribution that may account for differences in a subset of samples. Of these 3 markers, the AD-test showed that only KRT5 was significantly different at the RNA level with protein data nearing p < 0.05 (Methods), a compatible result with Applicant’s PDX data that suggests heterogeneity in KRT5 abundance for non-pCR tumors and that a subset of these non-pCR tumors may have lower levels of KRT5 compared to pCR tumors.

[0115] Both KRT5 mRNA and protein abundance were able to discriminate non-pCR CPTAC-TNBC samples from pCR samples with an AUROC of 0.69 and 0.65, respectively. Importantly, both AUROC curves demonstrated appreciable sensitivity with a 0% false positive rate, indicating high specificity of K.RT5 to distinguish non-pCR tumors to neoadjuvant chemotherapy.

[0116] Applicant further validated KRT5 by IHC staining of baseline tumors prior to treatment from the PDX cohort (FIG. 7D) where staining intensity and frequency were quantified to generate an Allred score (FIGS. 7D-7F). By using the Allred score, Applicant achieved an AUROC of 0.83 in discriminating PDX tumors responsive to any chemotherapy arm in the cohort (FIG. 7F) suggesting the potential use of KRT5 as a biomarker of responsiveness to non-anthracycline-based chemotherapy regimens consisting of carboplatin, docetaxel, or the combination.

[0117] Example 1.6. Targeted agents can enhance chemotherapy responsePCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0118] In resistant PDXs. Applicant also observed higher expression of several “cancer stemlike cell” associated pathways previously implicated in breast cancer, including Hedgehog, VEGF, Notch, and MET / RAP1 / RAC1 (FIGS. 7A1-7A2), inhibitors of which have all been evaluated in clinical trials, and all of which have not been approved for clinical use as single agents. A gamma secretase (Notch) inhibitor MK0752 was evaluated in combination with docetaxel and showed enhanced response but is not approved for clinical use. For a partial analysis of these results, Applicant used a previously completed SPORE / U54 PDXNet preclinical trial in which Applicant investigated responses to seven agents targeting these “cancer stem-like cell”-associated pathways alone and in combination with carboplatin in 11-20 randomly selected PDX models in a manner similar to unselected clinical trials without molecular matching (FIG. 8A). Four models were included that were resistant to all chemotherapy regimens, BCM-0046, BCM-7821, BCM- 15029, and HCI-028. Of the seven targeted agents evaluated, only niraparib (PARP inhibitor) and EPZ011989 (EZH2 inhibitor) resulted in significant tumor shrinkage (PR or better) as single agents, but in only two and one PDX models, respectively (FIG. 8A). Of these three models responsive to single agents, only BCM- 15029 was in the chemoresistant group. The response to single agents indicates a 2.6% overall success rate for candidate investigational agents in the absence of appropriate biomarkers. Although these sparse positive data prevent Applicant from learning the biological mechanisms underlying drug response, Applicant hypothesized that shared features between the responsive PDX models with other breast tumors that have high similarity to these PDXs could predict the observed therapeutic vulnerabilities.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0119] To test this hypothesis. Applicant applied a multi-omic computational approach that uses publicly available human data to prioritize agents for PDX testing by first querying the RNA profiles of the three PDX models that showed significant tumor shrinkage against the CPTAC cohort with proteogenomic profiling on breast tumors. For each PDX, the top 20% of the CPTAC breast tumors with the highest similarity by RNA profiles to the PDX were considered as a PDX-like group. Since the direct targets of these agents are proteins, proteomics profiles were then compared to those from the remaining tumors to identify significantly up-regulated proteins as putative targets. Remarkably, when HCI-015, which showed a high sensitivity to Niraparib, was used as a query, PARP1 (target of niraparib) ranked first among all 841 quantified druggable proteins (FIG. 8B). Moreover, for all three PDX models, the targets of effective agents (PARPl / niraparib for HCI-015 and BCM-15029, EZH2 / EPZ011989 for BCM-15006) ranked the best among targets of all tested agents (FIG. 8B) which was reflected in drug response profiles for these models (FIG. 8C), providing strong support to Applicant’s prediction approach. These data further suggest a single sample, tailored therapeutic strategy to treat a chemotherapy refractory TNBC PDX model, BCM-15029, and validates the general approach that selects PDX models for pharmacologic intervention based on drag target abundance.

[0120] Targeted agents were able to enhance carboplatin responses, albeit infrequently (FIG. 8A). For example, consistent with single agent response to niraparib in BCM-15029, niraparib enhanced response to carboplatin in this chemoresistant model (FIG. 8A). In another chemotherapy refractory model, BCM-0046, both romidepsin, an HD AC inhibitor, and carboplatin were completely ineffective as single agents. However, the combination induced a partial response (FIG. 8D). Protein abundance of romidepsin’ s targets HDAC1, HDAC2, and HDAC3 were highest in BCM-0046 out of all PDXs (FIG. 8E). Romidepsin decreases mitochondrial membrane potential which results in reduced mitochondrial function and increased generation of reactive oxygen species and that contributes to DNA damage and apoptosis.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0121] Sensitivity to the combination of romidepsin and carboplatin, but not with either single agent alone, may be explained by both high protein abundance of romidepsin’ s designated targets and the observation of highly enriched mitochondrial and OXPHOS pathways in chemotherapy resistant PDXs (FIGS. 7A1-7A2). In addition, DNA damage driven by romidepsin may enhance the cytotoxicity of platinum DNA damaging agents such as carboplatin. Future follow-up studies will be required for confirmation.

[0122] In contrast to previous preclinical studies that use positive data from a limited number of PDX models (usually 1-2 PDX models) to drive clinical trials, Applicant’s study demonstrates that benefit from targeted agents alone and in combination with chemotherapy is limited in unselected populations, similar to trials that are not biomarker driven. Indeed, two out of the four chemotherapy refractory models, BCM-7841 and HCI-028, remained insensitive to all seven targeted agents alone and in combination with carboplatin. Curiously, addition of either romidepsin or EPZ011969 to carboplatin in the HCI-015 PDX showed some evidence of antagonism such that CR to carboplatin alone converted to only a PR in combination (FIGS. 8F-8L) similar to the effect of added docetaxel in that model (FIGS. 2A1-2A2).

[0123] Furthermore, HCI-015 PDX demonstrated clear multi-agent antagonism along with other models such as BCM-4013 and FCP699 (FIGS. 8A and 8F-8L), suggesting that negative interactions with chemotherapy agents can occur with targeted agents in addition to other chemotherapy agents Applicant previously described (FIGS. 2A1-2B and 6A-6E). In summary, Applicant’s results highlight the potential of Applicant’s approach to facilitate rational design of preclinical drug studies using PDX models.

[0124] Example 1.7. Predicting objective response, complete response, and pathologic complete responsePCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0125] Following the identification of individual genes associated with differential chemotherapy responses, machine learning models were next employed to identify biomarker combinations predictive of complete response / pathologic complete response (pCR) and complete response plus partial response (CR / PR) or objective response to chemotherapy, both clinically meaningful response cutoffs. Individual datasets from this study, and previously described external resources, were used to train separate logistic regression models using a standardized feature selection process using a Protein Marker Selection (ProMS) tool that Applicant recently developed. ProMS identifies a group of minimally redundant, and therefore complementary, markers associated with an attribute label, which for this study is chemotherapy response, where each marker represents a biological function or pathway defined by co-expressed genes.

[0126] Although initially developed for protein marker selection using single or multi-omics data, ProMS can also be implemented for RNA marker selection, which is how it was applied in this study. ProMS selected features to predict CR / pCR for platinum, taxane, and their combination, respectively, using transcriptomics profiling data. Due to the small sample size of each dataset, five features were selected for model training. For each treatment type, a clinical dataset, or the largest clinical dataset when more than one exists, was selected as the independent test data to evaluate fully trained model performance. Prediction performance of models trained using single datasets were highly variable and close to random (0.50) as measured by area under ROC curve (AUROC) in the set-aside cross-validation data from the same dataset. In particular, a taxane dataset had a low AUROC of 0.35 and was omitted in subsequent analyses. Since models trained on individual datasets were unstable and not predictive, likely due to interpatient heterogeneity in chemotherapy resistance pathways, which cannot be fully captured by small sample sizes, datasets of the same treatment type were batch corrected and merged to increase sample size.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0127] Applicant’s previous study also showed that prediction performance is highly dependent on the feature selection method. Therefore, Applicant compared four different feature selection methods, (1) genes associated with quantitative responses (regression genes), (2) WGCNA- CTD, (3) ProMS, and (4) CR / PR-associated genes, to evaluate their ability to predict objective (CR / PR), complete, and pathologic complete responses in the merged transcriptomic datasets. Predictive features for predicting objective responses for platinum and taxane from each of the feature selection methods were largely non-overlapping (FIGS. 9A and 11A-11I), indicating that each of the feature selection methods may capture distinct aspects of chemotherapy response biology.

[0128] Logistic regression models trained using features from each method showed variable performance in predicting objective CR / PR responses to platinum and taxane chemotherapy (FIG. 9B), ranging from 0.55-0.75 and 0.52-0.58 AUROC, respectively. For chemotherapy regimens, pooling all non-overlapping features from each method resulted in even higher predictive performance than any feature selection method alone at 0.76 and 0.58 for platinum and taxane objective responses, respectively (FIG. 9B).

[0129] For complete and pathologic complete response predictors, the same four feature selection methods again identified largely distinct sets of genes (FIG. 9C) similar to the patterns observed for the CR / PR models. Logistic regression models trained using these feature sets also showed variable performance across chemotherapy regimens (FIG. 9D). For platinum, WGCNA- CTD features generated the highest performance predictor with an AUROC of 0.68 (FIG. 9D). For taxane and combination treatments, (p)CR associated genes generated the highest performance predictor with an AUROC of 0.68 and 0.81 , respectively (FIG. 9D). These results indicate that, as with the CR / PR predictor, the choice of feature selection methods influences (p)CR prediction performance.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0130] The ProMS method is unique for its ability to be extended to the multi-omics setting, leveraging multi-omic data for biomarker discovery within a single omic layer of interest. For the platinum + taxane predictor, both RNA and protein data were available for training datasets. Since 10 biomarkers achieved the best cross-validated performance by using RNA data alone (FIG. 11G), merged RNA and protein data were used together to also select a group of 10 protein-informed, RNA biomarkers by running ProMS in multi-omics mode (ProMSmo). Only one of these genes, LGALS1, overlapped with the RNA-only informed ProMS model (FIG. 11H). Performance of the platinum + taxane predictor trained with features selected by ProMSmo outperformed ProMS on independent test data, achieving an AUROC of 0.85 (FIG. 111).

[0131] These results suggest protein data heavily impacts RNA marker selection and can enhance prediction performance when used together with RNA data. It is notable that the protein- informed model achieved a 0% false positive rate with close to 60% sensitivity, as revealed by the sharp initial climb in the AUROC curve, underscoring its high specificity in predicting pCR tumors in response to platinum + taxane chemotherapy.

[0132] In sum, these results highlight the potential of using machine learning models, and the integration of protein data when available, to select TNBC tumors that may respond to either single agent carboplatin, docetaxel or their combination, consistent with our previous work.

[0133] Example 1.8. Optimizing feature selection approaches improves prediction of chemotherapy response

[0134] To improve upon the transcriptome-based models and to generate predictive models that can be taken forward in future PDX-based studies and clinical trials, final, composite, logistic regression models for prediction of platinum, taxane, and platinum + taxane complete / pCR response were generated using all existing data. This contrasts with the models described above where a clinical dataset was withheld intentionally to use as an independent test dataset.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0135] The four feature selection approaches again identified distinct sets of genes (FIG. 10A). Performance of logistic regression models to predict CR / pCR was assessed using Monte-Carlo cross-validation (MCCV) where 70% of the data was randomly used for training and the remaining 30% was held out for testing. This process was repeated 50 times to approximate how they would perform on unseen samples (FIG. 10B). This approach allowed Applicant to use the full dataset for training while still obtaining an internal estimate of generalizability. Results of this process generated higher performing models than previously described with the composite platinum predictor reaching an AUROC of 0.83 using CR-associated genes and pooled features, the composite taxane predictor achieving an AUROC of 0.81 with regression and CR-associated genes, and the composite platinum + taxane predictor achieving an AUROC of 0.86 with CR-associated genes (FIG. 10B). By using pooled features from the composite models, logistic trained predictors showed extremely high performance when applied to the models used to train them as expected (FIG. 10C). These logistic trained models using pooled composite features were then applied to a small, independent dataset that included 11 additional PDXs that were not part of the original PDXs. These models maintained strong predictive performance with an AUROC of 0.80 for platinum and platinum + taxane predictor (FIG. 10C). In summary, these findings highlight the impact of different feature- selection strategies and the benefit of maximizing sample size to train high-performance models for predicting chemotherapy response.

[0136] Example 1.9. Discussion

[0137] Cytotoxic chemotherapy regimens for TNBC patients frequently include several agents given in combination, or in series, without prior knowledge of whether a given agent would be effective or ineffective for an individual patient. Deconvolution of response to multiple single agents is difficult-to-impossible to address effectively in clinical trials and it is not possible to assign the same patient to multiple treatment arms. Applicant addressed this critical issue by leveraging a clinically- relevant, large cohort of 50 orthotopically transplanted PDXs where each model was assessed for response to human equivalent doses of single agent carboplatin, docetaxel, or the combination.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0138] Applicant also leveraged multiple publicly available PDX and neoadjuvant TNBC datasets in which mice or patients were treated with similar chemotherapy regimens for validation throughout the study to suggest clinical relevance of their findings, particularly if these gene panels can be refined. Applicant’s investigation into the lack of enhanced combination response compared to the best single agent for a given TNBC PDXs has numerous important biological and clinical implications discussed herein.

[0139] Molecularly guided therapy is largely lacking for TNBC, and the underlying molecular associations of treatment response to platinum derivatives, taxane compounds, and their combination is poorly understood. FIGS. 5A1-5A2 show molecular profiling data from multiple omic platforms in baseline PDX tumors prior to treatment associated gene sets related to chromatin regulation that were upregulated in tumors with better response to single agent carboplatin vs docetaxel. Changes in chromatin accessibility have been linked to sensitivity and resistance to DNA cross-linking, platinum chemotherapy agents such as cisplatin and these changes have been associated with impacts on the transcriptional landscape. In contrast, in PDXs for which docetaxel response was better than carboplatin, both molecular data associated higher levels of genes with roles in metabolism and structural integrity (FIGS. 5A1-5A2).

[0140] More specifically, metabolism genes such as Glutathione Synthetase (GSS) and Glutathione S-Transferase Kappa 1 (GSTK1) are involved in the synthesis of a detoxification enzyme, glutathione, and conjugation of glutathione to substrates promotes elimination of toxic compounds from cells. There is evidence for glutathione promoting resistance to alkylating agents, including platinum agents. After cisplatin enters cells, it can be complexed with glutathione and subsequently exported out of cells. This may explain higher levels of GSS and GSTK1 observed in PDXs with better response to docetaxel than carboplatin where these genes may contribute to a degree of platinum insensitivity due to carboplatin being inactivated by elevated glutathione metabolism. In addition, genes positively regulating the microtubule and actin cytoskeleton were found to be higher in PDXs that responded better to docetaxel than carboplatin, suggesting a level of microtubule- actin coordination which may impact responses to taxanes since their mechanism of action involves microtubule disruption. Together, these data provide biological insights into the distinct underlying associations to different chemotherapy agents.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0141] There is a great need to identify additional biomarkers for precision diagnostics beyond ER, PR, and HER2. In contrast to neoadjuvant pCR predictors for taxane-anthracycline based regimens using gene expression, predictors for anthracycline-free and platinum-containing regimens are understudied. Incorporation of carboplatin with taxane-anthracycline regimens improved pCR rates compared with taxane-anthracycline alone in TNBC patients from the BrighTNess trial6 (58% vs 31%, respectively). Furthermore, multiple TNBC trials examining anthracycline-free regimens consisting only of carboplatin + taxane have shown pCR rates above 50%, suggesting opportunities for chemotherapy optimization. Although the immune-checkpoint inhibitor pembrolizumab is now approved for neoadjuvant use in combination with carboplatin / taxane / anthracy cline-containing chemotherapy, this regimen provided a 7% improvement in pCR rate compared with chemotherapy alone, suggesting a critical need for predictive biomarkers to identify patients that will benefit from immune-checkpoint inhibition.

[0142] Since tumor shrinkage is a meaningful endpoint of neoadjuvant chemotherapy that leads to downstaging and improving surgical outcomes, Applicant’s CR / PR predictors, especially for single agent platinum (FIG. 4J) could also have implications for personalizing treatment strategies, optimizing patient selection for neoadjuvant therapy, and guiding clinical decision making to minimize overtreatment. The taxane CR / PR predictors did not perform as well as their CR counterparts which might be attributed to the inclusion of multiple CR / PR datasets with response annotation from MRI- based clinical measurements. Discrepancies might arise in generating accurate response labels, such as distinguishing PR from SD, and therefore may impact the consistency and reliability of the training data, leading to reduced model performance and less predictive power in borderline response categories.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0143] The high performance and high specificity of Applicant’ s protein-informed, multi-omic pCR predictor for platinum + taxane (FIG. 41) has important implications for identifying patients that will respond to chemotherapy without the need for additional pembrolizumab and anthracycline / cyclophosphamide. Integrating proteomic data with transcriptomic data demonstrates the added value of incorporating diverse molecular profiles to enhance chemotherapy response predictions. Moreover, the ProMS and ProMSmo selected biomarkers that comprise Applicant’s chemotherapy response predictors to single-agent platinum, taxane, and their combination form a relatively small set of genes that is tractable for further validation and clinical translation and therefore attractive for future development into a precision diagnostic.

[0144] Applicant has trained a final composite model using all available datasets for each treatment type and these are ready to be applied to any additional dataset, such as the BEAUTY31 (NCT02022202), TBCRC 03032 (NCT01982448). and RESPONSE (NCT05020860) clinical trials. Applicant’s previous WGCNA / CTD work employed pseudo-bulk RNA-Seq data in which the mouse stromal reads were added to the human epithelial tumor cell reads in an attempt to mimic bulk RNA Seq data from human-only clinical samples. Unfortunately, not all datasets were appropriate for such analysis

[0145] However, going forward, using stromal genes from pseudo-bulk data could also help improve Applicant’s predictions, as these genes have been demonstrated to be highly informative, especially for taxane response prediction, in Applicant’s previous study that used a complementary approach (WGCNA / CTD) for chemotherapy response prediction.

[0146] Together with a recently described high-performance gene biomarker panel to predict pCR to neoadjuvant taxane plus anthracycline based chemotherapy regimens in TNBC, these predictors cover the multitude of chemotherapy regimens given to TNBC patients and provides strong rationale for incorporation into future clinical trials. Models of negative biomarker combinations will also be very useful to predict progressive disease or residual cancer burden, but will require more studies that include these measurements together with molecular profiling.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0147] Despite finding differences in molecular associations to various chemotherapy agents described above, Applicant’s investigation into associations with response to any treatment arm tested identified KRT5, a basal cytokeratin associated with basal-like breast cancer, as a potential biomarker to stratify TNBC tumors for treatment. Immunohistochemistry for basal cytokeratins 5 / 6, 14, and 17 have been used previously to define basal-like breast cancer and examine associations with chemotherapy responses to different treatment regimens. Further stratifying TNBC tumors using positivity for at least one of these basal cytokeratins identified patients with better adjuvant response to cyclophosphamide, methotrexate, and 5-fluorouracil (CMF) chemotherapy and to capecitabine but also identified patients with worse adjuvant response to anthracycline-based chemotherapy compared to patients without these markers.

[0148] The presence of these markers was also associated with worse response of TNBC patients treated with anthracycline-based chemotherapy in the neoadjuvant setting. Here, Applicant observed high KRT5 protein abundance by mass-spectrometry-based measurements in TNBC tumors responsive to non-anthracycline-based chemotherapy consisting of single agent carboplatin, docetaxel, or their combination. These data suggest basal-like markers may be either positive or negative markers of TNBC response to chemotherapy, depending on the regimen and also provide rationale for further investigation for KRT5 as a companion diagnostic.

[0149] Applicant confirmed KRT5 findings by IHC in PDX tumors and a KRT5 Allred IHC score achieved a high AUROC of 0.83 for discriminating responsive PDXs from this study to any chemotherapy (FIG. 7F). Additional validation of KRT5 IHC in human breast cohorts with chemotherapy response information is ongoing.

[0150] Applicant also identified a group of genes in PDXs quantified at the RNA level, aided by protein level measurements, that was predictive of neoadjuvant chemotherapy response in TNBC tumors (FIGS. 4A-4K). Future diagnostic assays and prospective clinical trials will be required to evaluate the clinical utility of these candidate biomarker or biomarker combinations.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0151] In PDXs resistant to all treatment arms, Applicant also found elevated levels of OXPHOS and lower levels of glucose metabolism / glycolysis related pathways (FIGS. 7A1-7A2). These findings of high OXPHOS but low glycolysis in resistant PDXs is consistent with a previous study that also showed elevated OXPHOS and decreased glycolysis in a residual TNBC PDX tumor post adriamycin / cyclophosphamide chemotherapy treatment that was generated from a treatment- naive TNBC patient. In addition, mitochondrial gene expression and protein synthesis were among the top pathways enriched in resistant PDXs, as was OXPHOS, which may be fueled by an increase in respiratory chain complex components (FIGS. 7A1-7A2).

[0152] The finding that OXPHOS may also interfere with optimal response to combination treatment (FIG. 6D) is in line with a recent study where transcriptomic profiling of TNBC tumors prior to sequential taxane and anthracycline-based neoadjuvant therapy associated an OXPHOS signature with greater risk of recurrence and also observed that pharmacological targeting of OXPHOS suppressed tumor growth of many PDX models generated from patients with residual tumors. This also aligns with other studies that implicate divergent effects of platinum vs taxane agents on mitochondrial metabolism and demonstrate distinct effects of platinum plus taxane combination vs single agents on mitochondrial structure. The contribution of OXPHOS may therefore be critical to identify tumors insensitive to chemotherapy and / or used in treatment decisions for combination carboplatin + docetaxel and deserves further study.

[0153] Applicant found a substantial overlap of genes associated with drug responses in tumors from PDXs and clinical trials (FIGS. 3D-3F) and also found groups of genes predictive of chemotherapy response (FIGS. 4A-4K). Similarities between PDX models and patients were also highlighted in Applicant’s previous study that showed highly concordant drug responses between PDX and patient-of-origin, especially for taxanes. Lastly, Applicant’s study investigated tumor responses after four cycles of chemotherapy similar to evaluating patient responses to neoadjuvant chemotherapy.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002

[0154] In conclusion, Applicant’s proteogenomic characterization identifies candidate molecular mechanisms underlying response and resistance, as well as putative predictive biomarkers for stratifying TNBC tumors for single or combination chemotherapy treatments. These results also support evaluation of rationally selected targeted agents and rationally selected PDX most likely to respond to such agents (or not) that may augment chemotherapy response to a meaningful extent, and provide a valuable resource for researchers and clinicians.

[0155] Without further elaboration, it is believed that one skilled in the art can, using the description herein, utilize the present disclosure to its fullest extent. The embodiments described herein are to be construed as illustrative and not as constraining the remainder of the disclosure in any way whatsoever. While the embodiments have been shown and described, many variations and modifications thereof can be made by one skilled in the art without departing from the spirit and teachings of the invention. Accordingly, the scope of protection is not limited by the description set out above, but is only limited by the claims, including all equivalents of the subject matter of the claims. The disclosures of all patents, patent applications and publications cited herein are hereby incorporated herein by reference, to the extent that they provide procedural or other details consistent with and supplementary to those set forth herein.

Claims

1. PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002CLAIMS1. A method of assessing the treatment outcome of a subject suffering from triple negative breast cancer, said method comprising: receiving measured biomarkers from the subject, wherein the biomarkers are selected from the group consisting of PRKX, TMEM135, MRPL32, VASH1, PTBP2, RAB1B, NCOA2, SLC25A35, COMMD7, CDC25A, CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, NCAPG, LGALS1, GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11. KIF2C, CDK19, LGALS3BP, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469, SUV39H1, TP53INP2, LCAT, THEM6, IRS2, ARL4D, STUB1, ITM2B, HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1, CCDC91, IPO5, SUMF1, KRT5, ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, TULP3, TSSC4. ARMC7, FANCI, TRPV4, NDUFA2, USP49, SSX2IP, C3orf38, KNK2, SLC39A4, MFSD3, TSTA3, AEBP1 , MYH10, PRSS8, LAD1 , PKP3, LRP6, RGMA, ZNF462, COL27A1, APEH, BTG2, DEGS1, EBPL, EIF2D, FAM174A, FUT3, GALE, GNPNAT1, HIBCH, LAP3, LRRC8E, METTLl, PGD, PSCA, RNASEH2C, SPRYD7, GLTP, ENDOD1, AQP1, ARHGAP33, ASAP2, ATAD2B, ATAD5, BICD1, CDH24, CHICI, CNOT4, CNTLN, DEK, DMC1, DMXL2, EFNB3, EZH2, FAM168A, FIZ1, FOXN3, GPR19, GXYLT1, HAUS5, HELLS, HES6, IRF2BPL, ITPKB. KLHL25. MSANTD2. N4BP2L1, PDE4DIP, PLEKHG2, POLH, PPM1D, PRKAB2, SLC4A7, SMC6, SOWAHC, STARD13, TM2D3, TRAM1L1, USP1, UTRN, WHAMM, ZNF160, ZNF184, ZNF212. ZNF367, ZNF566, ZNF573. ZNF620, ZNF654, ZSCAN5A, BYSL, USP37, EXO5, HIC2, ZNF197, BCAR1, METRN, ZDHHC7, SLC22A18, PLXND1, SGCE, ATP7B, PHLDA3, CMBL, ALDH1A1, ASF1A, ECHDC1, ZNF100, ZNF493, ZNF85, KCNF1, KCTD17, PCOLCE2. DNAJC24, SAV1, TMEM126B, POGZ, SRSF7, TMPO, POLE, FAM83H, RPL8, ATP8B2, Clorfll6, AKAP7, SIMC1, FGD1, DHRS7, HIBADH, LRTOMT, NTN4, PFKFB2, SNX13, TAX1BP1, ZBTB3, CCDC61, TSPAN31, TMEM150A, ADCY1, ARRB2, ASH1L, CLK2, CPSF6. DNA2, DNAJC9, GPR63. HACE1. HYI, KCTD15. LYSMD1. MRPL9, PRPF3, RPRD2, TOE1, UCK1, ZNF189, ZNF510, ZNF740, ZWINT, GOPC, TRIP13, RHOBTB1, SPAG5, SRRD, NCOA7, STIL, COPS3, HSPA13, DONSON, CCDC117, CHAF1A, SUZ12, WNK3, TK2, PPP2R3A, ZNF17, SMAD4, MCOLN2, MSI1, FCHSD2, C2CD3, MAD2L1, TPBG, SRRT,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002MEX3C, PTK6, ZNF22, MDM1, SAR1B, VPS28, FOXM1. CAP2. FAM126A, MRPL2, MRPS10, MTHFSD, OAZ2, RAB3IL1, SLC25A17, SLC29A1, SNAP29, SPRTN, TM9SF4, TPMT, YWHAH, ZNF75A, ZYX, SPATA7, TLE2, KLHL7, ZNF133, NR1H2, ISCA1, NDUFA3, EFNA5, ERLEC1, GPR157, RELL1, BLMH. HIVEP1, ARID1B. TCHP, BRAP, RFC5, EWSR1, ZMAT5. TCEA1, KLK5, RAB6B, FAXC, RPS12, STX7, BCL2L10, GOLGA8A, FGF11, IL18R1, ANKRD6, ZNF483, EPHX4, FBN3, OVOL2, PCDH1, ANGPTL4, QSOX1, INPP5A, ADCY9, Cllorf24, RIN2, RAB2A, BCKDK, ABCC2, NAA60, HDLBP, SPARC, MGRN1, TRIOBP, TGM2, SERINC5, PMM2, POR, GMPPA, GNAI1, RAB11FIP5, FLYWCH1, FARP2, SYNC, TMEM214, STRN3, SFXN3, CERCAM, SEMA4B, USP40, TRPC4AP, ABLIM3, COMT, ZHX3, UBN1, ENG, HHLA3, YBX2, FITM2, PLCB3, ANKS3, WNT9A, MPP2, PGBD1, CCDC17, CC2D2A, EPM2A, ICA1L, KANSL1L, LRP2BP, LYPD1, MAP2, MYOID, NHSL1, PGAP1, PLEKHM3, PYGB, RSPH3, ZBTB44, ZNF431, ZNF708, PDSS2, AKIRIN2, SYNCRIP, FAM221A, MDK, CD83, RNGTT, JPH2, KIAA0556, MSRB3, SAMD9L, DHX38, ZNF81, PTTG1, SP110, IFIT1, DDX60, XAF1, IFI44, OAS2, GBP4, STAT1, ACTG2, KRT6B, AZGP1, ZG16B, STAC2, KLK7, KRT15. CDKN2A, IFI27. COL5A2. PXDN, ACTA2, TF, NTRK2, AGT, S100A1, CRYAB, EDN2, PCP4L1, ANGPT1, PTX3, INHBB, TIMP3, SIX1, RERG, FKBP10, SMOC2, COL6A2, SNAI2, COL8A1, PXDNL. CASP14, SOD3, PIK3C2G, PCOLCE, NMU, PI15, TACSTD2, BGN, SYNM, SLITRK6, MMP2, PRELP, ADM, TBX1, IGFBP5, BATF2, AKR1C1, IFITM1, C15orf48, FBXO2, ASPHD1, RCN3, TAGLN, MXRA8, MX2, AKR1C3, PPP1R3C, FN1, XYLT1, IL32, TPM2, MYL9, NDUFA4L2. SKAP1, TMEM47. ADCY2, GPRC5C, KIAA1549L, SMARCA1, IFIT2, DHX58, SEMA3C, SCUBE2, COL17A1, MFGE8, RTN4RL1, SRPX, NR2F1, ATP13A5, NDRG1, GXYLT2, TNC, KCNK5, GAS6, ARSJ, MAOA, SLC24A3, FHOD3, FST, DDIT4L, OSR1. CCND1, SERPINE2. SUSD2. GPT, MALL, SCUBE3, OAS1, CA12, COL7A1, EGLN3, SLC6A17, LAMB1, SCN4B, ESRRG, RBI, FAM83A, DDR2, ANKRD22, COPZ2, DAPP1, A4GALT, OPRK1, KLHL13, CNTNL MYLK, BMPR1B, RGS11, CITED4, LAG3, SCNN1B, NDP. TSPYL5, PID1. ALDH3B2, ADORAL GLB1L2, SORBS2, B4GALNT2. LCK, MEGF10, IGFBP3, STC1, TMEM200B, LOXL2, APLN, DKK3, PKDCC, TLR3, FGFR1, CAV1, FAT4, VIM, ZNF365, CADM1, ATP13A4, RAB3B, NFIA, TACR1, NRP1, FSTL4, LYPD3, AKR1E2, BOC, KCNMB4, FNDC4, LAMA4, ETV7, NGEF, SUSD3, EFR3B, MMP15, VSIG10L, MATN3, ENPP3, EFCAB6, SH3RF2, GHR, PMP22, LOX, SORCS2, RDH10, C1QTNF2,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002SCNN1G, RNF165, SDC2, SLC12A2, INHBA, SLC13A3, PLCB1, CX3CL1, HYDIN. GLT8D2, RNF43, FEZ1, RNF152, MPV17L, ANO1, CDK6, CILP2, PDGFD, HOXC11, EPHB3, DDX58, PLTP, SERPINE1, SLC2A10, KHDRBS3, TRIM9, CORO1A, B3GALT5, EVA1A, PDE6B, GPR176, EFEMP2, NPR2, GLRB. CTF1, CD8A, PMAIP1, ALDOC, PDGFA, TGFB2, LIMS2, FBLN7, TPST1, EMP1, UBASH3B, ADAMTS15, ISG20, SHOX2, VWDE, PROCR, HSH2D, CLCN4, FAM189A2, MAP1B, NOX5, GPC1, TBX3, PRSS27, GYG2, FAM83F, F3. PGF, PRSS23, ITGA5, COL18A1, SHANK2, SHANK3, ATP1B1, RASGRP3, PTGES, FRY, NOTUM, EID1, SLC27A2, WBP2NL, JAG1, PRRT2, RNF180, SCD5, PLLP, BEAN1, FERMT2, TPPP3, FUT9, ASRGL1, NPTXR, HCST, MPZL2, C6orfl41, PLK2, EFHC2, COL16A1, ADORA2B. FBLN1, ZNF501, CACNA1D, AFAP1L1, ATP8A1, DOC2A, MMEL1, CD6, ARHGEF25, PCSK6, SPATA6, TLR1, L3MBTL1, ADHFE1, GPX8, CES4A, TRPC1, CNIH3, MCAM, PCDHB13, ROR1, MEIS3, SNTB1, AK7, AHRR. NDRG4, GPR39. IGFBP6, SERTAD4. SPTBN5, NQO1, IL20RB, INHA, ZNF471, PNCK, ADAM12, MAPK15, MAML3, SHROOM2, CROT, RHOBTB3, SEC14L5, SGSM1, DUSP5, TNFRSF11A, MEGF6, NKD1, C1QTNF6, USP18, DMGDH, EPS8, EML1, MRAS, PNPLA7. ANKRD34A. PDGFC. VEGFA, FZD4, LAMA3, PDK3, EPAS1, CDH26, THRB, BRSK1, RIBC2, HSPG2, EGFR, GGT7, MYOMI, PPP1R36, HAS3, PDGFB, WNT2B, PPFIA4, HOXC13, CHST3, STM, THBS1, FIGN, HLX, GAL3ST4, RFTN1, Clorfll5, HSPA12A, SLC29A4, RPS6KA2, PHLDB2, PNPLA4, CDHR3, ST3GAL4, ITGB5, CRIP2, ULBP1, PTPRG, ZNF717, SCN1B, SH3RF3, ADAMTS1, PKD1L1, ATP2A1, ACOT4, SLC22A17, MAML2, CYBRD1, ZBTB20, CENPW, ARHGAP5, ARHGEF17, BCO2, C14orf28, CACNB1, CD59, CDIPT, CES2, CNNM2, CTNNAL1, CTSS, ENGASE, GLIS2, HM13, JMJD8, KLHL26, L3MBTL2, MORN4, NR4A1, PLOD3, RNF40, SIDT2, SLC25A42, SLC39A13, SOCS5, TBC1D20, TECPR2, TMEM184B, TTC23. WWP2, ARTN. CADM4, CARD14, CNBD2, DBNDD1, ENPP4, EPB41L5, EXD3, FHL2, KIFC3, KRT83, PLA2R1, PRR3, SIAE, SLC12A8, TBC1D7, TMEM217, TOMI, TRNP1, TXNRD2, VLDLR, ZDHHC1, PGBD5, ANK2, SRPX2, MAP1A. COL1A1, SLC2A12. SLC6A11. ADAMTS12. CCDC80, COL14A1, COL1A2. COL3A1. COL5A1, COL6A3, EXOG, INPP4B, KLF6, LDLR, MAST4, MTMR11, OLFML2A, PDE4A, PHKG1, RARB, UTP23, MAT2B, SET. TPM3, ARMCX3, DECR1, DYSF, EXOCI, STAM2, KDELR2, AP1B1, VRK3, INTS8, PRRC1, PDE6D, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, ACBD5, AIG1, DTWD1, ELP2, PAQR6, PIK3C3, RARS2, SF3B5, SHPRH, ZC3HAV1L, ORC1,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002EIF4A3, CSRP2, NUP85. CEBPB, MOB3B, MCM3, NCAPH2, ERI1, CDCA7. PRKAB1. NUP210, POP5, TNFAIP2, PARD6A, RHEBL1, FBL, MFHAS1, PRIM1, PINX1, C12orf43, PCBP2, CHAF1B, E2F7, MED12L, DDX23, WDR76, MCM2, HAUS1, IFI44L, DNAJC3, DSTYK, KPNA3, PEX2, SLC35B3. STX12, SUGT1, TMEM106B, TWISTNB. UBE2W, VPS36. ZNF12, ZNF623, NFKB2, NUP37, RELB, GOLGA5, DUSP18, EHBP1L1, TRIP11, FOXRED2, ZNF70, PES1, D2HGDH. RNF185, MORC2, MPV17, HSCB, ATP6V0E1, EHD1, PHF20, SERINC3, FLVCR2, HPS4, VPS37C, RBKS, PRKCD, JKAMP, ANKRD46, ATP6AP1L, BTBD3, C2orf76, CLHC1, COA5, CRCP, DBT, DCUN1D4, DHRS12, DPH5, DPY19L4, DYNC1LI2, EFNA3, INTS6, KIF3A, KRIT1, LAMTOR3, MFF, NEURL2, PCGF3, PEX6, PSTK, RAB11FIP2, RAD50, SAR1A, SENP8, SMARCAD1, TIGD6, TMEM67, WDPCP, ZKSCAN1, ZRANB1, GPHN, MACROD2, YLPM1, UNC119B, ZNF787, ZNF287, APOLD1, MEST, TNKS, RUVBL2, UBR7, COX14, PPP3CC. RARRES1, CCAR1, IGF2BP2, AKAP5, LXN, ACP2, ALAS1, ANKRD33B, ANXA11, C1R, CC2D1B, CD274, CYTH1, DRAM1, EGLN2, ELF4, FBXO6, GRB2, IFIH1, IKBKG, IL18BP, JMJD6, KLHDC7B, LAMP3, MX1, MYD88, OAS3, OASL, PARP12. PIK3CD, RAB35, RBM42, REC8, RNF213. RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM14, PTGER4, PPM1A, RBFOX2, BRWD1, IRF1, FEN1, TOMM40, PARPBP, AURKB. AURKA, BTN3A3, PLSCR1, IRF9 , UBE2L6, GBP1, BST2, PARP14, SP100, B2M, SAMD9, IFI6, PSMB9, IFIT3, HERC5, ISG15, RSAD2, PSME1, PSMB10, IFI35, PARP9, HERC6, NMI, GLI4, ZNF696, ZNF517, ARHGEF37, GRHL2, SPINT2, ACO2, CLTCL1, CXCL14, GDF9, HECTD1, HMGXB4, MAPK1 , MPP6, NAA30, NR3C2, PHF7, PIGH, PLA2G6, POLI, PPARGC1 A, RHBDD3, RNF215, SLC23A2, SLC30A9, TTLL1, WIPF2, ZFP28, ARMC10, PTCD3, PUM2, RABGGTB, SRSF11, ZNF644, DZANK1. ACPI. E2F6, TXLNB, ATP6V0A4, LTF, ARPC1B, CYBA, DDX60L, or combinations thereof; and correlating differentially expressed levels of the biomarkers to a treatment outcome.

2. The method of claim 1, wherein the treatment outcome is determined by tumor shrinkage.

3. The method of claim 1, wherein the treatment outcome is determined by a likelihood of a successPCT Application Attorney Docket No. AF44111.P046WOBLG 22-002 of a treatment plan.

4. The method of claim 3, wherein the treatment plan is selected from the group consisting of treatment through chemotherapeutic agents, carboplatin, cisplatin, taxane chemotherapeutic agents, docetaxel, paclitaxel, or combinations thereof.

5. The method of claim 1, wherein the measured biomarkers are selected from the group consisting of PRKX, TMEM135, MRPL32, VASH1, PTBP2, RAB1B, NCOA2, SLC25A35, COMMD7, CDC25A, CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, NCAPG, LGALS1. GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11, KIF2C, CDK19, LGALS3BP, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469, SUV39H1, TP53INP2, LCAT, THEM6, IRS2, ARL4D, STUB1, ITM2B, HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1. CCDC91, IPO5, SUMF1, KRT5, or combinations thereof.

6. The method of claim 1, wherein the measured biomarkers comprise PRKX, TMEM135, MRPL32, VASH1, PTBP2, RAB1B, NCOA2, SLC25A35, COMMD7, and CDC25A; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered as a single agent.

7. The method of claim 1 , wherein the measured biomarkers comprise one or more of the following measured biomarkers:ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, or combinations thereof;TULP3, TSSC4. ARMC7, FANCI, TRPV4. NDUFA2, USP49, SSX2IP. C3orf38, KNK2, or combinations thereof;SLC39A4, MFSD3, TSTA3, AEBP1, TGFB1I1, RAB9B, MYH10, PRSS8, LAD1, PKP3,LRP6, RGMA, ZNF462, COL27A1, or combinations thereof;APEH, BTG2, DEGS1, EBPL, EIF2D, ESRRA, FAM174A, FUT3, GALE, GNPNAT1,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002HIBCH, ITM2B, LAP3, LRRC8E, METTL1, PGD, PSCA, RNASEH2C, SLC39A4, SPRYD7, TSTA3, GLTP, ENDOD1, AEBP1, AQP1, ARHGAP33, ASAP2, ATAD2B, ATAD5, BICD1, CDH24, CHICI, CNOT4, CNTLN, DEK, DMC1, DMXL2, EFNB3, EZH2, FAM168A, FIZ1, FOXN3, GPR19, GXYLT1, HAUS5, HELLS, HES6, IRF2BPL, ITPKB. KLHL25, MSANTD2, N4BP2L1, PDE4DIP, PLEKHG2, POLH, POTI, PPM ID, PRKAB2, SLC4A7, SMC6, SOWAHC, STARD13, TM2D3, TMEM98, TRAM1L1, USP1, UTRN, WHAMM, ZFP37, ZNF160, ZNF184, ZNF212, ZNF367, ZNF566, ZNF573, ZNF620, ZNF654, ZSCAN5A, BYSL, USP37, EXO5, HIC2, ZNF197, or combinations thereof;ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, TULP3, TSSC4, ARMC7, FANCI, TRPV4, NDUFA2, USP49, SSX2IP, C3orf38, KNK2, SLC39A4, MFSD3, TSTA3, AEBP1, MYH10, PRSS8, LAD1, PKP3, LRP6, RGMA. ZNF462, COL27A1, APEH. BTG2, DEGSL EBPL, EIF2D, FAM174A, FUT3, GALE, GNPNAT1, HIBCH, ITM2B, LAP3, LRRC8E, METTL1, PGD, PSCA, RNASEH2C, SPRYD7, GLTP, ENDOD1, AQP1, ARHGAP33, ASAP2, ATAD2B, ATAD5, BICD1, CDH24, CHICI. CNOT4. CNTLN, DEK, DMCL DMXL2, EFNB3, EZH2, FAM168A, FIZ1, FOXN3, GPR19, GXYLT1, HAUS5, HELLS, HES6, IRF2BPL, ITPKB, KLHL25, MSANTD2, N4BP2L1, PDE4DIP, PLEKHG2, POLH, PPM ID, PRKAB2, SLC4A7, SMC6, SOWAHC, STARD13, TM2D3, TRAM1L1, USP1, UTRN, WHAMM, ZNF160, ZNF184, ZNF212, ZNF367, ZNF566, ZNF573, ZNF620, ZNF654, ZSCAN5A, BYSL, USP37, EXO5, HIC2, ZNF197, or combinations thereof; or combinations thereof; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered as a single agent.

8. The method of claim 1, wherein the measured biomarkers comprise one or more of the following measured biomarkers:PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, or combinations thereof;POGZ, COMMD7, SRSF7, TMPO, POLE, or combinations thereof;MFSD3, FAM83H, RPL8, ATP8B2, AEBP1. Clorfll6. AKAP7. SIMC1, MYH10. FGD1, or combinations thereof;DHRS7, HIBADH, LRTOMT, NTN4, PFKFB2, SNX13, TAX1BP1, ZBTB3, CCDC61, TSPAN31, TMEM150A, ADCY1, ARRB2, ASH1L, CLK2, CPSF6, DNA2, DNAJC9, EZH2, GPR63, HACE1, HYI, KCTD15, LYSMD1, MRPL9, PRPF3, RPRD2, SIMC1, TOE1, UCK1, ZNF189, ZNF510. ZNF740, ZWINT, GOPC, TRIP13, RHOBTB1, SPAG5, TULP3, SRRD, NCOA7, STIL, COPS3, HSPA13, DONSON, CCDC117, CHAF1A, HIC2, ATAD5, SUZ12, WNK3, or combinations thereof;ACSS2, ESRRA, CCL5, POTI, ZFP37, ZNF256, ZNF394, SPICE1, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, POGZ, COMMD7, SRSF7, TMPO, POLE, MFSD3, FAM83H, RPL8, ATP8B2, AEBP1, Clorfll6, AKAP7, SIMC1, MYH10, FGD1, DHRS7, HIBADH, LRTOMT, NTN4. PFKFB2, SNX13, TAX1BP1. ZBTB3, CCDC61, TSPAN31. TMEM150A, ADCY1, ARRB2, ASH1L, CLK2, CPSF6, DNA2, DNAJC9, EZH2, GPR63, HACE1, HYI, KCTD15, LYSMD1, MRPL9, PRPF3, RPRD2, TOE1, UCK1, ZNF189, ZNF510, ZNF740, ZWINT, GOPC, TRIP13, RHOBTB1, SPAG5, TULP3, SRRD, NCOA7, STIL, COPS3, HSPA13, DONSON, CCDC117, CHAF1A, HIC2, ATAD5, SUZ12, WNK3, or combinations thereof;TK2, ACSS2, ESRRA, CCL5, PPP2R3A, POTI, ZFP37, ZNF256, ZNF394. SPICEL ZNF17, CUL4A, PIK3CA, SMAD4, TMEM98, TOP3A, BRIP1, MCOLN2, MSH6, RND2, RAB9B, CNTLN, TGFB1I1, MSI1, FCHSD2, C2CD3, or combinations thereof;MAD2L1, TPBG, SRRT. MEX3C, PTK6, ZNF22, MDM1, SAR1B, or combinations thereof;VPS28, FOXM1, or combinations thereof;CAP2, DHRS7, FAM126A, HIBADH, LRTOMT, MRPL2. MRPS10, MTHFSD, NTN4. OAZ2, PFKFB2, RAB3IL1, SLC25A17, SLC29A1, SNAP29, SNX13, SPRTN, TAX1BP1, TM9SF4, TPMT, YWHAH, ZBTB3, ZNF75A, ZYX, SPATA7. TLE2, CCDC61, KLHL7, ZNF133, NR1H2, ISCA1, TSPAN31, TK2, TMEM150A, NDUFA3, EFNA5, ZNF17, ERLEC1, GPR157, MFSD3, RELL1, BLMH, SPAG5, LYSMD1, HIVEP1, SIMC1, ZNF510, PRPF3, MCOLN2,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002ARID1B. RPRD2. ATAD5, ARRB2, ADCY1, CNTLN, ZNF740. TCHP, MSI1, EZH2, DNA2, HACE1, BRAP, RFC5, RHOBTB1, TULP3, GPR63, TOE1, DONSON, HIC2, EWSR1, ASH1L, TRIP13, CCDC117, ZNF189, ZWINT, or combinations thereof;TK2. ACSS2, ESRRA. CCL5. PPP2R3A, POTI, ZFP37, ZNF256. ZNF394, SPICE1, ZNF17. CUL4A, PIK3CA, SMAD4, TMEM98, TOP3A, BRIP1, MCOLN2, MSH6, RND2, RAB9B, CNTLN, TGFB1I1, MSI1, FCHSD2, C2CD3, MAD2L1, TPBG, SRRT, MEX3C, PTK6, ZNF22, MDM1, SAR1B, VPS28, FOXM1, CAP2, DHRS7, FAM126A, HIBADH, LRTOMT, MRPL2, MRPS10, MTHFSD, NTN4, OAZ2, PFKFB2, RAB3IL1, SLC25A17, SLC29A1, SNAP29, SNX13, SPRTN, TAX1BP1, TM9SF4, TPMT, YWHAH, ZBTB3, ZNF75A, ZYX, SPATA7, TLE2, CCDC61, KLHL7, ZNF133, NR1H2, ISCA1, TSPAN31, TMEM150A, NDUFA3, EFNA5, ERLEC1, GPR157, MFSD3, RELL1, BLMH, SPAG5, LYSMD1, HIVEP1, SIMC1, ZNF510, PRPF3. ARID1B, RPRD2, ATAD5, ARRB2, ADCY1, ZNF740, TCHP, EZH2, DNA2. HACE1, BRAP, RFC5, RHOBTB1, TULP3, GPR63, TOE1, DONSON, HIC2, EWSR1, ASH1L, TRIP13, CCDC117, ZNF189, ZWINT, or combinations thereof; or combinations thereof; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered as a single agent.

9. The method of claim 1, wherein the measured biomarkers comprise LCAT, THEM6, IRS2, ARL4D, STUB1, and ITM2B; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents administered as a single agent.

10. The method of claim 1, wherein the measured biomarkers comprise CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, and NCAPG; andPCT Application Attorney Docket No. AF44111.P046WOBLG 22-002 wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by taxane chemotherapeutic agents administered as a single agent.

11. The method of claim 1, wherein the measured biomarkers comprise HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1, CCDC91, IPO5, and SUMF1; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by taxane chemotherapeutic agents administered as a single agent.

12. The method of claim 1, wherein the measured biomarkers comprise one or more of the following measured biomarkers:BCAR1, METRN, ZDHHC7, SLC22A18, PLXND1, SGCE, ATP7B, PHLDA3, CMBL, ALDH1A1, ASF1A, ECHDC1, or combinations thereof;HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1, CCDC91, IPO5, SUMF1, or combinations thereof;ZNF100, ZNF493, ZNF85, or combinations thereof;KCNF1, KCTD17, PCOLCE2, PLXND1, DNAJC24, ECHDC1, SAV1, TMEM126B, or combinations thereof;BCAR1, METRN. ZDHHC7, SLC22A18, PLXND1. SGCE, ATP7B, PHLDA3. CMBL, ALDH1 Al , ASF1 A, ECHDC1 , HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1 , CCDC91 , IPO5, SUMF1, ZNF100, ZNF493, ZNF85, KCNF1, KCTD17, PCOLCE2, DNAJC24, SAV1, TMEM126B, or combinations thereof; or combinations thereof; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by taxane chemotherapeutic agents administered as a single agent.

13. The method of claim 1,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002 wherein the measured biomarkers comprise one or more of the following measured biomarkers:ZMAT5, TCEA1, KLK5, RAB6B, FAXC, RPS12, STX7, BCL2L10, GOLGA8A, FGF11, IL18R1, ANKRD6, ZNF483. EPHX4. FBN3. or combinations thereof;CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, NCAPG, or combinations thereof;OVOL2, PCDH1, or combinations thereof;ANGPTL4, QSOX1, STX7, or combinations thereof;ZMAT5, TCEA1, KLK5, RAB6B, FAXC, RPS12, STX7, BCL2L10, GOLGA8A, FGF11, IL18R1, ANKRD6, ZNF483, EPHX4, FBN3, CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, NCAPG, OVOL2, PCDH1, ANGPTL4, QSOX1, or combinations thereof;INPP5A, ADCY9, BCAR1, METRN, Cllorf24, RIN2, RAB2A, BCKDK, ABCC2, NAA60, HDLBP, ZMAT5, SPARC, MGRN1, TRIOBP. TGM2, SERINC5, TCEA1, PMM2, POR, GMPPA, GNAI1, RAB11FIP5, FLYWCH1, FARP2, SPRYD7, SYNC, TMEM214, STRN3, SFXN3, CERCAM, SEMA4B, USP40, ATP7B, TRPC4AP, ABLIM3, COMT, ZHX3, UBN1, ENG, HHLA3, YBX2. FITM2, PLCB3, ANKS3, CMBL. WNT9A, MPP2, ANKRD6. BCL2L10, EPHX4. FAXC, FBN3, FGF11, GOLGA8A, KLK5, RAB6B, PGBD1, CCDC17, CC2D2A, EPM2A, ICA1L, KANSL1L, LRP2BP, LYPD1, MAP2, MYOID, NCOA7, NHSL1, PGAP1, PLEKHM3, PYGB, RSPH3, ZBTB44, ZNF431, ZNF708, RPS12, PDSS2, AKIRIN2, STX7, SYNCRIP, FAM221A, MDK, CD83, RNGTT, IL18R1, ZNF483, or combinations thereof;JPH2, KIAA0556. NCAPG, MSRB3, SAMD9L, DHX38, ZNF81, PTTG1, or combinations thereof;SP110, IFIT1, DDX60, XAF1, IFI44, OAS2, SAMD9L, GBP4, STAT1, ACTG2, KRT6B, AZGP1, ZG16B, STAC2. KLK7, KRT15. CDKN2A, IFI27. SPARC. COL5A2, PXDN, ACTA2, TF, NTRK2, AGT, S100A1, CRYAB, EDN2, PCP4L1, ANGPT1, PTX3, ANGPTL4, INHBB, TIMP3, SIX1, RERG, FKBP10, SMOC2, COL6A2, SNAI2, COL8A1, PXDNL, CASP14, SOD3, PIK3C2G, PCOLCE, NMU, PI15, TACSTD2, BGN. SYNM, SLITRK6. MMP2, PRELP, ADM. TBX1, IGFBP5, BATF2, AKR1C1, IFITM1, C15orf48, FBXO2, ASPHD1, RCN3, TAGLN, MXRA8, MX2, AKR1C3, PPP1R3C, FN1, XYLT1, IL32, TPM2, MYL9, NDUFA4L2, SKAP1, TMEM47, MSRB3, ADCY2, GPRC5C, KIAA1549L, SMARCA1, IFIT2, DHX58, SEMA3C, SCUBE2, COL17A1, MFGE8, RTN4RL1, SRPX, NR2F1, ATP13A5, NDRG1, GXYLT2, TNC,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002KCNK5, GAS6, ARSJ, MAOA, SLC24A3, FHOD3, FST, DDIT4L, OSR1, CCND1, SERPINE2, SUSD2, GPT, MALL, SCUBE3, OAS1, CA12, COL7A1, EGLN3, SLC6A17, METRN, LAMB1, SCN4B, ESRRG, RBI, FAM83A, DDR2, ANKRD22, COPZ2, DAPP1, A4GALT, TLE2, OPRK1, KLHL13, PRSS8, CNTN1, MYLK, BMPR1B, RGS11, CITED4, LAG3. ZNF469, SCNN1B, NDP, TSPYL5, PID1, ALDH3B2, ADORA1, GLB1L2, SORBS2, B4GALNT2, LCK, MEGF10, TGFB1I1, IGFBP3, STC1, TMEM200B, LOXL2, APLN, DKK3, PKDCC, TLR3, FGFR1, CAV1, FAT4, VIM, ZNF365, CADM1, ATP13A4, RAB3B, TGM2, NFIA, TACR1, NRP1, FSTL4, LYPD3, AKR1E2, BOG, KCNMB4, FNDC4, LAMA4, ETV7, NGEF, SUSD3, EFR3B, MMP15, VSIG10L, MATN3, ENPP3, EFCAB6, SH3RF2, CMBL, GHR. PMP22, LOX, SORCS2, RDH10, C1QTNF2, SCNN1G, RNF165, SDC2, SLC12A2, INHBA, SLC13A3, PLCB1, CX3CL1, HYDIN, GLT8D2, MDK, RNF43, FEZ1, RNF152, MPV17L, ANO1, CDK6, CILP2, JPH2, PDGFD, HOXC11, EPHB3, DDX58, PLTP, SERPINE1. SLC2A10, KHDRBS3, TRIM9. NTN4, CORO1A, B3GALT5, EVA1A, PDE6B, GPR176, EFEMP2, NPR2, GLRB, DMC1, CTF1, CD8A, PMAIP1, ALDOC, PDGFA, TGFB2, LIMS2, FBLN7, TPST1, EMP1, UBASH3B. ADAMTS15, ISG20, ECHDC1, LYPD1, SHOX2, VWDE, PROCR, HSH2D, CLCN4, FAM189A2. MAP1B, NOX5, GPC1, TBX3, PRSS27, GYG2, FAM83F, F3, PGF, PRSS23, ITGA5, COL18A1, SHANK2, SHANK3, ATP1B1. RASGRP3, PTGES, SGCE, FRY, NOTUM, ENG, EIDL SLC27A2, WBP2NL, JAG1, PRRT2, RNF180, SCD5, PLLP, BEAN1, FERMT2, TPPP3, FUT9, ASRGL1, NPTXR, HCST, MPZL2, C6orfl41, PLK2, EFHC2, COL16A1, ADORA2B, FBLN1, ZNF501, CACNA1D, AFAP1L1, ATP8A1, DOC2A, MMEL1, CD6, ARHGEF25, PCSK6, SPATA6, TLR1, L3MBTL1 , ADHFE1, GPX8, ABLTM3, CES4A, TRPC1, CNIH3, MCAM, PCDHB13, ROR1 , MEIS3, SNTB1, AK7, AHRR, ABCC2, NDRG4, GPR39, IGFBP6, SERTAD4, SPTBN5, NQO1, IL20RB, INHA, ZNF471. PNCK, ADAM12, MAPK15, MAML3, SHROOM2, FAM221A, CROT, RHOBTB3, SEC14L5, SGSM1, DUSP5, TNFRSF11A, MAP2, MEGF6, NKD1, C1QTNF6, USP18, DMGDH, EPS8, EML1, MRAS, PNPLA7, ANKRD34A, PDGFC, VEGFA, FZD4, LAMA3. CD83. PDK3. EPAS1, CDH26, THRB. BRSK1. RIBC2, HSPG2, EGFR, GGT7, MYOM1, PPP1R36, HAS3, PDGFB, WNT2B, PPFIA4, HOXC13, CHST3, STU, THBS1, FIGN, HLX, GAL3ST4, RFTN1, Clorfll5, HSPA12A, SLC29A4, RPS6KA2, PHLDB2, PNPLA4. CDHR3, ST3GAL4, ITGB5, CRIP2, ULBP1, PTPRG, ZNF717, SCN1B, SH3RF3, ADAMTS1, PKD1L1, ATP2A1, ACOT4, SLC22A17, MAML2, CYBRD1, ZBTB20, CENPW, LGALS1, orPCT Application Attorney Docket No. AF44111.P046WOBLG 22-002 combinations thereof;ADCY9, ANGPTL4, ANKS3, ARHGAP5, ARHGEF17, ATP7B, BCAR1, BCO2, C14orf28, CACNB1, CD59, CDIPT, CES2, CMBL, CNNM2, COPZ2, CTNNAL1, CTSS, DDR2, ENGASE, EPAS1, FGFR1. FLYWCH1, GHR, GLIS2, GMPPA, GNAI1, HM13, JMJD8, KLHL26. L3MBTL2, MAOA, MORN4, NR4A1, NTRK2, PCSK6, PLOD3, PPP1R3C, QSOX1, RNF40, SHANK2, SIDT2, SLC25A42, SLC39A13, SOCS5, TBC1D20, TECPR2, TIMP3, TMEM184B, TMEM214, TTC23, USP40, WWP2, ZNF81, ADCY2, ADM, ANKRD6, ARTN, CADM4, CARD14, CNBD2, CRIP2, DBNDD1, EMP1, ENPP4, EPB41L5, EXD3, FAM189A2, FBN3, FGF11, FHL2, FSTL4, GPC1, JPH2, KIFC3, KLK5, KRT83, MFGE8, NDRG1, PLA2R1, PPFIA4, PRR3, PRSS27, PXDN, RNF180, SCNN1G, SIAE, SLC12A8, SLC24A3, SLC6A17, STC1, TBC1D7, TLE2, TMEM217, TOMI, TRNP1, TXNRD2, VEGFA, VLDLR, ZDHHC1, ZNF469, ZNF717, PGBD5, ANK2, SRPX2, MAP1A, COL1A1. SLC2A12, SLC6A11, ADAMTS12, ATP8B2, CCDC80, COL14A1, COL1A2, COL3A1, COL5A1, COL6A3, EXOG, INPP4B, KLF6, LDLR, MAST4, MTMR11, OLFML2A, PDE4A, PHKG1, RARB, UTP23, UTRN, AKIRIN2, STX7, SYNCRIP. FAM221A, RNGTT, CD8A. MAT2B, SLC27A2, STAT1, SET, TPM3, or combinations thereof;INPP5A, ADCY9, BCAR1, METRN, Cllorf24, RIN2, RAB2A, BCKDK. ABCC2, NAA60, HDLBP, ZMAT5, SPARC, MGRN1, TRIOBP, TGM2, SERINC5, TCEA1, PMM2, POR, GMPPA, GNAI1, RAB11FIP5, FLYWCH1, FARP2, SPRYD7, SYNC, TMEM214, STRN3, SFXN3, CERCAM, SEMA4B. USP40, ATP7B, TRPC4AP. ABLIM3, COMT, ZHX3, UBN1, ENG, HHLA3, YBX2, FITM2, PLCB3, ANKS3, CMBL, WNT9A, MPP2, ANKRD6, BCL2L10, EPHX4, FAXC, FBN3, FGF11, GOLGA8A, KLK5, RAB6B, PGBD1, CCDC17, CC2D2A, EPM2A, ICA1L, KANSL1L, LRP2BP, LYPD1, MAP2. MYOID, NCOA7, NHSL1, PGAP1, PLEKHM3, PYGB. RSPH3, ZBTB44, ZNF431, ZNF708, RPS12, PDSS2, AKIRIN2, STX7, SYNCRIP, FAM221A, MDK, CD83, RNGTT, IL18R1, ZNF483, JPH2, KIAA0556, NCAPG, MSRB3, SAMD9L, DHX38, ZNF81. PTTG1. SP110, IFIT1. DDX60. XAF1, IFI44. OAS2. GBP4. STATE ACTG2. KRT6B. AZGP1, ZG16B, STAC2, KLK7, KRT15, CDKN2A, IFI27, COL5A2, PXDN, ACTA2, TF, NTRK2, AGT, S100A1, CRYAB, EDN2, PCP4L1, ANGPT1, PTX3. ANGPTL4, INHBB, TIMP3, SIX1, RERG, FKBP10, SMOC2, COL6A2, SNAI2, COL8A1, PXDNL, CASP14, SOD3, PIK3C2G, PCOLCE, NMU, PI15, TACSTD2, BGN, SYNM, SLITRK6, MMP2, PRELP, ADM, TBX1,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002IGFBP5, BATF2, AKR1C1, IFITM1, C15orf48, FBXO2, ASPHD1, RCN3, TAGLN, MXRA8, MX2, AKR1C3, PPP1R3C, FN1, XYLT1, IL32, TPM2, MYL9, NDUFA4L2, SKAP1, TMEM47, ADCY2, GPRC5C, KIAA1549L, SMARCA1, IFIT2, DHX58, SEMA3C, SCUBE2, COL17A1, MFGE8, RTN4RL1, SRPX, NR2F1. ATP13A5, NDRG1, GXYLT2, TNC. KCNK5, GAS6, ARSJ, MAOA, SLC24A3, FHOD3, FST, DDIT4L, OSR1, CCND1, SERPINE2, SUSD2, GPT, MALL, SCUBE3, OAS1, CA12, COL7A1, EGLN3, SLC6A17, LAMB1, SCN4B, ESRRG, RBI, FAM83A, DDR2, ANKRD22, COPZ2, DAPP1, A4GALT, TLE2, OPRK1, KLHL13, PRSS8, CNTN1, MYLK, BMPR1B, RGS11, CITED4, LAG3, ZNF469, SCNN1B, NDP, TSPYL5, PID1, ALDH3B2, ADORA1, GLB1L2, SORBS2. B4GALNT2, LCK. MEGF10, TGFB1I1, IGFBP3, STCL TMEM200B, LOXL2, APLN, DKK3, PKDCC, TLR3, FGFR1, CAV1, FAT4, VIM, ZNF365, CADM1, ATP13A4, RAB3B, NFIA, TACR1, NRP1, FSTL4, LYPD3, AKR1E2, BOC, KCNMB4, FNDC4, LAMA4, ETV7, NGEF. SUSD3. EFR3B, MMP15, VSIG10L, MATN3, ENPP3, EFCAB6. SH3RF2, GHR, PMP22, LOX, SORCS2, RDH10, C1QTNF2, SCNN1G, RNF165, SDC2, SLC12A2, INHBA, SLC13A3, PLCB1, CX3CL1, HYDIN, GLT8D2, RNF43, FEZ1, RNF152, MPV17L, ANO1, CDK6. CILP2, PDGFD, HOXC11, EPHB3, DDX58, PLTP, SERPINEL SLC2A10, KHDRBS3, TRIM9, NTN4, CORO1A, B3GALT5, EVA1A, PDE6B, GPR176, EFEMP2, NPR2, GLRB, DMCL CTF1, CD8A, PMAIP1, ALDOC, PDGFA, TGFB2, LIMS2, FBLN7, TPST1, EMP1, UBASH3B, ADAMTS15, ISG20, ECHDC1, SHOX2, VWDE, PROCR, HSH2D, CLCN4, FAM189A2, MAP1B, NOX5, GPC1, TBX3, PRSS27, GYG2, FAM83F, F3, PGF, PRSS23, ITGA5, COL18A1. SHANK2, SHANK3, ATP1B1, RASGRP3, PTGES, SGCE, FRY, NOTUM, EID1 , SLC27A2, WBP2NL, JAG1, PRRT2, RNF180, SCD5, PLLP, BEAN1, FERMT2, TPPP3, FUT9, ASRGL1, NPTXR, HCST, MPZL2, C6orfl41, PLK2, EFHC2, COL16A1. ADORA2B. FBLNL ZNF501, CACNA1D, AFAP1L1, ATP8A1, DOC2A, MMEL1, CD6, ARHGEF25, PCSK6, SPATA6, TLR1, L3MBTL1, ADHFE1, GPX8, CES4A, TRPC1, CNIH3, MCAM, PCDHB13, ROR1, MEIS3, SNTB1, AK7, AHRR, NDRG4, GPR39, IGFBP6, SERTAD4, SPTBN5. NQOL IL20RB, INHA, ZNF471, PNCK. ADAM12, MAPK15, MAML3. SHROOM2, CROT, RHOBTB3, SEC14L5, SGSM1, DUSP5, TNFRSF11A, MEGF6, NKD1, C1QTNF6, USP18, DMGDH, EPS8, EML1, MRAS, PNPLA7, ANKRD34A, PDGFC, VEGFA, FZD4, LAMA3, PDK3, EPAS1, CDH26, THRB, BRSK1, RIBC2, HSPG2, EGFR, GGT7, MYOM1, PPP1R36, HAS3, PDGFB, WNT2B, PPFIA4, HOXC13, CHST3, STU, THBS1, FIGN,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002HLX, GAL3ST4, RFTN1, Clorfll5, HSPA12A, SLC29A4. RPS6KA2, PHLDB2, PNPLA4. CDHR3, ST3GAL4, ITGB5, CRIP2, ULBP1, PTPRG, ZNF717, SCN1B, SH3RF3, ADAMTS1, PKD1L1, ATP2A1, ACOT4, SLC22A17, MAML2, CYBRD1, ZBTB20, CENPW, LGALS1, ARHGAP5, ARHGEF17. BCO2, C14orf28, CACNB1, CD59, CDIPT, CES2, CNNM2, CTNNAL1, CTSS, ENGASE, GLIS2, HM13, JMJD8, KLHL26, L3MBTL2, MORN4, NR4A1, PLOD3, QSOX1, RNF40, SIDT2, SLC25A42, SLC39A13, SOCS5, TBC1D20, TECPR2, TMEM184B, TTC23, WWP2, ARTN, CADM4, CARD14, CNBD2, DBNDD1, ENPP4, EPB41L5, EXD3, FHL2, KIFC3, KRT83, PLA2R1, PRR3, SIAE, SLC12A8, TBC1D7, TMEM217, TOMI, TRNP1, TXNRD2, VLDLR, ZDHHC1, PGBD5, ANK2, SRPX2. MAP1A, COL1A1, SLC2A12, SLC6A11, ADAMTS12, ATP8B2, CCDC80, COL14A1, COL1A2, COL3A1, COL5A1, COL6A3, EXOG, INPP4B, KLF6, LDLR, MAST4, MTMR11, OLFML2A, PDE4A, PHKG1, RARB, UTP23, UTRN, MAT2B, SET, TPM3. or combinations thereof; or combinations thereof; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by taxane chemotherapeutic agents administered as a single agent.

14. The method of claim 1, wherein the measured biomarkers comprise LGALS1 , GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11, KIF2C, CDK19, LGALS1, LGALS3BP, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469. SUV39H1, and TP53INP2; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum and taxane chemotherapeutic agents administered in combination.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-00215. The method of claim 1. wherein the measured biomarkers comprise one or more of the following measured biomarkers:ACSS2, ARMCX3, RAB2A. WBP2NL, SLC22A18. DECR1. DYSF, EXOCI, STAM2, KDELR2, AP1B1, VRK3, METRN, INTS8, PRRC1, PDE6D, NCOA2, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, EIF2D, ACBD5, AIG1, DTWD1, ELP2, EPM2A, PAQR6, PIK3C3, RARS2, SF3B5, SHPRH, ZC3HAV1L, ORC1, EIF4A3, CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERI1, CDCA7, PRKAB1, NUP210, POP5, TNFAIP2, PARD6A, RHEBL1, FBL, HAUS5, MFHAS1, PRIM1, PINX1, C12orf43, PCBP2, CHAF1B, TMPO. E2F7, MED12L, CNTLN, DDX23, GATC, WDR76, MCM2, RFC5, HAUS1, or combinations thereof;LGALS1, GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11, KIF2C, CDK19, or combinations thereof;MAD2L1, OVOL2, OAS2, IFI44, IFI44L, OAS1, or combinations thereof;ARMCX3, DNAJC3, DSTYK, EIF2D, KDELR2, KPNA3, METRN, PEX2, RAB2A, SLC35B3, STX12, SUGT1, TMEM106B. TWISTNB, UBE2W, VPS36, WBP2NL. ZNF12, ZNF623, ALYREF, C12orf43, EIF4A3, ERH, FBL, GATC, HAUS1, KIF2C, LGALS3BP, MCM2, NFKB2, NUP37, NUP85, ORC1, PCBP2, POP5, PRIM1, RELB, RFC5, TMPO, or combinations thereof;ACSS2, ARMCX3, RAB2A, WBP2NL, SLC22A18, DECR1, DYSF, EXOCI, STAM2, KDELR2, AP1B1, VRK3, METRN, INTS8, PRRC1. PDE6D, NCOA2, NFE2L1, FAM160B1. ZC2HC1 A, OSGTN2, EIF2D, ACBD5, AIG1, DTWD1, ELP2, EPM2A, PAQR6, PIK3C3, RARS2, SF3B5, SHPRH, ZC3HAV1L, ORC1, EIF4A3, CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERIE CDCA7, PRKABL NUP210, POP5, TNFAIP2, PARD6A, RHEBL1, FBL, HAUS5, MFHAS1, PRIME PINX1, C12orf43, PCBP2, CHAF1B, TMPO, E2F7, MED12L, CNTLN, DDX23, GATC. WDR76, MCM2, RFC5, HAUSL LGALS1, ATG2B, DTX3L, ERH, ALYREF, MORC3. SLC2A11, KIF2C, CDK19, MAD2L1, OVOL2. OAS2. IFI44, IFI44L, OAS1, DNAJC3, DSTYK, KPNA3, PEX2, SLC35B3, STX12, SUGT1, TMEM106B, TWISTNB, UBE2W, VPS36, ZNF12, ZNF623, LGALS3BP, NFKB2, NUP37, RELB, or combinations thereof;LGALS1, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469, LGALS3BP, SUV39H1, TP53INP2, or combinations thereof;PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002GOLGA5, DUSP18, EHBP1L1, ACSS2, ARMCX3, TRIP11, RAB2A. WBP2NL, SLC22A18, FOXRED2, DECR1, DYSF, TOMI, ZNF70, EXOCI, PES1, D2HGDH, STAM2, KDELR2, AP1B1, TECPR2, RNF185, VRK3, METRN, MORC2, MPV17, INTS8, HSCB, PRRC1, ATP6V0E1, EHD1, PHF20, SERINC3, FLVCR2, PDE6D, HPS4, INPP5A, TM9SF4, NCOA2, VPS37C, RBKS, PRKCD, JKAMP, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, EIF2D, ACBD5, AIG1, ANKRD46, ATP6AP1L, BTBD3, C2orf76, CLHC1, COA5, CRCP, DBT, DCUN1D4, DHRS12, DPH5, DPY19L4, DTWD1, DYNC1LI2, EFNA3, ELP2, EPM2A, INTS6, KIF3A, KRIT1, LAMTOR3, MFF, NEURL2, PAQR6, PCGF3, PEX6, PIK3C3, PSTK, RAB11FIP2, RAD50, RARS2, SAR1A, SENP8. SF3B5, SHPRH, SLC2A11, SMARCAD1, TIGD6, TMEM67, WDPCP, ZC3HAV1L, ZKSCAN1, ZRANB1, GPHN, MACROD2, YLPM1, UNC119B, ZNF787, ZNF287, APOLD1, MEST, TNKS, RUVBL2, UBR7, COX14, ORC1, PPP3CC, EIF4A3, RARRESE CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERI1, CDCA7, PRKAB1, NUP210, CCAR1, POP5, TNFAIP2, IGF2BP2, PARD6A, AKAP5, RHEBL1, FBL, HAUS5, CDKN2A, MFHAS1, PRIM1, PINX1, C12orf43, PCBP2, CHAF1B, TMPO, LXN, TLR1, E2F7, MED12L, CNTLN, ZNF483. DDX23. GATC, WDR76, MCM2, RFC5, HAUS1, ACP2, ALAS1, ANKRD22, ANKRD33B, ANXA11, C1R, CC2D1B, CD274, CYTH1, DRAM1, EGLN2, ELF4, FBXO6, GRB2, IFIH1, IKBKG, IL18BP, JMJD6, KLHDC7B, LAG3, LAMP3, LGALS3BP, MX1, MYD88, NFKB2, OAS2, OAS3, OASL, PARP12, PIK3CD, RAB35, RBM42, REC8, RELB, RNF213, RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM 14, or combinations thereof;PTGER4, PPM1 A, RBFOX2, BRWD1 , TRF1 , FEN1 , TOMM40, OAS2, or combinations thereof;PARPBP, AURKB, AURKA, BTN3A3, TLR3, SAMD9L, PARP12, DDX60, IFIH1, PLSCR1, IFITM1, IRF9, OAS2, BATF2, STATE OAS3, IFI27, OAS1, UBE2L6, GBP4, ETV7, GBP1, BST2, XAF1, DDX60L, PARP14, OASL, DTX3L, SP100, B2M, SAMD9, IFI6, PSMB9, IFIT3, HERC5, ISG15, RSAD2, LAMP3. MX1, IRF1. PSME1. PSMB10, IFI35, IFI44. PARP9. IFIT1, IFIT2, HERC6, NMI, GLI4, ZNF696, ZNF517, ARHGEF37, GRHL2, SPINT2, or combinations thereof;ACO2, ACSS2, ARMCX3, ATG2B, CADM1, CLTCL1, CXCL14, DNAJC3, DSTYK, DUSP18, EHBP1L1, EIF2D, FITM2, FOXRED2, GDF9, GLI4, HECTD1, HMGXB4, KDELR2,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002KPNA3, MAPK1, METRN, MORC2, MPP6, MPV17, NAA30, NR3C2, PEX2, PHF7, PIGH, PLA2G6, POLI, PPARGC1A, RAB2A, RHBDD3, RNF185, RNF215, SLC23A2, SLC29A4, SLC30A9, SLC35B3, SPRYD7, STX12, SUGT1, TMEM106B, TOMI, TRIP11, TTLL1, TWISTNB, UBE2W, VPS36, WBP2NL, WIPF2. ZFP28, ZNF12. ZNF471, ZNF623, ZNF70, ANKRD46, ARMC10, ATP6AP1L, BTBD3, C2orf76, CLHC1, COA5, CRCP, DBT, DCUN1D4, DHRS12, DPH5, DPY19L4, DYNC1LI2, EFNA3, ELP2, INTS6, ISCA1, KIF3A, KRIT1, LAMTOR3, MFF, NEURL2, PAQR6, PCGF3, PEX6, PIK3C3, PSTK, PTCD3, PUM2, RAB11FIP2, RABGGTB, RAD50, SAR1A, SENP8, SLC2A11, SMARCAD1, SRSF11, TIGD6, TMEM67, WDPCP. ZKSCAN1, ZNF644, ZRANB1, DZANK1, GPHN, ACPI, E2F6, YLPM1, ZNF787, MEST, RUVBL2, UBR7, ORC1, EIF4A3, NUP85, NUP210, POP5, IGF2BP2, FBL, PRIM1, C12orf43, PCBP2, TMPO, LXN, TLR1, ZNF483, GATC, MCM2, RFC5, HAUS1, ACP2, ALAS1, ALYREF, ANKRD22, ANKRD33B, ANXA11, C1R, CC2D1B, CD274, CYTH1. DRAM1, EGLN2, ELF4, ERH, FBXO6, GRB2, IFIH1, IKBKG, IL18BP, JMJD6, KIF2C, KLHDC7B, LAG3, LAMP3, LGALS3BP, MX1, MYD88, NFKB2, NUP37, OAS2, OAS3, OASL, PARP12. PIK3CD, RAB35, RBM42, REC8, RELB, RNF213. RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM 14, TXLNB, C15orf48, ATP6V0A4, LTF, HERC5. ARPC1B, CYBA, or combinations thereof;GOLGA5, DUSP18, EHBP1L1, ACSS2, ARMCX3, TRIP11, RAB2A, WBP2NL, SLC22A18, FOXRED2, DECR1, DYSF, TOMI, ZNF70, EXOCI, PES1, D2HGDH, STAM2, KDELR2, AP1B1. TECPR2, RNF185, VRK3, METRN, MORC2, MPV17, INTS8, HSCB. PRRC1, ATP6V0E1 , EHD1 , PHF20, SERINC3, FLVCR2, PDE6D, HPS4, INPP5A, TM9SF4, NCOA2, VPS37C, RBKS, PRKCD, JKAMP, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, EIF2D, ACBD5, AIG1, ANKRD46, ATP6AP1L, BTBD3, C2orf76, CLHC1, COA5. CRCP, DBT, DCUN1D4, DHRS12, DPH5, DPY19L4, DTWD1, DYNC1LI2, EFNA3, ELP2, EPM2A, INTS6, KIF3A, KRITl, LAMTOR3, MFF, NEURL2, PAQR6, PCGF3, PEX6, PIK3C3, PSTK, RAB11FIP2, RAD50, RARS2, SAR1A, SENP8. SF3B5, SHPRH, SLC2A11. SMARCAD1, TIGD6, TMEM67. WDPCP, ZC3HAV1L, ZKSCAN1, ZRANB1, GPHN, MACROD2, YLPM1, UNC119B, ZNF787, ZNF287, APOLD1, MEST, TNKS, RUVBL2, UBR7, COX14, ORC1, PPP3CC, EIF4A3, RARRES1, CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERI1, CDCA7, PRKAB1, NUP210, CCAR1, POP5, TNFAIP2, IGF2BP2, PARD6A, AKAP5, RHEBL1, FBL, HAUS5,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002CDKN2A, MFHAS1, PRIM1, PINX1. C12orf43. PCBP2, CHAF1B, TMPO, LXN, TLR1, E2F7, MED12L, CNTLN, ZNF483, DDX23, GATC, WDR76, MCM2, RFC5, HAUS1, ACP2, ALAS1, ANKRD22, ANKRD33B, ANXA11, C1R, CC2D1B, CD274, CYTH1, DRAM1, EGLN2, ELF4, FBXO6, GRB2, IFIH1, IKBKG, IL18BP, JMJD6, KLHDC7B, LAG3, LAMP3, LGALS3BP, MX1, MYD88, NFKB2, OAS2, OAS3, OASL, PARP12, PIK3CD, RAB35, RBM42, REC8, RELB, RNF213, RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM14, PTGER4, PPM1A, RBFOX2, BRWD1, IRF1, FEN1, TOMM40, PARPBP, AURKB, AURKA, BTN3A3, TLR3, SAMD9L, DDX60, PLSCR1, IFITM1, IRF9, BATF2, STAT1, IFI27, OAS1, UBE2L6. GBP4, ETV7, GBP1, BST2, XAF1, DDX60L. PARP14, DTX3L, SP100, B2M, SAMD9, IFI6, PSMB9, IFIT3, HERC5, ISG15, RSAD2, PSME1, PSMB10, IFI35, IFI44, PARP9, IFIT1, IFIT2, HERC6, NMI, GLI4, ZNF696, ZNF517, ARHGEF37, GRHL2. SPINT2, ACO2, ATG2B, CADM1. CLTCL1, CXCL14, DNAJC3, DSTYK, FITM2, GDF9, HECTD1, HMGXB4, KPNA3, MAPK1, MPP6, NAA30, NR3C2, PEX2, PHF7, PIGH, PLA2G6, POLI, PPARGC1A, RHBDD3, RNF215, SLC23A2, SLC29A4, SLC30A9, SLC35B3, SPRYD7, STX12. SUGT1. TMEM106B, TTLL1, TWISTNB, UBE2W, VPS36, WIPF2. ZFP28, ZNF12, ZNF471, ZNF623, ARMC10, ISCA1, PTCD3, PUM2, RABGGTB, SRSF11, ZNF644, DZANK1, ACPI, E2F6, ALYREF, ERH, KIF2C, NUP37, TXLNB, C15orf48, ATP6V0A4, LTF, ARPC1B, CYBA, or combinations thereof; or combinations thereof; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum and taxane chemotherapeutic agents administered in combination.

16. The method of claim 1, wherein the measured biomarkers comprise KRT5; and wherein differentially expressed levels of the biomarkers are correlated to a likelihood of a success of treatment by platinum chemotherapeutic agents, taxane chemotherapeutic agents, or combinations thereof.

17. The method of claim 1, wherein the subject is a human being.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-00218. The method of claim 1, wherein the differentially expressed levels of the biomarkers correspond to increased levels of the biomarkers, decreased levels of the biomarkers, or combinations thereof.

19. The method of claim 1, wherein the differentially expressed levels of the biomarkers correspond to increased levels of the biomarkers.

20. The method of claim 1, wherein the differentially expressed levels of the biomarkers correspond to decreased levels of the biomarkers.

21. The method of claim 1, wherein the assessment occurs manually.

22. The method of claim 1, wherein the assessment occurs automatically through the utilization of an algorithm.

23. The method of claim 22, wherein the algorithm is a machine learning algorithm trained on the measured biomarkers.

24. The method of claim 1, further comprising a step of implementing a treatment decision based on the assessment.

25. The method of claim 24, wherein the treatment decision comprises monitoring the course of the triple negative breast cancer, removing a tumor from the subject, administering a therapeutic agent to the subject, modifying a pre-existing treatment regimen, or combinations thereof.

26. The method of claim 24, wherein the treatment decision comprises administering a therapeutic agent to the subject.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-00227. The method of claim 26, wherein the therapeutic agent is selected from the group consisting of chemotherapeutic agents, carboplatin, cisplatin, taxane chemotherapeutic agents, docetaxel, paclitaxel, or combinations thereof.

28. A system for assessing the treatment outcome of a subject suffering from triple negative breast cancer, wherein the system comprises one or more computer-readable storage mediums having a program code embodied therewith, wherein the program code comprises programming instructions for: receiving measured biomarkers from the subject, wherein the biomarkers are selected from the group consisting of PRKX, TMEM135, MRPL32, VASH1, PTBP2, RAB1B, NCOA2, SLC25A35, COMMD7, CDC25A, CCNE2, MTMR3, TMEM219, HMGN4, MLYCD, NCAPG, LGALS1, GATC, ATG2B, DTX3L, ERH, ALYREF, MORC3, SLC2A11, KIF2C, CDK19, LGALS3BP, IMMP2L, PPM1G, NFYA, RBBP7, WSB1, ZNF469, SUV39H1, TP53INP2, LCAT, THEM6, IRS2, ARL4D, STUB1, ITM2B, HINT3, PTDSS2, XPO6, ZNF322, ZNF669, TPCN1, CCDC91, IPO5, SUMF1. KRT5. ACSS2. ESRRA. CCL5. POTI. ZFP37, ZNF256, ZNF394. SPICEl, CUL4A, PIK3CA, TMEM98, TOP3A, BRIP1, MSH6, RND2, RAB9B, TGFB1I1, TULP3, TSSC4. ARMC7, FANCI, TRPV4, NDUFA2, USP49, SSX2IP, C3orf38, KNK2, SLC39A4, MFSD3, TSTA3, AEBP1, MYH10, PRSS8, LAD1, PKP3, LRP6, RGMA, ZNF462, COL27A1, APEH, BTG2, DEGS1, EBPL, EIF2D, FAM174A, FUT3, GALE, GNPNAT1, HIBCH, LAP3, LRRC8E, METTLE PGD, PSCA, RNASEH2C, SPRYD7, GLTP, ENDOD1, AQP1, ARHGAP33, ASAP2, ATAD2B, ATAD5, BICD1 , CDH24, CHICI , CNOT4, CNTLN, DEK, DMC1 , DMXL2, EFNB3, EZH2, FAM168A, FIZ1, FOXN3, GPR19, GXYLT1, HAUS5, HELLS, HES6, IRF2BPL, ITPKB. KLHL25, MSANTD2. N4BP2L1, PDE4DIP, PLEKHG2, POLH, PPM1D, PRKAB2, SLC4A7, SMC6, SOWAHC, STARD13, TM2D3, TRAM1L1, USP1, UTRN, WHAMM, ZNF160, ZNF184, ZNF212, ZNF367, ZNF566, ZNF573, ZNF620, ZNF654, ZSCAN5A, BYSL, USP37, EXO5, HIC2, ZNF197, BCAR1. METRN, ZDHHC7, SLC22A18, PLXND1, SGCE, ATP7B, PHLDA3, CMBL, ALDH1A1, ASF1A, ECHDC1, ZNF100, ZNF493, ZNF85, KCNF1, KCTD17, PCOLCE2. DNAJC24, SAV1, TMEM126B, POGZ, SRSF7, TMPO, POLE, FAM83H, RPL8, ATP8B2, Clorfl l6, AKAP7, SIMC1, FGD1, DHRS7, HIBADH, LRTOMT, NTN4, PFKFB2, SNX13, TAX1BP1, ZBTB3, CCDC61, TSPAN31, TMEM150A, ADCY1, ARRB2, ASH1L, CLK2,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002CPSF6. DNA2, DNAJC9. GPR63, HACE1. HYI, KCTD15, LYSMD1. MRPL9, PRPF3, RPRD2, TOE1, UCK1, ZNF189, ZNF510, ZNF740, ZWINT, GOPC, TRIP13, RHOBTB1, SPAG5, SRRD, NCOA7, STIL, COPS3, HSPA13, DONSON, CCDC117, CHAF1A, SUZ12, WNK3, TK2, PPP2R3A, ZNF17, SMAD4, MCOLN2. MSI1, FCHSD2, C2CD3, MAD2L1, TPBG, SRRT. MEX3C, PTK6, ZNF22, MDM1, SAR1B, VPS28, FOXM1, CAP2, FAM126A, MRPL2, MRPS10, MTHFSD, OAZ2, RAB3IL1, SLC25A17, SLC29A1, SNAP29, SPRTN, TM9SF4, TPMT, YWHAH, ZNF75A, ZYX, SPATA7, TLE2, KLHL7, ZNF133, NR1H2, ISCA1, NDUFA3, EFNA5, ERLEC1, GPR157, RELL1, BLMH, HIVEP1, ARID1B, TCHP, BRAP, RFC5, EWSR1, ZMAT5, TCEA1, KLK5, RAB6B, FAXC, RPS12, STX7, BCL2L10, GOLGA8A, FGF11, IL18R1, ANKRD6, ZNF483, EPHX4, FBN3, OVOL2, PCDH1, ANGPTL4, QSOX1, INPP5A, ADCY9, Cllorf24, RIN2, RAB2A, BCKDK, ABCC2, NAA60, HDLBP, SPARC, MGRN1, TRIOBP, TGM2, SERINC5. PMM2, POR. GMPPA, GNAI1, RAB11FIP5, FLYWCH1, FARP2, SYNC, TMEM214, STRN3, SFXN3, CERCAM, SEMA4B, USP40, TRPC4AP, ABLIM3, COMT, ZHX3, UBN1, ENG, HHLA3, YBX2, FITM2, PLCB3, ANKS3, WNT9A, MPP2, PGBD1, CCDC17, CC2D2A, EPM2A, ICA1L. KANSL1L, LRP2BP, LYPD1, MAP2, MYOID, NHSL1, PGAP1. PLEKHM3, PYGB, RSPH3, ZBTB44, ZNF431, ZNF708, PDSS2, AKIRIN2, SYNCRIP, FAM221A, MDK, CD83, RNGTT, JPH2, KIAA0556, MSRB3, SAMD9L, DHX38, ZNF81, PTTG1, SP110, IFIT1, DDX60, XAF1, IFI44, OAS2, GBP4, STATE ACTG2, KRT6B, AZGP1, ZG16B, STAC2, KLK7, KRT15, CDKN2A, IFI27, COL5A2, PXDN, ACTA2, TF, NTRK2, AGT, S100A1, CRYAB. EDN2, PCP4L1, ANGPT1, PTX3, INHBB, TIMP3. SIX1, RERG, FKBP10, SMOC2, COL6A2, SNAI2, COL8A1, PXDNL, CASP14, SOD3, PIK3C2G, PCOLCE, NMU, PI15, TACSTD2, BGN, SYNM, SLITRK6, MMP2, PRELP, ADM, TBX1, IGFBP5, BATF2, AKR1C1, IFITM1, C15orf48, FBXO2, ASPHD1, RCN3, TAGLN. MXRA8, MX2. AKR1C3, PPP1R3C. FN1, XYLT1, IL32, TPM2, MYL9, NDUFA4L2, SKAP1, TMEM47, ADCY2, GPRC5C, KIAA1549L, SMARCA1, IFIT2, DHX58, SEMA3C, SCUBE2, COL17A1, MFGE8, RTN4RL1, SRPX, NR2F1, ATP13A5. NDRG1. GXYLT2. TNC, KCNK5, GAS6. ARSJ, MAOA, SLC24A3. FHOD3. FST. DDIT4L, OSR1, CCND1, SERPINE2, SUSD2, GPT, MALL, SCUBE3, OAS1, CA12, COL7A1, EGLN3, SLC6A17, LAMB1, SCN4B, ESRRG, RBI, FAM83A, DDR2, ANKRD22, COPZ2, DAPP1, A4GALT, OPRK1, KLHL13, CNTN1, MYLK, BMPR1B, RGS11, CITED4, LAG3, SCNN1B, NDP, TSPYL5, PID1, ALDH3B2, ADORA1, GLB1L2, SORBS2, B4GALNT2, LCK,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002MEGF10, IGFBP3, STC1, TMEM200B, LOXL2, APLN, DKK3, PKDCC, TLR3. FGFR1, CAVE FAT4, VIM, ZNF365, CADM1, ATP13A4, RAB3B, NFIA, TACR1, NRP1, FSTL4, LYPD3, AKR1E2, BOC, KCNMB4, FNDC4, LAMA4, ETV7, NGEF, SUSD3, EFR3B, MMP15, VSIG10L, MATN3, ENPP3, EFCAB6, SH3RF2, GHR, PMP22, LOX, SORCS2, RDH10, C1QTNF2. SCNN1G, RNF165, SDC2, SLC12A2, INHBA, SLC13A3, PLCB1, CX3CL1, HYDIN, GLT8D2, RNF43, FEZ1, RNF152, MPV17L, ANO1, CDK6, CILP2, PDGFD, HOXC11, EPHB3, DDX58, PLTP, SERPINE1, SLC2A10, KHDRBS3, TRIM9, CORO1A, B3GALT5, EVA1A, PDE6B, GPR176, EFEMP2, NPR2, GLRB, CTF1, CD8A, PMAIP1, ALDOC, PDGFA, TGFB2, LIMS2, FBLN7, TPST1, EMP1. UBASH3B, ADAMTS15, ISG20, SHOX2, VWDE. PROCR, HSH2D, CLCN4, FAM189A2, MAP1B, NOX5, GPC1, TBX3, PRSS27, GYG2, FAM83F, F3, PGF, PRSS23, FTGA5, COL18A1, SHANK2, SHANK3, ATP1B1, RASGRP3, PTGES, FRY, NOTUM, EIDE SLC27A2, WBP2NL, JAG1, PRRT2, RNF180, SCD5, PLLP, BEAN1, FERMT2, TPPP3. FUT9, ASRGL1, NPTXR, HCST, MPZL2, C6orfl41, PLK2, EFHC2, COL16A1, ADORA2B, FBLN1, ZNF501, CACNA1D, AFAP1L1, ATP8A1, DOC2A, MMEL1, CD6, ARHGEF25, PCSK6, SPATA6, TLRL L3MBTL1, ADHFE1, GPX8. CES4A, TRPC1, CNIH3, MCAM, PCDHB13. ROR1, MEIS3, SNTB1, AK7, AHRR, NDRG4, GPR39, IGFBP6, SERTAD4, SPTBN5, NQO1, IL20RB, INHA, ZNF471, PNCK, ADAM12, MAPK15, MAML3, SHROOM2, CROT, RHOBTB3, SEC14L5, SGSM1, DUSP5, TNFRSF11A, MEGF6, NKD1, C1QTNF6, USP18, DMGDH, EPS8, EML1, MRAS, PNPLA7, ANKRD34A, PDGFC, VEGFA, FZD4, LAMA3, PDK3, EPAS1, CDH26, THRB, BRSK1, RIBC2, HSPG2, EGFR, GGT7, MYOM1, PPP1R36, HAS3, PDGFB, WNT2B, PPFIA4, HOXC13, CHST3, STU, THBS1, FIGN, HLX, GAL3ST4, RFTN1, Clorfl 15, HSPA12A, SLC29A4, RPS6KA2, PHLDB2, PNPLA4, CDHR3, ST3GAL4, ITGB5, CRIP2, ULBP1, PTPRG, ZNF717, SCN1B, SH3RF3. ADAMTS1, PKD1L1, ATP2A1, ACOT4, SLC22A17, MAML2, CYBRD1, ZBTB20, CENPW, ARHGAP5, ARHGEF17, BCO2, C14orf28, CACNB1, CD59, CDIPT. CES2, CNNM2, CTNNAL1, CTSS, ENGASE, GLIS2, HM13, JMJD8, KLHL26, L3MBTL2. MORN4, NR4A1, PLOD3, RNF40. SIDT2, SLC25A42, SLC39A13, SOCS5. TBC1D20, TECPR2, TMEM184B, TTC23, WWP2, ARTN, CADM4, CARD14, CNBD2, DBNDD1, ENPP4, EPB41L5, EXD3, FHL2, KIFC3, KRT83, PLA2R1, PRR3, SIAE, SLC12A8, TBC1D7, TMEM217, TOMI, TRNP1, TXNRD2, VLDLR, ZDHHC1, PGBD5, ANK2, SRPX2, MAP1A, COL1A1, SLC2A12, SLC6A11, ADAMTS12, CCDC80, COL14A1, COL1A2, COL3A1,PCT Application Attorney Docket No. AF44111.P046WOBLG 22-002COL5A1, COL6A3. EXOG, INPP4B, KLF6, LDLR. MAST4, MTMR11, OLFML2A, PDE4A, PHKG1, RARB, UTP23, MAT2B, SET, TPM3, ARMCX3, DECR1, DYSF, EXOCI, STAM2, KDELR2, AP1B1, VRK3, INTS8, PRRC1, PDE6D, NFE2L1, FAM160B1, ZC2HC1A, OSGIN2, ACBD5, AIG1, DTWD1, ELP2, PAQR6, PIK3C3. RARS2. SF3B5, SHPRH, ZC3HAV1L, ORC1, EIF4A3, CSRP2, NUP85, CEBPB, MOB3B, MCM3, NCAPH2, ERI1, CDCA7, PRKAB1, NUP210, POP5, TNFAIP2, PARD6A, RHEBL1, FBL, MFHASL PRIM1, PINX1, C12orf43, PCBP2, CHAF1B, E2F7, MED12L, DDX23, WDR76, MCM2, HAUS1, IFI44L, DNAJC3, DSTYK, KPNA3, PEX2, SLC35B3, STX12, SUGT1, TMEM106B, TWISTNB, UBE2W, VPS36, ZNF12. ZNF623, NFKB2, NUP37, RELB, GOLGA5, DUSP18, EHBP1L1, TRIP11, FOXRED2, ZNF70, PES1, D2HGDH, RNF185, MORC2, MPV17, HSCB, ATP6V0E1, EHD1, PHF20, SERINC3, FLVCR2, HPS4, VPS37C, RBKS, PRKCD, JKAMP, ANKRD46, ATP6AP1L, BTBD3, C2orf76, CLHC1, COA5. CRCP, DBT, DCUN1D4, DHRS12, DPH5, DPY19L4, DYNC1LI2, EFNA3, INTS6, KIF3A, KRIT1, LAMTOR3, MFF, NEURL2, PCGF3, PEX6, PSTK, RAB11FIP2, RAD50, SAR1A, SENP8, SMARCAD1, TIGD6, TMEM67, WDPCP, ZKSCAN1, ZRANB1, GPHN. MACROD2, YLPM1, UNC119B. ZNF787, ZNF287, APOLD1, MEST. TNKS, RUVBL2, UBR7, COX14, PPP3CC, RARRES1, CCAR1, IGF2BP2, AKAP5, LXN, ACP2, ALAS1, ANKRD33B, ANXA11, C1R, CC2D1B, CD274, CYTH1, DRAM1, EGLN2, ELF4, FBXO6, GRB2, IFIH1, IKBKG, IL18BP, JMJD6, KLHDC7B, LAMP3, MX1, MYD88, OAS3, OASL, PARP12, PIK3CD, RAB35, RBM42, REC8, RNF213, RNF34, SCARA3, SHKBP1, SLC25A22, SLC9A6, SOCS1, SOCS3, SPATS2L, STAT3, SYNGR2, TAOK3, TRAFD1, TRIM14, PTGER4, PPM1 A, RBFOX2, BRWD1 , TRF1 , FEN1 , TOMM40, PARPBP, AURKB, AURKA, BTN3A3, PLSCR1, IRF9 , UBE2L6, GBP1, BST2, PARP14, SP100, B2M, SAMD9, IFI6, PSMB9, IFIT3, HERC5, ISG15, RSAD2, PSME1, PSMB10, IFI35, PARP9. HERC6. NMI, GLI4. ZNF696, ZNF517, ARHGEF37, GRHL2, SPINT2, ACO2, CLTCL1, CXCL14, GDF9, HECTD1, HMGXB4, MAPK1, MPP6, NAA30, NR3C2, PHF7, PIGH, PLA2G6, POLI, PPARGC1A, RHBDD3, RNF215, SLC23A2, SLC30A9. TTLL1, WIPF2, ZFP28, ARMC10. PTCD3, PUM2. RABGGTB, SRSF11, ZNF644, DZANK1, ACPI, E2F6, TXLNB, ATP6V0A4, LTF, ARPC1B, CYBA, DDX60L,or combinations thereof; and correlating differentially expressed levels of the biomarkers to a treatment outcome.PCT Application Attorney Docket No. AF44111.P046WOBLG 22-00229. The system of claim 28, wherein the computing device comprises an algorithm, and wherein the assessment occurs through the utilization of the algorithm.

30. The system of claim 29, wherein the algorithm is a machine learning algorithm trained on the measured biomarkers.

31. The system of claim 29, wherein the program code further comprises programming instructions for recommending a treatment decision based on the assessment.

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