Pancancer gene fusions and rearrangements and methods and uses related thereto

Abstract

Provided herein are methods related to treating or delaying progression of cancer in an individual. In some embodiments, the methods comprise detecting one or more TMPRSS2-ERG gene rearrangements in one or more samples from an individual having prostate cancer; and administering to the individual an effective amount of a treatment that comprises an anti-cancer agent.

Description

PANCANCER GENE FUSIONS AND REARRANGEMENTS AND METHODS ANDUSES REEATED THERETOCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 605,179, filed December 1, 2023, which is hereby incorporated by reference in its entirety.SUMMARY OF THE INVENTION

[0002] In one aspect, provided herein are methods related to treating or delaying progression of cancer in an individual. In some embodiments, the methods comprise detecting one or more TMPRSS2-ERG gene rearrangements in one or more samples from an individual having prostate cancer; and administering to the individual an effective amount of a treatment that comprises an anti-cancer agent.

[0003] It is to be understood that one, some, or all of the properties of the various embodiments described herein may be combined to form other embodiments of the present invention. These and other aspects of the invention will become apparent to one of skill in the art. These and other embodiments of the invention are further described by the detailed description that follows.BRIEF DESCRIPTION OF THE DRAWINGS

[0004] FIG. 1A shows frequency of detection of gain-of-function (GOF) rearrangements in kinase genes prevalence of pathogenic rearrangements (pan-cancer).

[0005] FIG. IB shows frequency of detection of gain-of-function (GOF) rearrangements in kinase genes prevalence of pathogenic rearrangements (pan-cancer), including rearrangements that were categorized as GOF in non-kinase oncogenes, and loss-of-function (LOF) in tumor suppressor genes

[0006] FIG.2A Shows a heatmap of the prevalence of the most frequently rearranged oncogenes in the pan-tumor cohort (cancer types with > 200 liquid biopsies profiled shown), with kinase genes on the left, transcription factors on the right.

[0007] FIG.2B shows the clonal fraction (variant allele frequency / tumor fraction) (VAF / TF) of gene rearrangements considered to be potential pan-tumor bio markers and which appear in multiple cancer types.

[0008] FIG. 2C shows, in tissue and liquid biopsies from same subject, the VAF / TF of each rearrangement that was detected in both tissue and liquid (concordant) or in the liquid biopsy only.

[0009] FIG. 3A shows relative prevalence of short variants (SV), copy number deletions (CN), and rearrangements (RE) predicted to disrupt tumor suppressor genes: for all tumor suppressor genes (top), and for the top 15 rearranged tumor suppressor genes (bottom).

[0010] FIG. 3B shows a heatmap of the prevalence of the tumor suppressor genes frequently disrupted by rearrangement in the pan-tumor cohort. Cancer types with > 200 liquid biopsies profiled and genes altered in >0.5% of at least 1 cancer type are shown.

[0011] FIG. 4A shows a comparison of the prevalence of FGFR2 activating rearrangements among CCA tissue biopsies and liquid biopsies with tumor fraction (TF) >1% and <1%.

[0012] FIG. 4B shows gene partners in rearrangements predicted to encode FGFR2 fusion genes.

[0013] FIG. 4C shows a comparison between the diversity of FGFR2 fusion gene partners in CCA tissue and liquid biopsies.

[0014] FIG. 4D shows a comparison of the prevalence of FGFR2 fusions versus truncations in CCA tissue and liquid biopsies.

[0015] FIG. 4E shows the clonality (variant allele frequency / tumor fraction) of FGFR2 fusions and rearrangements in CCA liquid biopsies.

[0016] FIG. 4F shows concordance of FGFR2 rearrangement detection in a set of samples from the same patient (201 CCA, 160 CUP pairs), with numbers in parentheses are the concordance results within CCA pairs alone.

[0017] FIG. 4G shows results from 16 liquid biopsies where FGFR inhibitor resistance mutations were detected (one sample per vertical column). The top row shows the presumed FGFR2 driver, while the grid below shows the presence of particular FGFR inhibitor acquired resistance mutations. Colors indicate the gene fusion partners detected, “intergenic” indicates a truncation without a specific fusion partner, and the red asterisk denotes a sample with a FGFR2 C382R driver mutation. In 15 / 16 samples, a FGFR2 driver variant was detected alongside resistance mutations.

[0018] FIG. 5A shows a comparison of the prevalence of activating rearrangements in ALK, RET, and ROS1 among NSCLC tissue biopsies and liquid biopsies with tumor fraction (TF) >1% and <1%.

[0019] FIG. 5B shows a comparison of the diversity of fusion gene partners in ALK, RET, and ROS1 fusions in tissue and liquid biopsies.

[0020] FIG. 5C shows a comparison of the clonality of ALK, RET, and ROS1 rearrangements in samples with and without an EGFR driver short variant (L858R, exon 19 deletion, or exon 20 insertion).

[0021] FIG. 5D shows results from 51 liquid biopsy where ALK inhibitor resistance mutations were detected (one sample per vertical column). The top row shows the ALK fusion driver, while the grid below shows the presence of particular ALK inhibitor acquired resistance mutations. Colors indicate the gene fusion partners detected. In 47 / 51 samples, an ALK fusion was detected alongside resistance mutations.

[0022] FIG. 6A shows a comparison of the prevalence of activating rearrangements among prostate cancer tissue biopsies and liquid biopsies with tumor fraction (TF) >1% and <1%.

[0023] FIG. 6B shows the clonality (variant allele frequency / tumor fraction) of driver rearrangements like TMPRSS2-ERG and BRAF, and putative acquired resistance rearrangements in AR in prostate cancer liquid biopsy.

[0024] FIG. 6C shows the overlapping appearance of AR variants in the same prostate cancer liquid biopsy.

[0025] FIG. 6D show the clonality (variant allele frequency / tumor fraction) of the most common pathogenic rearrangements detected in CRC LBx (N>10), in order of median.

[0026] FIG. 6E shows a comparison of the rearrangement frequencies among CRC liquid biopsy that have no clonal KRAS / NRAS / BRAF V600E mutations (N = 1,352) versus CRC liquid biopsy and a clonal KRAS or NRAS mutation (with VAF / TF of at least 25%; N =1,370). Only LBx with TF>1% were included, and liquid biopsy with clonal BRAF V600E mutations were excluded from this analysis.

[0027] FIG. 7 shows rare gain-of-function fusions

[0028] FIG. 8 shows sensitivity of detection of driver rearrangements in paired tissue and liquid biopsy from the same patient

[0029] FIG. 9 shows sensitivity of detection of driver fusions (ALK, RET, and ROS1) in paired tissue and liquid biopsy at different tumor fraction thresholds.EXAMPLES

[0030] The invention will be more fully understood by reference to the following examples. They should not, however, be construed as limiting the scope of the invention. It is understood that the examples and embodiments described herein are for illustrative purposes only and that various modifications or changes in light thereof will be suggested to personsskilled in the art and are to be included within the spirit and purview of this application and scope of the appended claims.Introduction

[0031] Detection of genomic rearrangements in circulating tumor DNA (ctDNA) is heterogeneous across various commercially available and lab developed liquid biopsy assays, with multiple reports of variable performance for the detection of these common genomic events. Some of these structural variants — deletions, duplications, inversions, and translocations — result in gene products that function as potent oncogenic drivers. Receptor tyrosine kinase fusions and activating truncations are well-established targetable driver alterations in non-small cell lung cancer (ALK, RET, ROS1), cholangiocarcinoma (FGFR2), bladder cancer (FGFR3), and thyroid cancer (RET). Testing for activating fusions has become standard of care in these cancer types. Other kinase fusions such as BRAF have had limited actionability to date, but next-generation inhibitors are currently being tested in clinical trials. Some rearrangements activate non-enzymatic oncogenes such as transcription factors (TMPRSS2-ERG, EWSR1-FEI1) and have not been druggable, but PROTACs (proteolysis targeting chimeras) could represent a new therapeutic inroad to inhibit them. Additionally, rearrangements can also disrupt tumor suppressor genes, including actionable genes (BRCA1 / 2) or clinically relevant biomarkers (RBI, STK11). Detection of rearrangements and fusions is therefore critical for clinical decision making in cancer care.

[0032] Rearrangements are detected using multiple molecular pathology tests, including fluorescence in situ hybridization (FISH), imbalance assays, and DNA and RNA-based next generation sequencing (NGS). NGS testing has seen recent increased uptake due to the ability to assess many relevant biomarkers simultaneously, but rearrangements present specific technical challenges for NGS platforms, and the NGS assay design dramatically affects performance. One obstacle for DNA-based assays is that rearrangement breakpoints can occur inside intronic regions that may be challenging to sequence, requiring intentional design and bioinformatics to ensure reliable detection. Some of the intronic regions are long, may have repetitive stretches. While some genes have recurrent breakpoints in specific introns (e.g. AEK, FGFR2, RET), others have more flexible breakpoints and require sequencing across many introns (e.g. BRAF, ROS1, NTRK1), as shown in Table 4. Sequencing RNA can allow breakpoint detection with a smaller sequencing footprint, but RNA has significant instability and high assay failure rates in real world formalin-fixed,paraffin-embedded (FFPE) specimens. When tissue is unavailable, Liquid biopsy-based NGS of ctDNA from peripheral blood is a pragmatic alternative sample type, but poses the additional challenge of detecting rearrangement events in samples with low tumor DNA relative to DNA from healthy cells (often <1% compared to tissue biopsy where the specimen’s tumor content is generally screened visually by a pathologist and required to be enriched to at least >20% prior to being advanced to DNA extraction). Sequencing must be performed to higher depth, which can increase the number of erroneous reads, and make it challenging to capture long intronic regions with sufficient depth in a targeted sequencing panel. Circulating tumor RNA is swiftly digested by circulating ribonucleases and immune cells, and RNA from necrotic cells, which are a major contributor of tumor-derived circulating nucleic acids, can be degraded before it enters circulation. Clinical-grade interpretation of sequencing of this analyte is as yet unproven.TABLE 4.

[0033] Liquid biopsies have been widely considered to lack robust detection of fusions and gene rearrangements. In this study we analyze liquid biopsy results from patients with solid tumors and report the detection of pathogenic rearrangements in a wide set of genes, including gain-of-function fusions and rearrangements in kinase and transcription factor oncogenes, as well as truncating rearrangements in tumor suppressors. We compare detection of select rearrangements with tissue biopsies, including concordance analyses in specimens from the same patient, and report on rearrangements that appear in liquid biopsies as potential polyclonal resistance mechanisms.MethodsPatient and Samples

[0034] Liquid biopsies from patients with solid tumors ordered within the United States between 9 / 2020-3 / 2023 during routine clinical care (N = 53,842) were retrospectively analyzed. For patients with multiple liquid biopsy results (2,594, 4.8%), one specimen was chosen on the basis of quality metrics heuristic that incorporates factors such as sample run date and quality metrics to choose a representative sample. The numbers of samples analyzed for each cancer type are provided in Figure 7. Liquid biopsies submitted without a documented site of origin were designated as cancer of unknown primary (CUP) due to lack of a clear diagnosis and include true CUPs as well as samples for which tissue diagnostic workup may be ongoing or with inadequate information on the requisition form. Approval for this study, including a waiver of informed consent and Health Insurance Portability and Accountability Act (HIPAA) waiver of authorization, was obtained from the Western Institutional Review Board (protocol no. 20152817).Comprehensive genomic profiling of liquid biopsies

[0035] Comprehensive genomic profiling (CGP) was performed. Circulating cell-free DNA was extracted from peripheral whole blood and CGP was performed using hybridization- captured, adaptor ligation-based libraries. The liquid biopsy test interrogates a total of 324 cancer-related genes for base substitutions, short insertions and deletions, copy number amplifications and homozygous deletions, and large genomic rearrangements, as well as micro satellite instability, blood tumor mutational burden, and tumor fraction genomic signatures. Of the 324 genes in the panel, 309 are sequenced with complete exonic coverage, 20 of these with additional intronic coverage, and 15 with only select non-coding coverage. Targeted regions in 75 genes are sequenced with ultra-deep coverage for increased sensitivity. Importantly, the tissue and liquid biopsiers had coverage of the same exons and introns of the 324 cancer-related genes (see FIG. 8 and Table 2 for complete gene list).TABLE 2.

[0036] De novo assembly is performed for detection of short variants, fusions, and other large-scale genomic rearrangements using proprietary algorithms which build de Bruijn graph models from k-mers spanning a variant candidate and take into account the local coverage, number of supporting read clusters, read redundancy, and number of error-containing clusters for the mutant and reference alleles.Tumor fraction quantification and clonality assessment in liquid biopsy

[0037] The ctDNA tumor fraction (TF) on the liquid biopsy is a composite algorithm prioritizing aneuploidy at higher levels to avoid germline signal and prioritizing variant allele frequency (VAF) of canonical alterations at lower levels to maximize dynamic range, is a composite algorithm, rather than relying on only somatic variant allele frequencies (VAF). Because nearly all solid tumors have aneuploidy, the TF estimate prioritizes aneuploidy at higher levels. The algorithm prioritizes VAF of canonical alterations at lower levels when the fraction of cfDNA with aneuploidy cannot be reliably estimated. This composite approach avoids mistaking germline variants for somatic alleles and relying on VAF of variants in amplified genes. The purity assessment from a robust copy-number model, which accounts for both the observed coverage variation and allele frequencies of genome- wide SNP allele frequencies, is used to determine the TF estimate from aneuploidy. When aneuploidy is below the limit of reliable estimation, the allele frequencies of short variants and rearrangements known to be somatic through heuristics are used to estimate TF. Additionally, a multiomic assessment of cfDNA is used both to exclude clonal hematopoiesis-derived aneuploidy from copy-number modeling and to positively identify the somatic status of short variants in this analysis. In this study, the clonality of a rearrangement variant was calculated as the ratio of percent reads of a rearrangement event to the TF of the sample (with a maximum set at 1).Comprehensive genomic profiling of tissue biopsies

[0038] Tissue biopsies from patients with the same cancer types as those analyzed for liquid biopsy that were ordered within the United States between 1 / 2017-1 / 2023 during routine clinical care (N = 295,592) were analyzed using a tissue biopsy as previously described. Briefly, the pathologic diagnosis of tissue biopsy was confirmed on routine hematoxylin andeosin-stained slides. Samples with a minimum of 20% tumor nuclei underwent DNA extraction and underwent hybrid capture-based sequencing of the same 324 cancer-related genes interrogated by liquid biopsy. Some differences in sample preparation between the tissue and liquid platforms include fragmentation by sonication for DNA extracted from tissue, as well as more uniform and lower sequencing depth.Concordance analysis between tissue and liquid biopsy

[0039] For patients with CCA or an unknown primary with CGP results available for both tissue biopsy and liquid biopsy (collected a median 34 days apart), agreement was assessed for detection of driver rearrangements. Sensitivity or percent positive agreement (PPA), and negative predictive value (NPV), were calculated with tissue as standard, 95% binomial confidence intervals were calculated using the Wilson score method with continuity correction. For FGFR2 rearrangement detection concordance, PPA was calculated among pairs submitted as CCA (N= 201) and CUP (N= 160), and NPV was calculated only among the CCA pairs.Statistical tests

[0040] Comparisons for VAF / TF in Figure 2B were made using the Kruskal- Wallis test in a pairwise fashion among the cancer types with >10 rearrangements in the analyzed gene. Comparisons between prevalence of rearrangements in KRAS-positive and -negative samples in Figure 6E were done using the Fisher Exact test. False discovery rate (FDR) was calculated using the Benjamini-Hochberg correction for multiple testing.ResultsPatients and Samples

[0041] Among 53,842 Liquid biopsy, 7,377 (14%) had at least one pathogenic gene rearrangement detected. Gain-of-function (GOF) fusions and rearrangements were detected in 16 receptor tyrosine kinases (RTKs) and downstream kinases (ALK, FGFR2, BRAF, RET, FGFR3, ROS1, EGFR, NTRK1, RAFI, MET, NTRK3, ERBB2, FGFR1, PDGFRA, NTRK2, and NRG1) (Figure 1A). Gastrointestinal cancer types had the highest frequencies of kinase rearrangements detected: cholangiocarcinoma (CCA; 6.1%), liver (4.9%) and gastroesophageal cancers (4.3%). GOF rearrangements were also detected in genes encoding transcription factors (TMPRSS2-ERG and EWSR1-FLI1 / ATF1 / WT1 fusions, rearrangements of AR, MYC, CTNNB1, MYB, ESRI). Loss-of-function (LOF) rearrangements predicted to truncate tumor suppressor genes, including DNA repaircomponents and cell cycle regulators, were even more prevalent. 3,648 (6.8%) Liquid biopsy had at least one gain-of-function rearrangement, 4,428 (8.2%) Liquid biopsy had at least one loss-of-function rearrangement detected, and 699 (1.3%) harbored both types (Figure IB). The frequency of rearrangement detection differed across cancer types. Cancer types with higher prevalence of GOF rearrangements included cancers with canonical fusion drivers: prostate cancer (19%), bladder (5.5%), and CCA (6.4%), as well as cancer types with abundant amplifications like liver (7.1%) and gastroesophageal (6.6%). Cancer types with lower detection rates of pathogenic rearrangements included pancreas (6.0%), endometrial (5.5%), kidney (5.3%), and thyroid (4.0%), some of which are also cancer types that shed less ctDNA14. Rearrangement events were detected at a median VAF of 2.2% but ranged from 0.02% for an EGFR activating rearrangement to as high as 52% for an RB 1 loss-of-function rearrangement in breast cancer. See, e.g., Table 5 and Table 7.TABLE 5TABLE 7.Gain-of-function rearrangements in oncogenes

[0042] Many of the expected enrichments in oncogenic fusions / rearrangements were observed in this cohort: ALK, RET, and ROS1 fusions in NSCLC, TMPRSS2-ERG fusions and AR rearrangements in prostate cancer, FGFR2 fusions / truncations in CCA, FGFR3 fusions / truncations in bladder and head and neck cancer, BRAF fusions in melanoma, and RET fusions in thyroid cancers (Figure 2A), see also Table 1.TABLE 1.The liquid biopsy cohort analyzed in this study, by cancer

[0043] Some oncogenic rearrangements that have been explored as pan-tumor biomarkers were detected across different cancer types. However, the clonality, i.e., the ratio between the VAF and TF of the sample, of FGFR2, BRAF, RET, and ALK rearrangements was not uniform in these cancer types. FGFR2 had high clonality in pancreatic cancer and CCA, but tended to be a minor allele (VAF / TF >25%) in gastroesophageal and colorectal cancer (CRC) (p < 0.05 for all pairwise comparisons). Pancreatic, prostate cancer, and NSCLC tended to have higher clonality BRAF rearrangements than melanoma and CRC (p < 0.001 for all comparisons). RET fusions tended to have higher clonality in NSCLC, whereas they tended to be subclonal variants in CRC (p < 0.0001) and breast cancer (p = 0.04). ALK fusions were found predominantly in NSCLC and were a major allele in 89% of cases, but tended to be a minor allele in breast cancer (p = 0.01) and CRC (p < 0.0001) (Eigure 2B). This suggests a rearrangement of a particular oncogene may not always be a truncal oncogenic driver, especially in cancer types like CRC where fusions tended to be minor alleles. Examining tissue and liquid biopsies from the same patient, GOF rearrangements in these genes that were detected in both tissue and liquid had higher median VAF / TF than those detected only in the liquid biopsy: 87% vs 5.0% for FGFR2, 30% vs 1.8% for BRAF, 84% vs 4.4% for ALK, and 50% vs 2.5% for RET (Figure 2C).

[0044] Rare gain-of-function fusions included NRG1 fusions (9), 8 of these were detected in NSCLC, and 7 were fusions to CD74. EWSR1 fusions (19) were detected fused to ATF1 (5) and FLU (5) and were detected among 5 soft tissue sarcoma, 2 Ewing sarcoma, 3 unknown primary, and 9 other cancer types (Figure ). Rearrangements in CD274 predicted to disrupt the 3’UTR, stabilize the transcript, and increase PD-L1 expressions 1,32 were detected among 42 Liquid biopsy (9 NSCLC, 6 CUP, 5 head and neck, and 5 liver, and 17 other types with N<5 each).

[0045] Potential driver rearrangements that were found predominantly in one cancer type included TMPRSS2-ERG (1,440 / 1,432 [98%] detected in prostate cancer, ALK (350 / 428 [82%] detected in NSCLC, CTNNB1 (61 / 118 [52%]) detected in CRC, and FGFR2 (85 / 285 [30%] detected in CCA) (Table 3).TABLE 3Pathogenic rearrangements in tumor suppressor genes

[0046] Although the majority of tumor suppressor gene disruptions detected by CGP are short variants (frameshift, nonsense mutations, splice site alterations), 3.1% of pathogenic variants in these genes were rearrangements (Figure 3A). The tumor suppressor genes most frequently disrupted by large-scale rearrangements in this study were: TP53 (0.7% of all Liquid biopsy), RBI (0.4%), CDKN2A (0.4%), NF1 (0.4%), STK11 (0.3%) and PTEN (0.3%). These LOF rearrangements did not show patterns of cancer type enrichment as strong as gain-of-function rearrangements. However, STK11 truncations were more common in NSCLC, RBI in breast cancer and small cell lung carcinoma, NF1 in ovarian and breast cancers, PTEN in prostate cancer, and BRCA2 in prostate, breast, and ovarian cancers, consistent with the established roles of these tumor suppressors in the oncogenesis of thecorresponding cancer types (Figure 3B). Rare but potentially clinically actionable truncating rearrangements were also detected in MTAP (35 Liquid biopsy, including 7 NSCLC and 5 CUP), and MEN1 (17 Liquid biopsy, including 8 breast cancer and 3 NSCLC).

[0047] In rare instances, rearrangements can restore function in tumor suppressor genes under therapeutic selective pressure, such as reversion events in BRCA1 / 2. Rearrangements predicted to skip BRCA2 exons containing deleterious short variants detected in the same Liquid biopsy were found in 26 Liquid biopsy (12 in breast, 11 in prostate, 1 each in ovarian, pancreas, and CUP).FGFR2 oncogenic rearrangements in cholangiocarcinoma

[0048] The overall prevalence of FGFR2 rearrangements in CCA Liquid biopsy was 5.3% (Figure 2A), lower than the 7.6% observed in tissue (p = 0.004). However, among Liquid biopsy samples with TF >1% (525 / 1,215; 43%), the prevalence of 8.4% was comparable to tissue (Figure 4A). FGFR2 fusions had breakpoints inside intron 17 or close to its junctions. Consistent with previous reports, BICC1, which resides near FGFR2 on chromosome 10, was the most common fusion partner gene (26% of FGFR2 fusions), but was only one of 34 partner genes found (Figure 4B). This mirrors the distribution observed in tissue biopsies (Figure 4C) and reported in the AACR GENIE database37.

[0049] Of 85 FGFR2 pathogenic rearrangements, 53 (62%) were fusions and 32 (38%) were truncations or deletions of exon 1823,38, all of which are predicted to encode a FGFR2 receptor that retains the kinase domain but lacks the regulatory C-terminal tail. This was somewhat higher than the relative prevalence of FGFR2 truncations in tissue (Figure 4D). The median VAF / TF for these two types of rearrangements was similar and close to 50% (51% and 43%, respectively). Truncations were more likely to be found at lower allele frequency (p = 0.02). However, 25% of FGFR2+ Liquid biopsy had multiple FGFR2 rearrangement events detected, versus 14% of tissue biopsies, and the samples with multiple events tended to have fusions and truncations present together.

[0050] In CCA and CUP paired samples from the same patient, the sensitivity of Liquid biopsy to detect FGFR2 rearrangements detected in tissue was 92% (12 / 13, 95% CI: 67- 99%). The TF of the Liquid biopsy that did not detect the FGFR2 variant from tissue was 0.5%. The 2 samples with detection in liquid but not tissue had subclonal rearrangements with VAF / TF 0.003% and 0.73%. The negative predictive value (NPV) of CCA Liquid biopsy samples was 99% (189 / 190, 95% CI: 97-99%) (Figure 4F).

[0051] Among 16 Liquid biopsy where mutations associated with acquired resistance to FGFR inhibitors were detected, 14 also detected the driver FGFR2 fusion or truncation, 1 harbored a C382R mutation in FGFR2 functioning as a driver39 (its VAF was 24% while the resistance mutation VAFs ranged from 0.26-3.3%), and 1 Liquid biopsy had no FGFR2 driver detected (the mutation’s VAF was 0.13% and it was the sole variant detected in the sample). In total, an FGFR2 driver variant was detected in 94% (15 / 16) of samples where it was expected based on the presence of resistance mutations (Figure 4G).Driver fusion detection in non-small cell lung cancer

[0052] The prevalence of ALK and RET fusions in NSCLC Liquid biopsy was 1.7% and 0.6%, respectively (Figure 2A), which was lower than the prevalence detected in tissue: 2.2% and 0.7% (p = 0.0002; 0.05). However, the prevalence of these fusions in the 6,805 / 15,534 (44%) of Liquid biopsy with TF >1% was more compatible with tissue: 1.9% and 0.7% (Figure 5A). ROS1 fusion detection was comparable to tissue regardless of TF in this cohort (0.5% in tissue, 0.4% in Liquid biopsy, p= 0.23). EML4 accounted for 87% of ALK fusion partners (30 unique genes); KIF5B (76%) and CCDC6 (13%) of RET fusion partners (8 unique genes); and CD74 (45%) and EZR (27%) of ROS1 fusion partners (10 unique genes). Tissue showed similar partner distributions (Figure 5B).

[0053] ALK, RET, and ROS1 fusions tended to be a major allele in NSCLC. Notably, their VAF / TF ratio was lower when an EGFR driver mutation was also present in the sample (Figure 5C). This finding could reflect fusions appearing as acquired resistance to EGFR inhibitors40,41, or the possible presence of multiple primaries42.

[0054] Of 51 Liquid biopsy with mutations associated with acquired resistance to ALK inhibitors, 47 (92%) also detected the ALK driver rearrangement (Figure 5D). In 62 patients with an ALK fusion detected in tissue biopsy and a Liquid biopsy collected, Liquid biopsy detected the ALK fusion in 42 cases (68% sensitivity). However, in the Liquid biopsy with TF >1%, sensitivity was 95% (20 / 21 concordantly detected, see Table 6). Similar patterns were observed for RET (23 RET+ tissue pairs) and ROS1 (19 ROS1+ tissue pairs) fusion detection (Figure 8). The sensitivity at several TF thresholds was examined in these NSCLC pairs. Sensitivity was 57% (95% confidence interval [95% CI] 47-66%) if no threshold was applied, and rose sharply to 92% (95% CI: 79-97%) even at the lower threshold of TF >0.5% (Figure 9). Frequency of TF >1% across different cancer types is provided in Table 8.TABLE 6TABLE 8.Pathogenic rearrangements in prostate cancer

[0055] The prevalence of TMPRSS2-ERG fusions in prostate cancer Liquid biopsy was 12% (Figure 2A), which was lower than the 28% rate in tissue (p = 2E-220). Among the 4,148 / 9,811 (42%) of Liquid biopsy with TF >1%, the prevalence was more comparable to tissue: 25% (Figure 6A). BRAF rearrangements were also identified at a similar rate (-1.5%) in tissue and Liquid biopsy with TF >1%. Rearrangements in the androgen receptor (AR) gene are a type of acquired resistance to androgen deprivation therapy or AR inhibitors.Consistent with this, we found the prevalence of AR rearrangements in Liquid biopsy, which are often collected after androgen deprivation therapy exposure, was dramatically higher than in our tissue cohort (4% of all Liquid biopsy, 9% of Liquid biopsy with TF >1%, 0.5% in TBx, p =3E-112) (Figure 6A). While TMPRSS2-ERG fusions and BRAF rearrangements had a median VAF / TF of 24% and 39%, respectively, AR rearrangements were subclonal events (median VAF / TF 1.5%), consistent with their role as acquired resistance, which is often heterogeneous and polyclonal (Figure 6B). Among 3,054 prostate cancer Liquid biopsy with evidence of castrate-resistant AR variants, 419 (14%) had activating AR rearrangements. Of those, 154 (37%) were the sole detectable AR variant in the sample (Figure 6C).

[0056] In 96 patients with TMPRSS2-ERG fusion detected in tissue biopsy and a Liquid biopsy collected, Liquid biopsy detected the ERG fusion in 52 cases (54% sensitivity). However, in the Liquid biopsy with TF >1%, sensitivity was 87% (46 / 53 concordantly detected) versus 14% (6 / 43) in TF <1% (Figure 8).Pathogenic rearrangements in colorectal cancer

[0057] CRC had a high overall prevalence of pathogenic rearrangements (5.4% of Liquid biopsy with GOF rearrangements, 8.6% with LOF, 1% with both) (Figure 1). However, some of the oncogenic rearrangements tended to be detected as minor alleles (Figure 2B).Examining the clonality of rearrangements prevalent in CRC, CTNNB1, TP53, PTEN, APC, NTRK1, and SOX9 tended to be major alleles (median VAF / TF >25%), while GOF rearrangements in kinases (MET, ROS1, ALK, FGFR2 / 3, RAFI, EGFR, BRAF, RET) and LOF rearrangements in DNA repair genes (BRCA2, ATR, ATM) often represented subclones (Figure 6D). MSLH CRC tumors have been reported to be enriched for targetable kinase fusions, but MSLH samples accounted for only 19 / 493 (3.9%) of the rearrangements in CRC liquid biopsies.

[0058] Since some of the kinase rearrangements potentially represent acquired resistance to anti-EGFR antibody therapy, we compared the prevalence of these rearrangements in Liquid biopsy with a clonal KRAS / NRAS mutation (KRAS-positive) versus Liquid biopsy with no clonal KRAS / NRAS / BRAL mutations (KRAS-negative, from patients who may have been treated with anti-EGLR antibody therapy prior to Liquid biopsy collection) in Liquid biopsy with TE >1% (Eigure 6E). Activating rearrangements in MET, EGFR, BRAF, CDK12, and MYC were significantly more prevalent in KRAS-negative Liquid biopsy (FDR < 0.05). Other kinase genes more often rearranged in KRAS-negative Liquid biopsy were FGFR2 / 3, MET, RET, and BRAFNTRK1. The only rearrangement significantly enriched in KRAS- positive Liquid biopsy (FDR < 0.05) was CTNNB1. These CTNNB1 activating rearrangements, which are predicted to excise exon 3 and disrupt a degron motif and stabilize the b -catenin transcription factor, and we queried whether they co-occur with mutations in APC, another Wnt / b -catenin pathway component frequently mutated in CRC. CTNNB1 rearrangements tended to be found in APC- wildtype samples: 6% (3 / 49) of CTNNB1- rearranged Liquid biopsy were APC-altered, versus 84% (2399 / 2,865) APC-altered samples in CRC Liquid biopsy with TF >1% overall.Discussion

[0059] Detection of genomic rearrangements by next-generation sequencing of liquid biopsies has historically been considered difficult. Several reports interrogating commercially available and laboratory developed assays have found inferior detection of genomic rearrangements in liquid biopsies compared to DNA-based tissue biopsy assays, including lower rates of detection, low concordance in matched samples, and reduced diversity of fusion gene partners.

[0060] High confidence CGP results are critical to support evidence-based care of cancer patients, but assay performance characteristics vary from manufacturer to manufacturer due to different design strategies and validation standards and the performance of one assay does not necessarily predict the accuracy of other tests using the same analyte. Well-designed DNA-based CGP platforms that can reliably detect fusion and rearrangement events must bait relevant intronic regions including in common partner genes, use hybrid-capture probes tiled at an appropriate density, sequence at a depth tailored to the application, and include an analytical pipeline that is capable of partner-gene-agnostic rearrangement calls. De novo assembly, rather than reliance on reference genomes, is especially important becausebreakpoints often feature novel sequences introduced by DNA repair. An additional consideration for Liquid biopsy in particular is that the presence of ctDNA cannot be ascertained prior to sequencing. A post-hoc estimate of the tumor content in the sample is valuable for the interpretation of a negative result. In this study, the sensitivity of the Liquid biopsy platform to detect driver rearrangements was much higher in samples with TF >1% than those with TF <1%. In contrast to some prior literature, this study demonstrated detection of a wide variety of rearrangements in Liquid biopsy, comparable prevalence of driver rearrangements in tissue and liquid biopsies when TF >1%, and distribution of fusion gene partners that resembles that of tissue biopsies.

[0061] In our study, cholangiocarcinoma was the cancer type with the highest prevalence of kinase fusions. This is a disease where there is often a lack of tissue to even make a diagnosis, and the utility of liquid biopsies to be able to reliably detect these actionable aberrations is of clinical value, given multiple approved FGFR inhibitors and available clinical trials. In parallel, the cancers of unknown primary that often present as a liver mass frequently turn out to be cholangiocarcinoma in the majority of cases. In these instances, the detection of FGFR2 fused with a common BICC1 partner not only has therapeutic potential but is diagnostic of the disease as well.

[0062] Kinase fusions remain the most actionable type of rearrangement but transcription factor fusions represent attractive, largely still untapped therapeutic targets that could be exploited using novel modalities such as targeted protein degradation. Some gain-of-function rearrangements are so typical of a particular cancer type (TMPRSS2-ERG, EML4-ALK) that they may aid in diagnosis when the site of origin of a tumor is uncertain, similar to the earlier discussion of FGFR2 and the cholangiocarcinoma.

[0063] Although generally less actionable than gain-of-function rearrangements, rearrangements that inactivate tumor suppressor genes may be overlooked biomarkers. RBI rearrangements are enriched in neuroendocrine tumors in this study and could help detect neuroendocrine transformation. STK11 loss is a marker of immunotherapy resistance in NSCLC. Tumors with BRCA1 / 2 inactivating rearrangements may be more sensitive to PARP inhibitors due to a low likelihood of reversion, but BRCA1 / 2 rearrangements may also function as reversions themselves.

[0064] Intriguingly, this study found that certain rearrangements often considered to be pantumor biomarkers are more likely to be truncal drivers in some cancer types than in others. Rearrangements in FGFR2 in CCA and pancreatic cancers, BRAF in pancreatic and prostate cancers, RET in thyroid cancers and NSCLC, and ALK in NSCLC tended to have highclonality. By contrast, in CRC these potentially targetable rearrangements tended to be minor alleles and found in KRAS-wildtype samples, which may have been collected from patients treated with EGFR monoclonal antibody (mAb) therapy, consistent with prior reports that such fusions may be resistance mechanisms to anti-EGFR therapy. Gastroesophageal cancers had frequent FGFR2 rearrangements but at variable clonality, suggesting they may sometimes be acquired or secondary events when the gene is amplified. This analysis underscores the utility of a TF estimate in Liquid biopsy as a tool to determine clonality. Further investigation into the association of clinical outcomes with the clonality of putative driver variants is warranted because heterogeneous tumors where fusion genes are a minor variant may not be as sensitive to targeted monotherapy. Beyond distinguishing truncal and acquired variants, these findings intimate that serial Liquid biopsy could be used to track changes in a tumor’ s predominant clones over time and inform treatment selection, since new clones can emerge and take over under therapeutic pressure. For detection of fusions that are acquired events, as in colorectal cancer post EGFR-blockade, Liquid biopsy serve as a more practical tool since repeated tissue biopsies are not necessarily safe, feasible, or practical. These are clinically actionable events as shown by work from Clifton and colleagues.

[0065] It has been proposed that RNA-based methods of rearrangement detection have superior sensitivity, because they do not require sequencing intronic regions, and profile highly expressed transcripts, with less ambiguity about the resultant fusion genes than DNA- based methods. While successful fusion detection using multiplex NGS of circulating tumor RNA (ctRNA) has been reported it is a more unstable analyte than RNA extracted from FFPE specimens and the workflow has not been scaled for the analytical and repeatability rigor of an FDA-approved, globally available assay. Additionally, while there is an advantage in preferentially detecting highly expressed gain-of-function rearrangements, RNA profiling may not detect loss-of-function rearrangements where the transcript becomes unstable.

[0066] There were certain limitations in this study. The cohort consisted of Liquid biopsy submitted in the course of routine clinical care, thus there may be some inherent biases. For instance, patients who test positive for a fusion driver in a tissue biopsy or a single-gene liquid biopsy test may be less likely to have a liquid biopsy submitted for CGP. A limitation in our analysis was the lack of patient information beyond cancer type, age, and gender. The analysis of rearrangements as potential resistance mechanisms is the lack ofthus lacked data on intervening treatments in these cohorts. The findings of this analysis are intended to be hypothesis-generating for future studies. Detection rates were compared between tissue and liquid biopsies, but both assays were DNA-based. This study does not include data fromRNA-based detection to compare the performance and sensitivity of the two methods. Future studies comparing DNA and RNA based hybrid capture targeted panels are warranted to address this question. When analyzing concordance, our paired analysis of sensitivity and negative predictive value for FGFR2 rearrangements was conducted using a convenience cohort of non-contemporaneously collected tissue and liquid biopsies, and reliance on tissue as standard presupposes that these rearrangements are truncal events.

[0067] In summary, this study describes the ability of liquid biopsy to detect pathogenic rearrangements. Many of these alterations are targetable kinase fusions. Liquid biopsies can report a rich, polyclonal landscape in patients with advanced, heavily treated disease. It can increase opportunities of precision medicine for patients for whom NGS of tissue may not be feasible or completed in a timely fashion. Since liquid biopsies have a faster turnaround and are non-invasive, a consideration for a liquid-first approach could also be a more practical and cost-effective consideration. Since some rearrangements are highly specific to certain cancer types, liquid biopsy could potentially be a powerful tool during diagnostic workup of advanced cancers where the site of origin is uncertain. Taken together, these results provide further evidence for liquid biopsy-based CGP by a well-designed assay to be a sensitive, pragmatic method for detection of rearrangements in solid tumors. 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Claims

CLAIMSWhat is claimed is:

1. A method of treating or delaying progression of prostate cancer in an individual, comprising:(a) detecting a TMPRSS2-ERG gene rearrangement in one or more samples from an individual having prostate cancer; and(b) administering to the individual an effective amount of a treatment that comprises an anti-cancer agent.

2. The method of claim 1, wherein the treatment includes a proteolysis targeting chimera (PROTAC) therapy.

3. The method of claim 1, wherein the treatment includes an androgen deprivation therapy (ADT).

4. The method of claim 1, wherein the one or more samples has a tumor fraction (TF) of greater than or equal to 1%.

5. The method of claim 1, wherein the TMPRSS2-ERG gene rearrangement is a gain-of-funciton rearrangement.

6. The method of claim 1, wherein the one or more samples is a liquid biopsy.

7. A method of treating or delaying progression of gastroesophageal cancer in an individual, comprising:(a) detecting a FGFR2 gene rearrangement in one or more samples from an individual having prostate cancer; and(b) administering to the individual an effective amount of a treatment that comprises an anti-cancer agent.

8. The method of claim 7, wherein the treatment includes a small molecule inhibitor therapy.

9. The method of claim 6, wherein the FGFR2 gene rearrangement is a gain-of- funciton rearrangement.

10. The method of claim 7, wherein the one or more samples is a liquid biopsy.

11. A method of treating or delaying progression of gastroesophageal cancer in an individual, comprising:(a) detecting a ERBB2 gene rearrangement in one or more samples from an individual having prostate cancer; and(b) administering to the individual an effective amount of a treatment that comprises an anti-cancer agent.

12. The method of claim 11, wherein the treatment includes a monoclonal antibody.

13. The method of claim 11, wherein the treatment includes a tyrosine kinase inhibitor.

14. The method of claim 11, wherein the ERBB2 gene rearrangement is a gain-of- funciton rearrangement.

15. The method of claim 11, wherein the one or more samples is a liquid biopsy.

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