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Purpose: We present seven cases of advanced cancer patients who initially underwent tumor testing utilizing smaller, panel-based tests, followed by a variety of therapeutic treatments which ultimately resulted in progression of their disease. These cases demonstrate the value of utilizing WES/RNA seq and characterization following disease progression in these patients and the determination of clinically targetable alterations as well as acquired resistance mutations. Materials and Methods: All patients are part of an IRB approved observational study. WES and RNA sequencing were performed, using GEM ExTra® on tumor and blood samples obtained during routine clinical care. To accurately determine somatic versus germline alterations the test was performed with paired normal testing from peripheral blood. Results: The presented cases demonstrate the clinical impact of actionable findings uncovered using GEM ExTra® in patients with advanced disease who failed many rounds of treatment. Unique alterations were identified resulting in newly identified potential targeted therapies, mechanisms of resistance, and variation in the genomic characterization of the primary versus the metastatic tumor. Conclusions: Taken together our results demonstrate that GEM ExTra® maximizes detection of actionable mutations, thus allowing for appropriate treatment selection for patients harboring both common and rare genomic alterations.

We developed and analytically validated a comprehensive genomic profiling (CGP) assay, GEM ExTra, for patients with advanced solid tumors that uses Next Generation Sequencing (NGS) to characterize whole exomes employing a paired tumor-normal subtraction methodology. The assay detects single nucleotide variants (SNV), indels, focal copy number alterations (CNA), TERT promoter region, as well as tumor mutation burden (TMB) and microsatellite instability (MSI) status. Additionally, the assay incorporates whole transcriptome sequencing of the tumor sample that allows for the detection of gene fusions and select special transcripts, including AR-V7, EGFR vIII, EGFRvIV, and MET exon 14 skipping events. The assay has a mean target coverage of 180X for the normal (germline) and 400X for tumor DNA including enhanced probe design to facilitate the sequencing of difficult regions. Proprietary bioinformatics, paired with comprehensive clinical curation results in reporting that defines clinically actionable, FDA-approved, and clinical trial drug options for the management of the patient's cancer. GEM ExTra demonstrated analytic specificity (PPV) of > 99.9% and analytic sensitivity of 98.8%. Application of GEM ExTra to 1,435 patient samples revealed clinically actionable alterations in 83.9% of reports, including 31 (2.5%) where therapeutic recommendations were based on RNA fusion findings only.

Background: Immune-oncology (I-O) drugs show promise across multiple tumor types, and several biomarkers (BM) predict responsiveness to I-O therapy. In this descriptive study of clinical lab experience (2018-2021), we investigated the prevalence of genomic BMs associated with sensitivity and resistance to I-O drugs across solid tumors. Methods: The GEM ExTra® assay was used to exome-sequence 2,359 paired samples at 180X and 400X coverage for germline and tumor DNA respectively. Reportable alterations were single base substitutions, indels, copy number alterations, fusions, alternate transcripts, as well as tumor mutational burden (TMB) and microsatellite instability (MSI) status. For I-O sensitive BMs we recorded MSI-High status, TMB-High (> 10 mut/Mb) status, and mutations in POLE/POLD1, MLH1, MSH2/3/6, PMS1/2, PD-L1/-L2, CTLA4, CD28, ARID2, and PBRM1. For I-O resistance BMs, IDO1 amplification and mutations in B2M, JAK1/2, IDO1, KRAS and STK11 were tallied. Results: I-O sensitive BMs varied from 0% to 58% (results in Table 1 for selected tumor types). Overall, TMB-High was in 6% of samples and MSI-High in 3%; all MSI-High were also TMB-High. In the 46% of renal cell carcinoma samples with I-O-sensitive BMs, PBRM1 mutation was common (94%). In 3 TMB-High endometrial samples, POLE/POLD1 was mutated, indicative of an ultra-mutated phenotype. Of note, 35% of colorectal cancer and 8% of melanoma samples with I-O sensitive mutations also had loss-of-function mutations in JAK1/2 and B2M, suggestive of I-O resistance. In non-small cell lung cancer, co-mutation of STK11 and KRAS, suggesting inferior response to I-O therapy, was present in 4% of samples with I-O BMs. IDO1 amplification was present in less than 1% of entire cohort. Conclusions: Our study found I-O sensitive BMs in common and in rare aggressive cancers. The GEM ExTra assay can stratify cancer patients for likely responsiveness to immunotherapy. Table 1. Immune-oncology sensitive biomarkers observed across select tumors Solid tumor type % of samples with signature All (n = 2,360) 13% Melanoma (n = 50) 54% Other skin cancers (n = 13) 62% Renal cell carcinoma (n = 200) 46% Urothelial (n = 86) 22% Endometrial (n = 88) 20% Gastro-intestinal (n = 360) 12% Sarcoma (n = 90) 11% Prostate (n = 151) 6% Lung (n = 100) 4% Breast (n = 297) 2% Central nervous system (n = 60) 0% Citation Format: Pawan Noel, David W. Hall, Sameer S. Udhane, Min Wang, Fadel S. Alyaqoub, Szabolcs Szelinger, Audrey A. Ozols, Janine R. LoBello, Frederick L. Baehner, Gargi D. Basu. Comprehensive genomic profiling to identify biomarkers predictive of response to immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1263.

1096 Background: The use of targeted therapies identified using genetic and genomic approaches is now routine in breast cancer (BC). In this clinical lab experience study the frequency of actionable somatic alterations in DNA repair pathway genes associated with the use of PARP inhibitors (PARPi) is described. Methods: BC samples were sequenced with the Oncomap ExTra assay, which uses whole-exome DNA sequencing with germline subtraction to detect somatic single base substitutions, indels, and copy number alterations, and RNA sequencing to detect gene fusions. Clinically actionable alterations were defined as associated with FDA approved drugs or clinical trial enrollment. Here, the focus is on 49 repair genes associated with PARPi response: ARID1A, ATM, ATR, ATRX, BAP1, BARD1, BLM, BRCA1/2, BRIP1, CDK12, CHEK1/2, EPCAM, ERCC1/2/3/4/5, FANCA/C/D2/E/F/G/I/L/M, MLH1, MRE11A, MSH2/6, MUTYH, NBN, PALB2, PMS2, PPP2R2A, PTEN, RAD21/50/51/51B/51C/51D/52/54L, XRCC1/2/3. Results: Of 1103 BCs, 246 (22.3%) had mutations in repair genes; 69 (6.3%) were in BRCA1/2. Repair gene mutations were less common in HER2+ cancers (n=27, 14.3%) compared to HR+ HER2- (n=156, 23.9%) or TN cancers (n=49, 26.1%) (p+ cancers (p- germline BRCA1/2 mutated BC patients. Recent evidence suggests somatic BRCA1/2 mutations predict PARPi benefit (Tung, NM. J Clin Oncol 2020). In addition to BRCA1/2 alterations, our study also highlights the importance of alterations in other DNA repair genes associated with response to PARPi. Trials are ongoing to determine if these genes predict for PARPi benefit.[Table: see text]

109 Background: Gastrointestinal cancers (GIC) account for 26% of global cancer incidence and 35% of cancer-related deaths. We investigated the molecular landscape and therapeutic targets across 18 types of GIC using whole exome (WES) and whole transcriptome sequencing (WTS). Methods: GEM ExTra assay was performed on 603 paired samples (ages 18-90 years, median = 61 years). Targeted sequence coverage was 180X for germline DNA and 400X for tumor DNA. Reportable somatic alterations included single base substitutions, indels, Copy Number Alterations, gene fusions, alternate transcripts, as well as tumor mutational burden (TMB) and microsatellite instability (MSI) status. Germline subtraction identified somatic-specific alterations. Results: Analysis of 603 GIC patient samples, including esophageal, gastric cancer (GC), biliary tract (BT), pancreatic cancer (PC), colorectal cancer (CRC), and other cancers, identified 434 actionable targets. The median number of alterations was 3 per GIC patient. The 5 most common actionable alterations were in APC, KRAS, CDKN2A, ARID1A and PIK3CA. Activation of Wnt signaling was found in 264/603 (44%), with the majority being in CRC cases. Alterations in cell cycle genes including CDKN2A, CDK4/6 and others were noted in 129/603 (21%) cases, with the majority in PC, suggesting benefit from CDK4/6 inhibitors. Activation of PI3K/PTEN/Akt/mTOR pathway was noted in 105/603 (17%), with the majority harbored in CRC, suggesting benefit from targeting this pathway. ERBB2 amplification and mutations were noted in 22/603 (4%) across different GIC tumor types. Alterations in homologous recombination genes predicting platinum and PARP inhibitor response was noted in 181/603 (30%) samples distributed across GIC subtypes. KRAS (G12C) mutation was found in 7% of all KRAS mutations across GIC subtypes, thus allowing patients to enroll in clinical trials with G12C-specific inhibitors. The majority of cases with MSI- and TMB-high status were identified in GC and CRC tumors and may be predictive of response to immunotherapy. WTS identified actionable fusions, including FGFR1/2/3 and novel NRG1 fusions in BT cancers. Conclusions: Our study revealed actionable targets used in patient selection for precision therapies, in addition to other mutational profiles of clinical significance. Overall, comprehensive genomic profiling enabled detection of established and novel actionable alterations, including fusions, which may have gone undetected using hotspot panels.

3628 Background: Fusions and translocations account for 20% of cancer mortality globally. Maximizing their detection enhances the utility of precision medicine for various solid and hematologic cancers. Practice guidelines stress the importance of RNA sequencing. Novel assay techniques employing a comprehensive genomic profiling approach, including RNA sequencing, yield information beyond conventional DNA next generation sequencing (NGS) alone. Methods: Tumor samples (N = 1517) were assayed combining whole transcriptome (RNA) sequencing, whole exome (DNA) sequencing, and comparison of tumor sequence vs. paired normal DNA. Results were analyzed to determine the frequency of rare and common RNA fusion and variant detection. Findings were mapped to a knowledge-base of targeted treatment options. Results: Analysis detected 79 (5.2%) actionable fusions and 15 (1%) transcript variants across major solid and heme-based malignancies. Notably, we observed actionable transcript variants that are not detectable at the DNA level including: EGFRvIII, EGFRvIVa and EGFRvIVb in GBM; ARv7 in prostate, and METe14 in TNBC. Many fusion cases (42%, n = 33) had no other actionable molecular abnormalities. Novel fusions included: SLC12A/ROS1 in low-grade spindle cell neoplasm with myogenic differentiation, KANK1/NTRK2 in ganglioneuroblastoma, ETV6/NTRK3 in metastatic mammary analogue secretory carcinoma, FGFR1/SCT in germ cell tumor, ZNF33B/RET fusion in GBM, SH3BP4/ERBB4 and EML4/ALK in RCC, VTCN1/NRG1 in pancreatic cancer, and AGRN/NRG1 in cholangiocarcinoma. More common actionable fusion events included: EML4/ALK in NSCLC, KIAA1549/BRAF in pilocytic astrocytoma, FGFR2 and FGFR3 in cholangiocarcinoma and urothelial cancers and ESR1 in endocrine therapy-resistant breast cancers. The fusion events detected in heme-based malignancies included MLLT10 and MLLT4 in AML, BCR/ABL in leukemias, TCF3/PBX1 in B cell ALL, NPM1/ALK in ALCL, and novel fusion CIITA/CD274 in DLBCL. All RNA fusions and transcript variants found were matched to FDA-approved or investigational treatment options. Conclusions: Maximizing the rate of variant detection for targeted therapy relies on precise identification of common and rare fusion events. Without the addition of RNA sequencing, 15 transcript variants in our cohort would have been missed and 33 of the fusions may have gone undetected by conventional DNA NGS testing, resulting in zero targeted treatment options for this vulnerable population. Further use of comprehensive genomic profiling is vital to optimizing cancer care.