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Purpose Deriving links between imaging and genomic markers is an evolving field. 2-[18F]FDG PET/CT (18F-fluorodeoxyglucose positron emission tomography–computed tomography) is commonly used for cancer imaging, with maximum standardized uptake value (SUVmax) as the main quantitative parameter. Tumor mutational burden (TMB), the quantitative variable obtained using next-generation sequencing on a tissue biopsy sample, is a putative immunotherapy response predictor. We report the relationship between TMB and SUVmax, linking these two important parameters. Methods In this pilot study, we analyzed 1923 patients with diverse cancers and available TMB values. Overall, 273 patients met our eligibility criteria in that they had no systemic treatment prior to imaging/biopsy, and also had 2-[18F]FDG PET/CT within 6 months prior to the tissue biopsy, to ensure acceptable temporal correlation between imaging and genomic evaluation. Results We found a linear correlation between TMB and SUVmax (p max, whereas age, gender, and tumor organ did not. Conclusion Our observations link SUVmax in readily available, routinely used, and noninvasive 2-[18F]FDG PET/CT imaging to the TMB, which requires a tissue biopsy and time to process. Since higher TMB has been implicated as a prognostic biomarker for better outcomes after immunotherapy, further investigation will be needed to determine if SUVmax can stratify patient response to immunotherapy.

Background Invasive lobular carcinoma (ILC) as a disease entity distinct from invasive ductal carcinoma (IDC) has merited focused studies of the genomic landscape, but those to date are largely limited to the assessment of early-stage cancers. Given that genomic alterations develop as acquired resistance to endocrine therapy, studies on refractory ILC are needed. Patients and methods Tissue from 336 primary-enriched, breast-biopsied ILC and 485 estrogen receptor (ER)-positive IDC and metastatic biopsy specimens from 180 ILC and 191 ER-positive IDC patients was assayed with hybrid-capture-based comprehensive genomic profiling for short variant, indel, copy number variants, and rearrangements in up to 395 cancer-related genes. Results Whereas ESR1 alterations are enriched in the metastases of both ILC and IDC compared with breast specimens, NF1 alterations are enriched only in ILC metastases (mILC). NF1 alterations are predominantly under loss of heterozygosity (11/14, 79%), are mutually exclusive with ESR1 mutations [odds ratio = 0.24, P 20 mutations/mb; P

Background Estrogen receptor-positive (ER-positive) metastatic breast cancer is often intractable due to endocrine therapy resistance. Although ESR1 promoter switching events have been associated with endocrine-therapy resistance, recurrent ESR1 fusion proteins have yet to be identified in advanced breast cancer. Patients and methods To identify genomic structural rearrangements (REs) including gene fusions in acquired resistance, we undertook a multimodal sequencing effort in three breast cancer patient cohorts: (i) mate-pair and/or RNAseq in 6 patient-matched primary-metastatic tumors and 51 metastases, (ii) high coverage (>500×) comprehensive genomic profiling of 287–395 cancer-related genes across 9542 solid tumors (5216 from metastatic disease), and (iii) ultra-high coverage (>5000×) genomic profiling of 62 cancer-related genes in 254 ctDNA samples. In addition to traditional gene fusion detection methods (i.e. discordant reads, split reads), ESR1 REs were detected from targeted sequencing data by applying a novel algorithm (copyshift) that identifies major copy number shifts at rearrangement hotspots. Results We identify 88 ESR1 REs across 83 unique patients with direct confirmation of 9 ESR1 fusion proteins (including 2 via immunoblot). ESR1 REs are highly enriched in ER-positive, metastatic disease and co-occur with known ESR1 missense alterations, suggestive of polyclonal resistance. Importantly, all fusions result from a breakpoint in or near ESR1 intron 6 and therefore lack an intact ligand binding domain (LBD). In vitro characterization of three fusions reveals ligand-independence and hyperactivity dependent upon the 3′ partner gene. Our lower-bound estimate of ESR1 fusions is at least 1% of metastatic solid breast cancers, the prevalence in ctDNA is at least 10× enriched. We postulate this enrichment may represent secondary resistance to more aggressive endocrine therapies applied to patients with ESR1 LBD missense alterations. Conclusions Collectively, these data indicate that N-terminal ESR1 fusions involving exons 6–7 are a recurrent driver of endocrine therapy resistance and are impervious to ER-targeted therapies.

Background Genomic changes that occur in breast cancer during the course of disease have been informed by sequencing of primary and metastatic tumor tissue. For patients with relapsed and metastatic disease, evolution of the breast cancer genome highlights the importance of using a recent sample for genomic profiling to guide clinical decision-making. Obtaining a metastatic tissue biopsy can be challenging, and analysis of circulating tumor DNA (ctDNA) from blood may provide a minimally invasive alternative. Patients and methods Hybrid capture-based genomic profiling was carried out on ctDNA from 254 female patients with estrogen receptor-positive breast cancer. Peripheral blood samples were submitted by clinicians in the course of routine clinical care between May 2016 and March 2017. Sequencing of 62 genes was carried out to a median unique coverage depth of 7503×. Genomic alterations (GAs) in ctDNA were evaluated and compared with matched tissue samples and genomic datasets of tissue from breast cancer. Results At least 1 GA was reported in 78% of samples. Frequently altered genes were TP53 (38%), ESR1 (31%) and PIK3CA (31%). Temporally matched ctDNA and tissue samples were available for 14 patients; 89% of mutations detected in tissue were also detected in ctDNA. Diverse ESR1 GAs including mutation, rearrangement and amplification, were observed. Multiple concurrent ESR1 GAs were observed in 40% of ESR1-altered cases, suggesting polyclonal origin; ESR1 compound mutations were also observed in two cases. ESR1-altered cases harbored co-occurring GAs in PIK3CA (35%), FGFR1 (16%), ERBB2 (8%), BRCA1/2 (5%), and AKT1 (4%). Conclusions GAs relevant to relapsed/metastatic breast cancer management were identified, including diverse ESR1 GAs. Genomic profiling of ctDNA demonstrated sensitive detection of mutations found in tissue. Detection of amplifications was associated with ctDNA fraction. Genomic profiling of ctDNA may provide a complementary and possibly alternative approach to tissue-based genomic testing for patients with estrogen receptor-positive metastatic breast cancer.

Background Recognition of rare molecular subgroups is a challenge for precision oncology and may lead to tissue-agnostic approval of targeted agents. Here we aimed to comprehensively characterize the clinical, pathological and molecular landscape of RET rearranged metastatic colorectal cancer (mCRC). Patients and methods In this case series, we compared clinical, pathological and molecular characteristics of 24 RET rearranged mCRC patients with those of a control group of 291 patients with RET negative tumors. RET rearranged and RET negative mCRCs were retrieved by systematic literature review and by taking advantage of three screening sources: (i) Ignyta's phase 1/1b study on RXDX-105 (NCT01877811), (ii) cohorts screened at two Italian and one South Korean Institutions and (iii) Foundation Medicine Inc. database. Next-generation sequencing data were analyzed for RET rearranged cases. Results RET fusions were more frequent in older patients (median age of 66 versus 60 years, P = 0.052), with ECOG PS 1-2 (90% versus 50%, P = 0.02), right-sided (55% versus 32%, P = 0.013), previously unresected primary tumors (58% versus 21%, P

Background cHCC-CCA is a rare primary liver carcinoma, with histologic features of both hepatocellular carcinomas (HCC) and liver cholangiocarcinomas (CCA). In order to elucidate their shared and distinctive biology, we used CGP to compare the genomic alterations (GA) of cHCC-CCA with those of HCC and CCA. Methods 1269 HCC, 3965 CCA and 44 cHCC-CCA were assayed by hybrid capture based CGP on 0.8-1.1 Mb of the coding genome to identify GAs in exons and select introns in up to 404 genes, tumor mutational burden (TMB), microsatellite status (MSI) and % monoallelic genome (gLOH). Utilizing the significant differences in GAs, biomarkers, and demographics between HCC and CCAs (Fischer exact test, FDR 10% shown, Table), we built a random forest-based machine learning model to rank a cHCC-CCA specimen in the CCA-HCC spectrum (Out of Bag error rate = 12.6%, AUC = 0.94). Results Biomarkers exclusively associated with one disease type included IDH1 (15% in CCA vs 1% in HCC, p = 1e-57), TERT (4% in CCA vs 47% in HCC, p = 2e-273) and Hepatitis B virus (HBV, 0.8% in CCA vs 8.5% in HCC, p = 9e-42). 10/44 cHCC-CCA were classified as CCA-like (IDH1 = 4/10, HBV = 0/10, TERT = 0/10, median TMB = 0.9) and 21/44 cases as HCC-like (IDH1=0/21, HBV=5/21, TERT = 15/21, median TMB = 4). 13/44 cHCC-CCA featured ambiguous/conflicting CGP findings (IDH1=0/13, HBV=1/13, TERT = 0/13, median TMB = 4). 5/13 cHCC-CCA had a computational tumor purity Table . 677PD HCC CCA GAs TERT, CTNNB1, MYC CDKN2A/B, KRAS, ARID1A, IDH1, BAP1, PBRM1, FGFR2 Biomarkers HBV +, low gLOH, intermediate TMB HBV -, high gLOH, low TMB Demographics Male, Younger patients, African & East Asian ancestry Female, Older patients, European ancestry Conclusions Using a machine learning model, the prevalence and mutual exclusivity of IDH1/2, FGFR2, TERT, CTNNB1 and other key GAs, suggest that the majority of cHCC-CCA cases fall into molecular subgroups either similar to CCA or HCC. These findings suggest that cHCC-CCA is not a true disease entity but may be a conglomerate of transformed CCA and HCC. Legal entity responsible for the study Foundation Medicine. Funding Foundation Medicine. Disclosure K. Murugesan: Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. M. Javle: Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: Rafael Pharmaceuticals; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: Incyte; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: Pieris Pharmaceuticals; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: Merck; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: Merck Serono; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: Novartis; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: Seattle Genetics; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: QED Therapeutics; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: Bayer; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Leadership role, Research grant / Funding (self), Research grant / Funding (institution), Travel / Accommodation / Expenses, Shareholder / Stockholder /: BeiGene. A.B. Schrock: Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. N. Ngo: Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. G.M. Frampton: Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. B.M. Alexander: Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. V.A. Miller: Full / Part-time employment: Foundation Medicine. T. Bekaii-Saab: Advisory / Consultancy: Amgen; Advisory / Consultancy: Bristol-Myers Squibb; Advisory / Consultancy: Lilly; Advisory / Consultancy: Regeneron; Advisory / Consultancy: AstraZeneca; Advisory / Consultancy: Celgene; Advisory / Consultancy: NCCN; Advisory / Consultancy: Genentech/Roche; Advisory / Consultancy: Bayer; Advisory / Consultancy: Taiho Pharmaceutical; Advisory / Consultancy: Boehringer Ingelheim; Advisory / Consultancy: Sirtex Medical; Advisory / Consultancy: Pfizer; Advisory / Consultancy: Glenmark; Advisory / Consultancy: Ipsen; Advisory / Consultancy: AbbVie; Advisory / Consultancy: Incyte; Advisory / Consultancy: Imugene; Advisory / Consultancy: Immuneering. L.A. Albacker: Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. J.S. Ross: Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Foundation Medicine. S.M. Ali: Shareholder / Stockholder / Stock options, Licensing / Royalties, Full / Part-time employment: Foundation Medicine; Advisory / Consultancy: Revolution Medicines; Leadership role: Incysus; Shareholder / Stockholder / Stock options: Exelixis; Shareholder / Stockholder / Stock options: Blueprint Medicines; Shareholder / Stockholder / Stock options: Agios; Shareholder / Stockholder / Stock options: Genocea Biosciences.

Background Little is known about the prognostic effect of TMB-H among patients with less common cancers who did not receive an immunotherapy (IO). Methods The de-identified Flatiron Health-Foundation Medicine (FMI) Clinico-Genomic Database was used to select patients (pts) with any of 10 solid cancers (Table). 109 Pts with confirmed microsatellite instability-high (MSIH) cancers were excluded, of which 101 pts were endometrial cancer. TMB-H was defined as ≥ 10 mutations per megabase (Mut/Mb) with an additional analysis using a cutoff of 13 Mut/Mb. For overall survival (OS) analysis, Pts with IO were excluded if start of IO earlier than or equal to FMI report date (69 pts), or censored if start of IO later than FMI report date (243 pts). OS was analyzed using Kaplan-Meier method and Cox proportional hazard model, adjusting for age, gender, cancer types, practice type and albumin. A non-inferiority test of TMB-H having longer OS than TMB-low (-L) was carried out with a prespecified hazard ratio (HR) of 0.75. Results Of the 2,589 pts (table), average age at diagnosis was 64 years and 65% were female. Median TMB was 2.6 Mut/Mb overall, ranged from 1.7 (Meso, salivary, thyroid) to 8.7 (SCLC) Mut/Mb. Overall 12.8% were TMB-H with the highest in SCLC (40.0%) and lowest in meso (1.2%). The adjusted HR (AHR) of TMB-H vs. -L was 0.94 (95% CI: 0.77-1.13) for OS from FMI report date, which met the prespecified threshold for non-inferiority by rejecting the null hypothesis. The AHR was 0.84 (0.67-1.05) using alternative cutoff of 13 Mut/Mb. Comparable results were observed when including MSI-H pts and calculating OS from 1st observed antineoplastic treatment date. Table: 1877PD . N TMB-H OS (month, 95%CI) HRadjust Padjust n % TMB-H TMB-L Total 2,589 332 12.8 8.4 (7.4; 11.4) 10.5 (9.5; 11.5) 0.94 (0.77; 1.13) 0.491 SCLC 305 122 40.0 6.4 (5.4; 7.5) 7.4 (5.5; 10.5) 1.03 (0.74; 1.44) 0.863 Neuroendocrine 164 48 29.3 10.4 (6.4; NA) 6.4 (4.5; 10.5) 0.83 (0.48; 1.44) 0.506 Cervical 114 17 14.9 NA (6.4; NA) 7.4 (4.4; 11.5) 0.32 (0.08; 1.31) 0.113 Anal 125 17 13.6 7.4 (2.5; NA) 7.5 (5.5; 15.4) 0.84 (0.40; 1.79) 0.659 Vulvar 30 4 13.3 8.5 (0.5; NA) 6.5 (2.5; NA) 1.18 (0.22; 6.29) 0.848 Salivary 169 22 13.0 4.5 (3.5; NA) 15.5 (10.5; 21.5) 1.20 (0.48; 2.99) 0.691 Endometrial 590 66 11.2 11.4 (8.5; 26.5) 13.5 (11.5; 15.4) 1.15 (0.75; 1.75) 0.522 Biliary 706 28 4.0 11.5 (7.4; NA) 8.4 (7.4; 10.4) 0.65 (0.35; 1.19) 0.162 Thyroid 223 6 2.7 10.2 (1.5; NA) 27.5 (21.5; NA) 1.64 (0.39; 6.96) 0.502 Meso 163 2 1.2 NA 12.5 (8.5; 15.5) - 0.997 Conclusions There is a wide range of TMB among these cancers. Non-inferiority testing and HR estimates comparing OS for TMB-H (≥10 Mut/Mb) vs. -L did not support an effect of TMB on OS in the absence of IO for these cancers. Further research is needed to explore whether the prognostic effect of TMB varies by tumor type or threshold. Legal entity responsible for the study Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Funding Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Disclosure D. Backenroth: Shareholder / Stockholder / Stock options, Full / Part-time employment: Flatiron Health Inc. C. Shao: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co. G. Li: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. L. Huang: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co.. S.K. Pruitt: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. E. Castellanos: Full / Part-time employment: Flatiron Health Inc.. G.M. Frampton: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. K.R. Carson: Full / Part-time employment: Flatiron Health Inc.. T. Snow: Full / Part-time employment: Flatiron Health Inc.. G. Singal: Full / Part-time employment: Foundation Medicine. D. Fabrizio: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. B.M. Alexander: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. F.J. Jin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. W. Zhou: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc..

Background The Neurotrophic Tyrosine Kinase genes, NTRK1-3 are extremely rare drivers of a wide variety of malignancies. The recent pan-cancer approval of kinase inhibitor drugs targeting NTRK has sparked interest in the frequency of NTRK rearrangements found in NSCLC. Methods Comprehensive genomic profiling (CGP) was performed on FFPE samples from 42,791 NSCLC cases. Tumor mutational burden (TMB) was determined on 0.8-1.1 Mbp of sequenced DNA and microsatellite instability (MSI) was determined on 95 loci. Results 58 (0.1%) of the NSCLC featured genomic fusions or rearrangements in the NTRK1-3 genes (Table). The ages and genders of NTRK1-3 fusion+ cases were similar to NSCLC in general and did not enrich for younger patients. NTRK fusions were highest in adenocarcinomas (67%) and squamous cell carcinomas (SCC; 9%). The average genomic alterations (GA) per NTRK1-3 altered tumor ranged from 6.1 – 8.2 GA and was higher than that reported for EGFR, ALK and ROS1 driven NSCLC. The NTRK1-3 fusions involved a wide variety of fusion partners with NTRK1- IRF2BP2 (6) and NTRK1-TPM3 (9) most frequent. The levels of TMB and frequencies of PD-L1 expression were higher than EGFR, ALK and ROS1 altered cases. The STK11 GA frequencies were similar to NSCLC in general but lower than the frequency in lung adenocarcinoma only. Table . 1549P NTRK1 NTRK2 NTRK3 Cases 47 5 6 Median age/Range 64 (22-88) 68 (65-76) 71 (63-74) Gender m/f 23/24 3/2 5/1 NSCLC Types Adenocarcinoma NSCLC NOS Large Cell Neuroendocrine SCC Sarcomatoid Large Cell 31 10 2 2 1 1 4 1 4 2 GA/tumor 6.1 8.2 6.2 TP53 55% 80% 67% KRAS 15% 0% 17% STK11 11% 20% 0% MSI High 0% 0% 0% Median TMB mut/Mb 3.5 11.3 14.4 TMB >10/20 mut/Mb 22%/7% 60%/20% 67%/33% PD-L1 Expression low/high 32%/16% (n = 19) 50%/50% (n = 2) 0%/33% (n = 3) Conclusions Although the addition of RNA sequencing may marginally increase their detection, based on this DNA-only CGP sequencing study, NTRK1-3 fusions are extremely rare in NSCLC. These NTRK1-3 fusion-driven NSCLC differ from other well-known driver associated NSCLC such as EGFR, ALK and ROS1 in their having higher GA/tumor, TMB and PD-L1 expression frequencies suggesting that immunotherapies may also be available for the care of these patients, possibly as a combination therapy. Legal entity responsible for the study Foundation Medicine. Funding Foundation Medicine. Disclosure E.S. Sokol: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. S.E. Trabucco: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. D.X. Jin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. G.M. Frampton: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J.A. Elvin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J. Vergilio: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J.K. Killian: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. N. Ngo: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. D. Lin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. S. Ramkissoon: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. E. Severson: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. S.M. Ali: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. A.B. Schrock: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J. Chung: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. P. Reddy: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. K. McGregor: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. B.M. Alexander: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment, Officer / Board of Directors: Foundation Medicine. J.S. Ross: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. All other authors have declared no conflicts of interest.