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Background We sought to determine the prevalence of germline pathogenic variants (gPVs) in unselected patients with endometrial cancer (EC), define biallelic gPVs within tumors, and describe their associations with clinicopathologic features. Methods Germline assessment of at least 76 cancer predisposition genes was performed in patients with EC undergoing clinical tumor-normal Memorial Sloan Kettering–Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) sequencing from January 1, 2015, to June 30, 2021. In patients with gPVs, biallelic alterations in ECs were identified through analysis of loss of heterozygosity and somatic PVs. Clinicopathologic variables were compared using nonparametric tests. Results Of 1625 patients with EC, 216 (13%) had gPVs, and 15 patients had 2 gPVs. There were 231 gPVs in 35 genes (75 [32%] high penetrance; 39 [17%] moderate penetrance; and 117 [51%] low, recessive, or uncertain penetrance). Compared with those without gPVs, patients with gPVs were younger (P = .002), more often White (P = .009), and less obese (P = .025) and had differences in distribution of tumor histology (P = .017) and molecular subtype (P Conclusions Of unselected patients with EC, 13% had gPVs, with 63% of gPVs in high-penetrance genes (MMR and homologous recombination) exhibiting biallelic inactivation, potentially driving cancer development. This supports germline assessment in EC given implications for treatment and cancer prevention.

The microbiome is hypothesized to have a significant impact on cancer development. In gastric cancer (GC), Helicobacter pylori is an established class I carcinogen. However, additional organisms in the intratumoral microbiome play an important role in GC pathogenesis and progression. In this study, we characterize the full spectrum of the microbes present within GC and identify distinctions among molecular subtypes.A microbiome bioinformatics pipeline that is generalizable across multiple next-generation sequencing platforms was developed. Microbial profiles for alpha diversity and enrichment were generated for 2 large, demographically distinct cohorts: (1) internal Memorial Sloan Kettering Cancer Center (MSKCC) and (2) The Cancer Genome Atlas (TCGA) cohorts. A total of 520 GC samples were compared with select tumor-adjacent nonmalignant samples. Microbiome differences among the GC molecular subtypes were identified.Compared with nonmalignant samples, GC had significantly decreased microbial diversity in both MSKCC and TCGA cohorts ( P0.05). Helicobacter , Lactobacillus , Streptococcus , Prevotella , and Bacteroides were significantly more enriched in GC samples when compared with nonmalignant tissue ( P0.05). Microsatellite instability-high GC had distinct microbial enrichment compared with other GC molecular subtypes.Distinct patterns of microbial diversity and species enrichment were identified in patients with GC. Given the varied spectrum of disease progression and treatment response of GC, understanding unique microbial signatures will provide the landscape to explore key microbial targets for therapy.

Table S2. Oncogenic/Likely-oncogenic structural variants in GBC

Purpose:Gallbladder carcinoma (GBC) is an uncommon and aggressive disease, which remains poorly defined at a molecular level. Here, we aimed to characterize the molecular landscape of GBC and identify markers with potential prognostic and therapeutic implications.Experimental Design:GBC samples were analyzed using the MSK-IMPACT (Memorial Sloan Kettering–Integrated Mutation Profiling of Actionable Cancer Targets) platform (targeted NGS assay that analyzes 505 cancer-associated genes). Variants with therapeutic implications were identified using OncoKB database. The associations between recurrent genetic alterations and clinicopathologic characteristics (Fisher exact tests) or overall survival (univariate Cox regression) were evaluated. P values were adjusted for multiple testing.Results:Overall, 244 samples (57% primary tumors and 43% metastases) from 233 patients were studied (85% adenocarcinomas, 10% carcinomas with squamous differentiation, and 5% neuroendocrine carcinomas). The most common oncogenic molecular alterations appeared in the cell cycle (TP53 63% and CDKN2A 21%) and RTK_RAS pathways (ERBB2 15% and KRAS 11%). No recurrent structural variants were identified. There were no differences in the molecular landscape of primary and metastasis samples. Variants in SMAD4 and STK11 independently associated with reduced survival in patients with metastatic disease. Alterations considered clinically actionable in GBC or other solid tumor types (e.g., NTRK1 fusions or oncogenic variants in ERBB2, PIK3CA, or BRCA1/2) were identified in 35% of patients; 18% of patients with metastatic disease were treated off-label or enrolled in a clinical trial based on molecular findings.Conclusions:GBC is a genetically diverse malignancy. This large-scale genomic analysis revealed alterations with potential prognostic and therapeutic implications and provides guidance for the development of targeted therapies.

Figure S1. Mutation signatures and altered canonical pathways in GBC.

Table S3. Therapy regimens

Table S1. Sample list (cBioPortal identifiers, ‘DMP_SAMPLE_ID’). Only the primary tumor (if available) or the earliest collected metastasis are included (n=233)

Detailed statistical results

Purpose: Gallbladder carcinoma (GBC) is an uncommon and aggressive disease, which remains poorly defined at a molecular level. Here, we aimed to characterize the molecular landscape of GBC and identify markers with potential prognostic and therapeutic implications. Experimental Design: GBC samples were analyzed using the MSK-IMPACT (Memorial Sloan Kettering–Integrated Mutation Profiling of Actionable Cancer Targets) platform (targeted NGS assay that analyzes 505 cancer-associated genes). Variants with therapeutic implications were identified using OncoKB database. The associations between recurrent genetic alterations and clinicopathologic characteristics (Fisher exact tests) or overall survival (univariate Cox regression) were evaluated. P values were adjusted for multiple testing. Results: Overall, 244 samples (57% primary tumors and 43% metastases) from 233 patients were studied (85% adenocarcinomas, 10% carcinomas with squamous differentiation, and 5% neuroendocrine carcinomas). The most common oncogenic molecular alterations appeared in the cell cycle (TP53 63% and CDKN2A 21%) and RTK_RAS pathways (ERBB2 15% and KRAS 11%). No recurrent structural variants were identified. There were no differences in the molecular landscape of primary and metastasis samples. Variants in SMAD4 and STK11 independently associated with reduced survival in patients with metastatic disease. Alterations considered clinically actionable in GBC or other solid tumor types (e.g., NTRK1 fusions or oncogenic variants in ERBB2, PIK3CA, or BRCA1/2) were identified in 35% of patients; 18% of patients with metastatic disease were treated off-label or enrolled in a clinical trial based on molecular findings. Conclusions: GBC is a genetically diverse malignancy. This large-scale genomic analysis revealed alterations with potential prognostic and therapeutic implications and provides guidance for the development of targeted therapies.

Mismatch repair deficient colon cancer is heterogeneous. Differentiating inherited constitutional variants from somatic genetic alterations and gene silencing is important for surveillance and genetic counseling.Determine the extent to which the underlying mechanism of loss of mismatch repair influences molecular and clinicopathologic features of microsatellite instability-high colon cancer.Retrospective analysis.Comprehensive cancer center.Patients with microsatellite instability-high colon cancer of stage I, II, or III.Curative surgical resection.Hypermethylation of the MLH1 promoter, biallelic inactivation, constitutional pathogenic variant, and loss of specific mismatch repair proteins.Of the 157 identified tumors with complete genetic analysis, 66% had hypermethylation of the MLH1 promoter, 18% had constitutional pathogenic variant (Lynch syndrome), 11% had biallelic somatic MMR gene pathogenic variants, and 6% had unexplained high microsatellite instability. The distribution of mismatch repair loss was as follows: MLH1 and PMS2 co-loss, 79% of the tumors; MSH2 and MSH6 co-loss, 10%; MSH6 alone, 3%; PMS2 alone, 2%; other combinations, 2%; no loss, 2%. Tumor mutational burden was lowest in MLH1- and PMS2-deficient tumors. MSH6-deficient tumors had the lowest levels of tumor-infiltrating lymphocytes, lowest MSIsensor scores, and fewest frameshift deletions. Patients with MLH1 promoter hypermethylation were significantly more likely to be older and female and to have right-colon lesions than patients with biallelic inactivation. Mutation was the most prevalent second hit in tumors with biallelic inactivation and tumors of patients with Lynch syndrome.Potential selection or referral bias, missing data for some patients, and relatively small sizes of some subgroups.Clinical characteristics of mismatch repair deficient colon cancer vary with the etiology of microsatellite instability, and its molecular characteristics vary with the affected mismatch repair protein. See Video Abstract at http://links.lww.com/DCR/B984.

Objective: The microbiome is associated with the pathogenesis and progression of disease in gastric cancer (GC). Eradication of Helicobacter pylori has reduced overall GC incidence, however, gastroesophageal cancer (GEJC) continues to increase. While there are oncologic differences between GEJC and GC, distinctions based on microbial profiles are unknown. In this study, we characterize differences in the microbial profiles of GEJC and GC. Methods: 562 patients with microsatellite stable GC (n=303) and GEJC (n=259) who had an institutional Integrated Mutation Profiling of Actionable Cancer Targets assay on the primary tumor were included in the study. A validated microbiome bioinformatics pipeline that is generalizable across multiple next generation sequencing platforms was utilized to compare microbial enrichment and alpha diversity between GC and GEJC, defined by type 1-3 Siewert classification. Results: Over 20 unique microbial species were enriched in GC when compared to GEJC, including Helicobacter and Lymphocryptovirus (Table 1). Prevotella had increased incidence in GEJC (OR:1.57,95%CI:1.02,2.41). Siewert type 2 and 3 GEJC had a significantly lower alpha diversity compared to GC. There was no significant difference in alpha diversity between GC and Siewert type 1 GEJC. Conclusion: There are distinct differences in microbial enrichment and alpha diversity between GEJC and GC. Helicobacter and Lymphocryptovirus, the genus family for Epstein Bar Virus, were noted to have the highest odds ratios in the GC group. Our findings showing the reduced incidence of microbes in GEJC which are the current targets of GC screening, prevention, and therapy, have implications in evaluating optimal preventative and treatment strategies in GEJC. Table 1. Microbes with enrichment in gastric cancer (GC) when compared to gastroesophageal cancer (GEJC) Microbes OR (95% Confidence Interval) p-value Helicobacter 85.40 (5.191, 1404.81) 0.002 Lymphocryptovirus 6.83 (2.3120,.17) 0.001 Pelagibacterium 6.01 (1.71, 21.06) 0.005 Gluconacetobacter 5.14 (1.70, 15.53) 0.004 Myxococcus 5.14 (1.70, 15.53) 0.004 Kribbella 4.48 (1.46, 13.74) 0.009 Celeribacter 3.46 (1.43, 8.37) 0.006 Halomonas 3.46 (1.43, 8.37) 0.006 Nakamurella 3.35 (1.46, 7.71) 0.004 Nitrobacter 2.91 (1.40, 6.05) 0.004 Pseudogulbenkiania 2.80 (1.30, 6.03) 0.009 Mycobacteroides 2.78 (1.33, 5.81) 0.006 Polaromonas 2.70 (1.49, 4.90) 0.001 Meiothermus 2.54 (1.41, 4.57) 0.002 Sphingopyxis 2.44 (1.33, 4.46) 0.004 Mesorhizobium 2.38 (1.32, 4.30) 0.004 Staphylococcus 2.23 (1.37, 3.62) 0.001 Thermus 2.13 (1.22, 3.70) 0.008 Mycolicibacterium 1.99 (1.29, 3.07) 0.002 Mycobacterium 1.95 (1.23, 3.08) 0.005 Lactobacillus 1.94 (1.17, 3.22) 0.01 Citation Format: Miseker Abate, Harrison Drebin, Shoji Shimada, Santosh Vardhana, Smita Sihag, Vivian E. Strong, Chad Vanderbilt. Distinct differences in microbial enrichment and diversity identified between gastric and gastroesophageal junction adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5890.

In silico approaches for next-generation sequencing (NGS) data modeling have utility in the clinical laboratory as a tool for clinical assay validation. In silico NGS data can take a variety of forms, including pure simulated data or manipulated data files in which variants are inserted into existing data files. In silico data enable simulation of a range of variants that may be difficult to obtain from a single physical sample. Such data allow laboratories to more accurately test the performance of clinical bioinformatics pipelines without sequencing additional cases. For example, clinical laboratories may use in silico data to simulate low variant allele fraction variants to test the analytical sensitivity of variant calling software or simulate a range of insertion/deletion sizes to determine the performance of insertion/deletion calling software. In this article, the Working Group reviews the different types of in silico data with their strengths and limitations, methods to generate in silico data, and how data can be used in the clinical molecular diagnostic laboratory. Survey data indicate how in silico NGS data are currently being used. Finally, potential applications for which in silico data may become useful in the future are presented.

Determining which lung cancer patients are likely to respond to immune checkpoint inhibitors (ICI) remains a crucial challenge. Existing FDA-approved biomarkers lack sensitivity and specificity for identifying treatment candidates. To overcome this problem, we present a computational biomarker for predicting ICI response directly from routine H&E stained whole slide images of the initial biopsy. To achieve this, we developed an end-to-end deep learning system (EPL-GNN) that performs hierarchical spatial modeling on whole slide images to learn both spatial and morphological features from 2.1 billion cells and output a response score for each patient. The computational biomarker was trained and evaluated on the largest reported cohort of stage 4 lung cancer patients with ICI treatment response (N=583), resulting in an AUC of 0.69 and sensitivity of 91% on the independent test cohort, which compares favorably to PD-L1 immunohistochemistry (IHC) with an AUC of 0.68 and sensitivity of 57%, and tumor mutation burden (TMB) with an AUC of 0.62. The EPL-GNN model correctly identified 81% of the patients with a negative PD-L1 IHC result as responders. Visualizations of the hierarchical spatial model revealed potential cellular patterns that correspond to ICI treatment response. In addition to the increased sensitivity achieved by the EPL-GNN model, H&E-based Computational Biomarkers offer a faster, less expensive, more objective and reproducible alternative or adjunct to existing IHC or sequencing based biomarkers.

458 Background: Microbial dysbiosis has been shown to be associated with the pathogenesis of gastric cancer (GC). However, the relationship between the GC microbiome and response to systemic therapy, such as neoadjuvant chemotherapy (NAC), is largely unknown. This study aims to explore changes in the microbiome after neoadjuvant chemotherapy, by analyzing the microbial profile of patients who received NAC and comparing differences among those with varied pathologic response to therapy. Methods: A microbiome bioinformatics pipeline using multiple next generation sequencing platforms was developed and used for analysis. GC tissue from patients who received NAC (n=101) and those who did not (n=85) were acquired at the time of surgical resection. Shannon alpha diversity plot and enrichment analyses by odds ratio were used to compare the microbial differences of the treatment cohorts. The microbial profiles of patients with pathologic response to NAC (>20% response) were characterized. Results: Of patients who received NAC, 66 (65.3%) experienced a greater than 20% response to NAC, and 35 (34.6%) demonstrated a 20% or lower response. Patients with a pathologic response to NAC were enriched for Rhizobium, Streptomyces, Comamonas, Sphingomonas, Micrococcus, Mycobacterium, Thauera, Hyphomicrobium, and Sinorhizobium (OR>4). There were no statistically significant differences in alpha diversity (p>0.05). Conclusions: Our results demonstrate that patients with a greater than 20% pathologic response to NAC have a distinct microbial enrichment compared to those with a poor pathologic response. Given the variable NAC treatment responses in GC, understanding unique microbial signatures in tumors will provide the landscape to explore key microbial contributors to GC NAC treatment response that may improve our understanding of treatment response variability among patients. [Table: see text]

222 Background: The microbiome is an important biomarker associated with the pathogenesis and progression of disease in colorectal cancer (CRC). Genetic, dietary and environmental factors have been implicated in CRC microbial dysbiosis, however geographical distinctions in the microbiome of CRC are largely unknown. In this study, we characterize distinctions in the microbial diversity and microbial enrichment of CRC specimen obtained from a Nigerian and U.S. population. Methods: A validated microbiome bioinformatics pipeline that is generalizable across multiple next generation sequencing platforms was utilized. Microbial profiles for alpha diversity and enrichment were generated for two large, geographically distinct cohorts: (1) U.S. (n=498) and (2) Nigerian (n=65) cohorts. CRC specimen from Nigeria were compared to CRC specimen from the U.S. using the same microbial bioinformatics pipeline and methodology for analysis. Microbial differences stratified based on CRC microsatellite-instability (MSI) status were identified. Results: 9 unique microbial species were significantly enriched in the CRC specimen from the Nigerian cohort when compared to the US cohort. Subset analysis based on MSI status revealed enrichment of Faecalibacterium and Veillonella in the Nigerian cohort for both MSI and microsatellite stable (MSS) CRC (Table). Prevotella was significantly enriched in MSS CRC in the Nigerian cohort (OR=53.35, CI=10.34,275.37, p0.05). Conclusions: Several unique species with taxonomic diversity are enriched in Nigerian CRC and can be independently validated based on stratification by MSI status. Given the varied accessibility of diagnostic and therapeutic tools for CRC in these distinct geographical settings, understanding unique microbial biomarkers will provide the landscape to explore key microbial targets for therapy specific to this population.[Table: see text]

Introduction: Gallbladder carcinomas (GBC) are rare and aggressive neoplasms. Previous studies in small GBC cohorts have suggested potential molecular alterations associated with poor prognosis, however, a comprehensive understanding of the recurrent genetic events in this cancer type is very limited. In this study, we aim to characterize in detail the recurrent molecular alterations in GBC and their association with pathologic and clinical characteristics. Material and Methods: We studied the prevalence of somatic mutations and copy number alterations (CNA) in n=244 GBC samples (54% primary, 56% metastatic), collected from 2014 to 2021, and sequenced with the targeted NGS panel MSK-IMPACT. We assessed the correlation of the recurrent genomic variants with several pathologic (e.g., T stage, N stage, grade, histologic subtypes) and clinical characteristics (e.g., clinical stage) using Fisher's exact test. We also used Cox Proportional-Hazards modeling to assess the correlation between genetic variants and patient overall survival (OS). Results: The most common histologic subtypes in this GCB cohort included adenocarcinomas NOS (83%), carcinomas with squamous differentiation (9%), high-grade carcinomas (4%), and carcinomas with neuroendocrine differentiation (3%). Most patients were diagnosed with stage IV (65%) and stage III (11%) disease at the time of biopsy/resection, and the mean OS survival was 29.4 months. The most commonly mutated genes were TP53 (59%), SMAD4 (21%), ARID1A (19%), PIK3CA (10%), KRAS (7%), and ERBB2 (7%). Potentially recurrent oncogenic CNAs included deep deletions in CDKN2A (14%) and CDKN2B (14%), and amplifications in MDM2 (12%), ERBB2 (10%), CCNE1 (9%), MYC (7%), and KRAS (7%). RB1, PBRM1, and CTNNB1 variants were more common in cases with neuroendocrine differentiation, whereas alterations in IKZF1 and AGO2 were enriched in cases with squamous differentiation. The most significant event associated with shorted OS was chromosome 12q13-15 amplification i.e., CDK4 p=0.03 HR=2 [95% CI 1-3.6] and MDM2 p=0.05 HR=1.6 [1-2.5], which associated with a median OS of 20 months (vs. 34 months in the wild-type). Genomic variants associated with longer OS included ERBB2 (p=0.006 HR=0.2 [0.06-0.6]), KMT2C (p=0.03 HR=0.2 [0.1-0.9]) and KMT2D (p=0.01 HR=0.2 [0.04-0.7]) mutations, and CDK12 amplification (p=0.04 HR=0.4 [0.2-0.96]). Although ERBB2 amplification was not associated with prognosis, co-amplification of CDK12 and ERBB2 (chromosome 17q12) was frequently observed (Pearson correlation r=0.8). Conclusions: This large-scale genomic analysis reveals recurrent genomic events potentially associated with prognosis in GBC, including single nucleotide variants in ERBB2, KMT2C, and KMT2D, in addition to CNAs in chromosome 12q13-15 and 17q12 regions. This effort will continue to include a detailed analysis of recurrent structural variants, loss of heterozygosity loci, and analysis of the microbiota in this GBC cohort. Citation Format: Nicolas A. Giraldo, Abhinita Mohanty, Chad Vanderbilt, Rose Brannon, Ryma Benayed, Efsevia Vakiani, Ghassan Abou-Alfa, James Harding, Imane El Dika, Nikolaus Schultz, Bob Li, Michael F. Berger, Marc Ladanyi, Eileen O'Reilly, William Jarnagin, Olca Basturk, Maria Arcila. Molecular characterization of gallbladder cancer [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 82.

PURPOSE: A subset of pediatric, adolescent and young adult (AYA) gliomas are located in the brainstem, eloquent locations, or present with diffuse/leptomeningeal disease, and are associated with high risk and low yield of biopsy. At the same time, accurate molecular diagnosis is necessary to direct optimal therapy. In such cases, analysis of cell free DNA (cfDNA) form cerebral spinal fluid (CSF) may represent a diagnostic alternative to biopsy. METHODS: We investigated the utility of CSF cfDNA sequencing through a stepwise approach, using clinically validated, targeted molecular assays. Testing was performed using a broad hybrid capture next generation sequencing assay (MSK-IMPACT) and subsequent targeted digital droplet PCR in a subset of cases. RESULTS: We analyzed 17 CSF samples from 17 pediatric (n=6) and AYA (n=11) glioma patients with primary or recurrent disease. Thirteen had tumors located within the brainstem, and four had leptomeningeal involvement. Somatic alterations were detected in 12/17 samples (71%). In 3/4 patients with leptomeningeal involvement, cfDNA testing revealed a BRAF fusion consistent with the diagnosis of diffuse leptomeningeal glioneuronal tumor (DLGNT). Among the 13 patients with brainstem involvement, four had somatic H3 K27M mutations, three had IDH mutations, and one had TP53 and ATRX mutations; five patients had no detectable mutations. CONCLUSION: In our analysis, we found that established glioma hotspot mutations were able to be detected within the CSF. We propose that in patients for whom tissue biopsy is high risk, not feasible, or tissue was nondiagnostic, CSF cfDNA sequencing has a substantial diagnostic yield and should be considered as a valuable novel diagnostic tool. Ongoing research is aiming to further increase the sensitivity of cfDNA testing, especially in patients with very low levels of CSF cfDNA.

To characterize the relationship between tumor-infiltrating lymphocytes (TIL), tumor mutational burden (TMB), and genetic alterations in microsatellite stable (MSS), microsatellite instability (MSI), or mutant POLE/POLD1 colon cancer. MATERIALS AND METHODS: Four hundred ninety-nine resected stage I-III colon tumors treated between 2014 and 2019 were assessed for TIL; somatic mutations, copy number alterations, and structural changes in > 400 oncogenes; and MSI status. RESULTS: Of the 499 tumors analyzed, 313 were MSS, 175 were MSI, and 11 had POLE/POLD1 pathogenic mutations. Both the percentage of tumors with a high level of TIL (≥ 4 lymphocytes per high-power field) and the median TMB differed significantly between the three phenotypes: MSS, 4.5% and 6 mutations/Mb; MSI, 68% and 54 mutations/Mb; POLE/POLD1, 82% and 158 mutations/Mb (P < .05). Within each phenotype, TMB did not vary significantly with TIL level. Among MSI tumors, the median number of frameshift indels was significantly higher in tumors with high levels of TIL (20 v 17; P = .018). In the MSS group, significantly higher proportions of tumors with high levels of TIL had mutations in the transforming growth factor-β (36% v 12%; P = .01), RAS (86% v 54%; P = .02), and Hippo (7% v 1%; P = .046) pathways; in contrast, TP53 alterations were associated with low levels of TIL (74% v 43%; P = .01). CONCLUSION: The association between TIL, TMB, and genetic alterations varies significantly between MSI, MSS, and mutant POLE/POLD1 colon tumors. These differences may help explain tumoral immunity and lead to predictors of response to immunotherapy.