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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

Detailed statistical results

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

Figure S2. Microbiome analysis in GBC.

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.

cBioPortal for Cancer Genomics is an open-source platform for interactive, exploratory analysis of large-scale clinico-genomic data sets. cBioPortal provides a suite of user-friendly visualizations and analyses, including OncoPrints, mutation “lollipop” plots, variant interpretation, group comparison, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization. The public site (https://www.cbioportal.org) is accessed by >35,000 unique visitors each month and hosts data from >350 studies spanning individual labs and large consortia. In addition, at least 74 instances of cBioPortal are installed at academic institutions and companies worldwide. To better support all users, we unified our documentation (https://docs.cbioportal.org) and added a user guide and an ongoing series of ‘how-to’ videos to address common questions. In 2022 we added 32 studies (>38,000 samples) to the public site. In addition, we added a nonsynonymous tumor mutation burden (TMB) value for all samples and enhanced the TCGA PanCancer Atlas studies with DNA methylation and treatment data. All data is available in the cBioPortal Datahub: https://github.com/cBioPortal/datahub. We also host a dedicated instance for AACR Project GENIE, enabling access to the GENIE cohort of >165,000 clinically sequenced samples from 19 institutions (https://genie.cbioportal.org). The GENIE Biopharma Collaborative (BPC) enables the collection of comprehensive clinical annotations, including response, outcome, and treatment history. The first BPC cohorts are now available: ~2,000 non-small cell lung cancer samples and ~1,500 colorectal cancer samples. Support for multimodal data analysis has been a major focus, including several new integrations with external tools. Single cell data is now available in the CPTAC GBM study and can be visualized throughout cBioPortal, and via integration with cellxgene. On the patient page, H&E and mIF images can be visualized via integration with Minerva, and the genomic overview now integrates IGV. We continue to enhance existing features. In the study view, users can now add charts comparing categorical vs continuous data, and the plots tab includes a heatmap option. We replaced the existing fusion data type with a generalized structural variant data type that supports detailed information including breakpoints and orientation, to enable new visualizations and analyses. Pathway level analysis has been extended with a new integration with NDEx. cBioPortal is fully open source (https://github.com/cBioPortal/). Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children’s Hospital of Philadelphia, Princess Margaret Cancer Centre, Caris Life Sciences, Bilkent University and The Hyve. We welcome open source contributions from others in the cancer research community. Citation Format: Ino de Bruijn, Tali Mazor, Adam Abeshouse, Diana Baiceanu, Stephanie Carrero, Elena Garcia Lara, Benjamin Gross, David M. Higgins, Prasanna K. Jagannathan, Priti Kumari, Ritika Kundra, Bryan Lai, Xiang Li, James Lindsay, Aaron Lisman, Divya Madala, Ramyasree Madupuri, Angelica Ochoa, Yusuf Ziya Özgül, Oleguer Plantalech, Sander Rodenburg, Baby Anusha Satravada, Robert Sheridan, Lucas Sikina, Jessica Singh, S Onur Sumer, Yichao Sun, Pim van Nierop, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Sjoerd van Hagen, Ugur Dogrusoz, Allison Heath, Adam Resnick, Trevor J. Pugh, Chris Sander, Ethan Cerami, Jianjiong Gao, Nikolaus Schultz. cBioPortal for Cancer Genomics. [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 4256.

cBioPortal for Cancer Genomics is an open-source platform for interactive, exploratory analysis of large-scale cancer genomics data sets. cBioPortal provides a user-friendly interface that integrates genomic and clinical data, and provides a suite of visualizations and analyses, including OncoPrints, mutation “lollipop” plots, variant interpretation, group comparison, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization. cBioPortal also integrates external tools including CIViC, Cancer Digital Slide Archive, Next-Generation Clustered Heat Map, IGV and Bioconductor to facilitate interpretation. The public site (https://www.cbioportal.org) is accessed by ~35,000 unique visitors each month and hosts data from >325 studies spanning individual labs and large consortia. In addition, >67 instances of cBioPortal are installed at academic institutions and pharmaceutical/biotechnology companies worldwide. In 2021 we added data from 32 studies, totaling >24,000 samples, to the public site. All data is also available in the cBioPortal Datahub: https://github.com/cBioPortal/datahub/. We also host a dedicated instance for AACR Project GENIE, enabling access to the GENIE cohort of >135,000 clinically sequenced samples from 19 institutions (https://genie.cbioportal.org). In addition, the GENIE Biopharma Collaborative (BPC) enables the collection of comprehensive clinical annotations, including response, outcome, and treatment histories. The first BPC release contains data from >1,800 non-small cell lung cancer samples and will be released in early 2022. The growing GENIE cohort and the BPC clinical data have driven a number of recent developments, including performance improvements (the load time for the GENIE cohort was reduced from minutes to seconds). To leverage the BPC clinical data, we enabled sample selection based on treatment status, extended support for outcome analysis, and enhanced the patient timeline representation to incorporate response data. Additional development work has focused on improvements to variant interpretation, enhancements to the Mutations tab, and support for novel molecular assays via the ‘generic assay’ data type. Documentation on these new features and many others is available at https://www.cbioportal.org/news. cBioPortal is fully open source (https://github.com/cBioPortal/) under a GNU Affero GPL license. Development is a collaborative effort among groups at Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children’s Hospital of Philadelphia, Princess Margaret Cancer Centre, Bilkent University and The Hyve. We welcome open source contributions from others in the cancer research community. Citation Format: Jianjiong Gao, Tali Mazor, Ino de Bruijn, Adam Abeshouse, Diana Baiceanu, Ziya Erkoc, Elena Garcia Lara, Benjamin Gross, David M. Higgins, Prasanna K. Jagannathan, Priti Kumari, Ritika Kundra, Xiang Li, James Lindsay, Aaron Lisman, Divya Madala, Ramyasree Madupuri, Angelica Ochoa, Oleguer Plantalech, Sander Rodenburg, Baby A. Satravada, Robert Sheridan, Lucas Sikina, Jessica Singh, S. Onur Sumer, Yichao Sun, Pim van Nierop, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Sjoerd van Hagen, Kees van Bochove, Ugur Dogrusoz, Allison Heath, Adam Resnick, Trevor J. Pugh, Chris Sander, Ethan Cerami, Nikolaus Schultz. cBioPortal for cancer genomics [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 1155.