Search

Although next-generation sequencing is widely used in cancer to profile tumors and detect variants, most somatic variant callers used in these pipelines identify variants at the lowest possible granularity, single-nucleotide variants (SNV). As a result, multiple adjacent SNVs are called individually instead of as a multi-nucleotide variants (MNV). With this approach, the amino acid change from the individual SNV within a codon could be different from the amino acid change based on the MNV that results from combining SNV, leading to incorrect conclusions about the downstream effects of the variants. Here, we analyzed 10,383 variant call files (VCF) from the Cancer Genome Atlas (TCGA) and found 12,141 incorrectly annotated MNVs. Analysis of seven commonly mutated genes from 178 studies in cBioPortal revealed that MNVs were consistently missed in 20 of these studies, whereas they were correctly annotated in 15 more recent studies. At the BRAF V600 locus, the most common example of MNV, several public datasets reported separate BRAF V600E and BRAF V600M variants instead of a single merged V600K variant. VCFs from the TCGA Mutect2 caller were used to develop a solution to merge SNV to MNV. Our custom script used the phasing information from the SNV VCF and determined whether SNVs were at the same codon and needed to be merged into MNV before variant annotation. This study shows that institutions performing NGS sequencing for cancer genomics should incorporate the step of merging MNV as a best practice in their pipelines.Significance:Identification of incorrect mutation calls in TCGA, including clinically relevant BRAF V600 and KRAS G12, will influence research and potentially clinical decisions.

Example knitr report based on CBio export for 26 TCGA melanoma samples

Comparison of MNV detection from VCFs vs MAFs

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.

Although next-generation sequencing is widely used in cancer to profile tumors and detect variants, most somatic variant callers used in these pipelines identify variants at the lowest possible granularity, single-nucleotide variants (SNV). As a result, multiple adjacent SNVs are called individually instead of as a multi-nucleotide variants (MNV). With this approach, the amino acid change from the individual SNV within a codon could be different from the amino acid change based on the MNV that results from combining SNV, leading to incorrect conclusions about the downstream effects of the variants. Here, we analyzed 10,383 variant call files (VCF) from the Cancer Genome Atlas (TCGA) and found 12,141 incorrectly annotated MNVs. Analysis of seven commonly mutated genes from 178 studies in cBioPortal revealed that MNVs were consistently missed in 20 of these studies, whereas they were correctly annotated in 15 more recent studies. At the BRAF V600 locus, the most common example of MNV, several public datasets reported separate BRAF V600E and BRAF V600M variants instead of a single merged V600K variant. VCFs from the TCGA Mutect2 caller were used to develop a solution to merge SNV to MNV. Our custom script used the phasing information from the SNV VCF and determined whether SNVs were at the same codon and needed to be merged into MNV before variant annotation. This study shows that institutions performing NGS sequencing for cancer genomics should incorporate the step of merging MNV as a best practice in their pipelines. Significance: Identification of incorrect mutation calls in TCGA, including clinically relevant BRAF V600 and KRAS G12, will influence research and potentially clinical decisions.

PURPOSE Interpretation of genomic variants in tumor samples still presents a challenge in research and the clinical setting. A major issue is that information for variant interpretation is fragmented across disparate databases, and aggregation of information from these requires building extensive infrastructure. To this end, we have developed Genome Nexus, a one-stop shop for variant annotation with a user-friendly interface for cancer researchers and clinicians. METHODS Genome Nexus (1) aggregates variant information from sources that are relevant to cancer research and clinical applications, (2) allows high-performance programmatic access to the aggregated data via a unified application programming interface, (3) provides a reference page for individual cancer variants, (4) provides user-friendly tools for annotating variants in patients, and (5) is freely available under an open source license and can be installed in a private cloud or local environment and integrated with local institutional resources. RESULTS Genome Nexus is available at https://www.genomenexus.org . It displays annotations from more than a dozen resources including those that provide variant effect information (variant effect predictor), protein sequence annotation (Uniprot, Pfam, and dbPTM), functional consequence prediction (Polyphen-2, Mutation Assessor, and SIFT), population prevalences (gnomAD, dbSNP, and ExAC), cancer population prevalences (Cancer hotspots and SignalDB), and clinical actionability (OncoKB, CIViC, and ClinVar). We describe several use cases that demonstrate the utility of Genome Nexus to clinicians, researchers, and bioinformaticians. We cover single-variant annotation, cohort analysis, and programmatic use of the application programming interface. Genome Nexus is unique in providing a user-friendly interface specific to cancer that allows high-performance annotation of any variant including unknown ones. CONCLUSION Interpretation of cancer genomic variants is improved tremendously by having an integrated resource for annotations. Genome Nexus is freely available under an open source license.

Interpreting genomic variants in tumor samples presents a challenge in research and the clinical setting. A major barrier is that information about variants is fragmented across disparate databases, and aggregating information from these requires building extensive infrastructure. To this end, we have developed Genome Nexus, a one stop shop for variant annotation, equipped with a powerful API for bulk annotation of variants and a user friendly interface for cancer researchers. Genome Nexus is available at https://www.genomenexus.org. It a) aggregates variant information from a large number of sources that are relevant to cancer research and clinical applications; b) allows high-performance programmatic access to the aggregated data via a unified API; c) provides a search interface and a reference page for individual cancer variants; d) provides user-friendly tools for annotating variants in patients; e) is freely available under an open source license and can be installed in a private cloud or local environment. Genome Nexus contains annotations from more than a dozen resources, including those that provide variant effect information (VEP), protein sequence annotation (Uniprot, Pfam, dbPTM), functional consequence prediction (Polyphen-2, Mutation Assessor, SIFT), population prevalence (gnomAD, dbSNP, ExAC), cancer population prevalence (Cancer Hotspots, SignalDB) and clinical actionability (OncoKB, CIViC, Clinvar). The annotations can be accessed through the website, the API, and a command line client. Genome Nexus is unique in providing a user friendly interface specific to cancer that allows high performance annotation of any variant. It is the main annotation service for the popular cancer genomics tool cBioPortal, which serves thousands of users daily. It is also offered as a standalone tool for annotation, allowing researchers and clinicians as well as genomic infrastructure developers to leverage it directly in their own workflows. For example, a local installation of Genome Nexus is used for annotating all variants in AACR Project GENIE. Citation Format: Ino de Bruijn, Xiang Li, Onur Sumer, Benjamin Gross, Robert Sheridan, Angelica Ochoa, Manda Wilson, Avery Wang, Hongxin Zhang, Aaron Lisman, Adam Abeshouse, Sander Rodenburg, Sjoerd van Hagen, Remond Fijneman, Gerrit Meijer, Nikolaus Schultz, Jianjiong Gao. Genome Nexus: A comprehensive resource for the annotation and interpretation of genomic variants in 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 1156.

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.

The cBioPortal for Cancer Genomics is an open-source software platform that enables interactive, exploratory analysis of large-scale cancer genomics data sets with a user-friendly interface. It integrates genomic and clinical data, and provides a suite of visualization and analysis options, including OncoPrint, mutation diagram, variant interpretation, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization, among others. The public site (https://www.cbioportal.org) hosts data from almost 300 studies spanning individual labs and large consortia. Data is also available in the cBioPortal Datahub (https://github.com/cBioPortal/datahub/). In 2020 we added data from 21 studies, totaling almost 30,000 samples. In addition, we added data to existing TCGA PanCancer Atlas studies, including MSI status, mRNA-seq z-scores relative to normal tissue, microbiome data, and RPPA-based protein expression. The cBioPortal also supports AACR Project GENIE with a dedicated instance hosting the GENIE cohort of 112,000 clinically sequenced samples from 19 institutions worldwide (https://genie.cbioportal.org). The site is accessed by over 30,000 unique visitors per month. To support these users, we hosted a five-part instructional webinar series. Recordings of these webinars are available on our website and have already been viewed thousands of times. In addition, more than 50 instances are installed at academic institutions and pharmaceutical/biotechnology companies. In support of these local instances, we continue to simplify the installation process: we now provide a docker compose solution which includes all microservices to run the web app as well as data validation, import and migration. We continue to enhance and expand the functionality of cBioPortal. This year we significantly enhanced the group comparison feature; it is now integrated into gene-specific queries and supports comparison of more data types including DNA methylation, microbiome, and any outcome measure. We also expanded support of longitudinal data: the existing patient timeline has been refactored and now supports a wider range of data and visualizations; a new “Genomic Evolution” tab highlights changes in mutation allele frequencies across multiple samples from a patient; and samples can now be selected based on pre- or post-treatment status. Other features released this year include: allowing users to add gene-level plots for continuous molecular profiles in study view, enabling users to select the desired transcript on the Mutations tab, and integration of PathwayMapper. The 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. Citation Format: Jianjiong Gao, Tali Mazor, Ino de Bruijn, Adam Abeshouse, Diana Baiceanu, Ziya Erkoc, Benjamin Gross, David Higgins, Prasanna K. Jagannathan, Karthik Kalletla, Priti Kumari, Ritika Kundra, Xiang Li, James Lindsay, Aaron Lisman, Pieter Lukasse, Divya Madala, Ramyasree Madupuri, Angelica Ochoa, Oleguer Plantalech, Joyce Quach, Sander Rodenburg, Anusha Satravada, Fedde Schaeffer, Robert Sheridan, Lucas Sikina, S. Onur Sumer, Yichao Sun, Paul van Dijk, 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. The cBioPortal for Cancer Genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 207.

The cBioPortal for Cancer Genomics is an open-source software platform that enables interactive, exploratory analysis of large-scale cancer genomics data sets with a biologist-friendly interface. It integrates genomic and clinical data, and provides a suite of visualization and analysis options, including OncoPrint, mutation diagram, variant interpretation, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization, among others. The public site (https://www.cbioportal.org) hosts data from more than 280 studies from diverse sources including individual labs and large consortia. All data is also available in the cBioPortal Datahub (https://github.com/cBioPortal/datahub/). Data from 40 studies, totaling more than 10,000 samples, was added in 2019, including the latest release from the Cancer Cell Line Encyclopedia and the Pediatric Preclinical Testing Consortium. The site is accessed by over 30,000 unique visitors per month. cBioPortal also supports AACR Project GENIE with a dedicated instance hosting the GENIE cohort of 80,000 clinically sequenced samples from 19 institutions worldwide (http://genie.cbioportal.org). In addition, more than 40 instances are installed locally at academic institutions and pharmaceutical/biotechnology companies. In support of these local installations, cBioPortal now has improved documentation and simplified installation via container technologies such as Docker and Kubernetes. Building on our successful refactoring of the code base, we have released a variety of new features and enhancements to cBioPortal over the past year. Most notably, we released a group comparison feature, enabling users to define groups of interest based on any clinical or genomic features. User-defined groups can be compared simultaneously across genomic and clinical data, including survival analysis and genomic alteration enrichment analysis. Additional new features include: integration of mutation annotations from dbSNP, ClinVar and gnomAD; support for waterfall plots to enable treatment response analysis; saving user preferences for chart layout on study view. The cBioPortal remains under active development. The portal 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, and The Hyve. Ongoing and future development is focused on: (1) building the open source community; (2) continued performance improvements; (3) expanding user support, documentation and training resources; (4) supporting longitudinal data analysis and visualization; (5) developing novel features to support immunogenomics and immunotherapy; (6) enhancing individual variants and overall patient interpretation; (7) supporting single cell data visualizations and analysis. Citation Format: Jianjiong Gao, Tali Mazor, Adam Abeshouse, Ino de Bruijn, Benjamin Gross, Karthik Kalletla, Priti Kumari, Ritika Kundra, Xiang Li, James Lindsay, Aaron Lisman, Pieter Lukasse, Ramyasree Madupuri, Angelica Ochoa, Oleguer Plantalech, Sander Rodenburg, Fedde Schaeffer, Robert Sheridan, Lucas Sikina, Jing Su, S. Onur Sumer, Yichao Sun, Paul van Dijk, Sjoerd van Hagen, Pim van Nierop, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Kelsey Zhu, Kees van Bochove, Ugur Dogrusoz, Allison Heath, Adam Resnick, Trevor J. Pugh, Chris Sander, Ethan Cerami, Nikolaus Schultz. The cBioPortal for Cancer Genomics [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3209.

The cBioPortal for Cancer Genomics is an open-source software platform that enables interactive, exploratory analysis of large-scale cancer genomics data sets with a biologist-friendly interface. It integrates genomic and clinical data, and provides a suite of visualization and analysis options, including OncoPrint, mutation diagram, variant interpretation, survival analysis, expression correlation analysis, alteration enrichment analysis, cohort and patient-level visualization, among others. The public site (http://www.cbioportal.org) hosts data from more than 200 studies from individual labs and large consortia, including the newly added TCGA Pan-Cancer Atlas data and the Count Me In project. These studies can be explored and queried individually or combined together into “virtual studies”. Users are now allowed to login and save virtual studies for query and analysis. The site is currently accessed by approximately 30,000 unique visitors per month. The software is also installed locally at dozens of academic institutions and pharmaceutical/biotechnology companies. A notable instance is the cBioPortal for AACR GENIE (http://www.cbioportal.org/genie/) hosting 60,000 clinically sequenced samples from multiple institutions. Over the past year, the code base has been fully refactored, resulting in a more responsive and interactive website. A new web API is in beta facilitating easier programmatic access to data. In addition, all public studies are available for download from the new datahub (https://github.com/cBioPortal/datahub/). The cBioPortal remains under active development. The portal 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, and The Hyve. Ongoing and future development is focused on: (1) building the open source community; (2) continued performance improvements; (3) expanding user support, documentation and training resources; (4) developing novel features to support immunogenomics and immunotherapy; (5) enhancing individual variants and overall patient interpretation; (6) creating a simplified query interface; and (7) enabling comparative analysis of user-defined patient cohorts. Citation Format: Jianjiong Gao, Tali Mazor, Adam Abeshouse, Ersin Ciftci, Ino de Bruijn, Benjamin Gross, Karthik Kalletla, Priti Kumari, Ritika Kundra, James Lindsay, Aaron Lisman, Pieter Lukasse, Ramyasree Madupuri, Angelica Ochoa, Oleguer Plantalech, Pichai Raman, Fedde Schaeffer, Robert Sheridan, Jing Su, S. Onur Sumer, Yichao Sun, Sander Tan, Sjoerd van Hagen, Avery Wang, Manda Wilson, Hongxin Zhang, Gaofei Zhao, Kelsey Zhu, Kees van Bochove, Ugur Dogrusoz, Trevor J. Pugh, Adam Resnick, Chris Sander, Ethan Cerami, Nikolaus Schultz. The cBioPortal for cancer genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 910.