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Madhavan, Subha

https://orcid.org/0000-0001-7617-3547

Mayo Clinic

Georgetown University

Citations 15

Abstract 1096: Harmonization standards from the Variant Interpretation for Cancer Consortium
Babb, Larry, Liang, Yonghao , Roy, Angshumoy , Brush, Matthew , Lee, Jennifer, Lu, Anna, Coard, Thomas, Ritter, Deborah , Walsh, Brian , Madhavan, Subha , Raca, Gordana , Wagner, Alex H. , Hart, Reece K. , Babb, Larry, Freimuth, Robert R. , Coffman, Adam , Pitel, Beth A. , Rao, Shruti , Mockus, Susan M. , Horak, Peter , King, Ian F. G. , Sonkin, Dmitriy , Chakravarty, Debyani , Griffith, Malachi , Griffith, Obi L.

Cancer Research | September 4, 2020 | Volume: 80 | Issue: 16_Supplement | Pages: 1096-1096

10.1158/1538-7445.am2020-1096 Get It

Abstract The use of clinical gene sequencing is now commonplace, and genome analysts and molecular pathologists are often tasked with the labor-intensive process of interpreting the clinical significance of large numbers of tumor variants. Numerous independent knowledgebases have been constructed to alleviate this manual burden, however these knowledgebases are non-interoperable. As a result, the analyst is left with a difficult tradeoff: for each knowledgebase used the analyst must understand the nuances particular to that resource and integrate its evidence accordingly when generating the clinical report, but for each knowledgebase omitted there is increased potential for missed findings of clinical significance.The Variant Interpretation for Cancer Consortium (VICC; cancervariants.org) was formed as a driver project of the Global Alliance for Genomics and Health (GA4GH; ga4gh.org) to address this concern. VICC members include representatives from several major somatic interpretation knowledgebases including CIViC, OncoKB, Jax-CKB, the Weill Cornell PMKB, the IRB-Barcelona Cancer Biomarkers Database, and others. Previously, the VICC built and reported on a harmonized meta-knowledgebase of 19,551 biomarker associations of harmonized variants, diseases, drugs, and evidence across the constituent resources.In that study, we analyzed the frequency with which the tumor samples from the AACR Project GENIE cohort would match to harmonized associations. Variant matches increased dramatically from 57% to 86% when broader matching to regions describing categorical variants were allowed. Unlike precise sequence variants with specified alternate alleles, categorical variants describe a collection of potential variants with a common feature, such as “V600” (non-valine alleles at the 600 residue), “Exon 20 mutations” (all non-silent mutations in exon 20), or “Gain-of-function” (hypermorphic alterations that activate or amplify gene activity). However, matching observed sequence variants to categorical variants is challenging, as the latter are typically only described as unstructured text. Here we describe the expressive and computational GA4GH Variation Representation specification (vr-spec.readthedocs.io), which we co-developed as members of the GA4GH Genomic Knowledge Standards work stream. This specification provides a schema for common, precise forms of variation (e.g. SNVs and Indels) and the method for computing identifiers from these objects. We highlight key aspects of the specification and our work to apply it to the characterization of categorical variation, showcasing the variant terminology and classification tools developed by the VICC to support this effort. These standards and tools are free, open-source, and extensible, overcoming barriers to standardized variant knowledge sharing and search. Citation Format: Alex H. Wagner, Reece K. Hart, Larry Babb, Robert R. Freimuth, Adam Coffman, Yonghao Liang, Beth Pitel, Angshumoy Roy, Matthew Brush, Jennifer Lee, Anna Lu, Thomas Coard, Shruti Rao, Deborah Ritter, Brian Walsh, Susan Mockus, Peter Horak, Ian King, Dmitriy Sonkin, Subha Madhavan, Gordana Raca, Debyani Chakravarty, Malachi Griffith, Obi L. Griffith. Harmonization standards from the Variant Interpretation for Cancer Consortium [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 1096.
Abstract A58: Curation of pediatric cancer variants within the Clinical Genome Resource (ClinGen)
Church, Alanna J. , Ritter, Deborah , Danos, Arpad , Krysiak, Kilann, Hiemenz, Matthew , Janeway, Katherine A. , Ji, Jianling , Laetsch, Theodore W. , Schmidt, Ryan J. , Sund, Kristen L. , Lin, Wan‐Hsin , Kulkarni, Shashikant , Madhavan, Subha , Roy, Angshumoy , Raca, Gordana , Rao, Shruti , Corson, Laura , Fisher, Kevin E. , Kesserwan, Chimene A. , Parsons, D. Williams , Griffith, Malachi , Griffith, Obi L.

Cancer Research | August 12, 2020 | Volume: 80 | Issue: 14_Supplement | Pages: A58-A58

10.1158/1538-7445.pedca19-a58 Get It

Abstract Introduction: The Clinical Genome Resource (ClinGen) Somatic Working Group (sWG) is a multi-institution team engaged in developing processes, resources, and standards to support accurate classification of somatic variants in cancer. Existing decision support resources in cancer knowledgebases are heavily skewed towards genes and variants relevant in adult cancers; however, information to support variant interpretation in childhood cancers is limited. Here we report on the goals and progress of the Pediatric Cancer Taskforce, created within the ClinGen sWG, to lead curation efforts of actionable alterations in childhood cancers. Methods: The ClinGen sWG Pediatric Cancer Taskforce (PCT) consists of a core group of twelve members comprising geneticists, pathologists, and oncologists with expertise in different pediatric cancers and with representation from 9 leading pediatric institutions. The taskforce has a total of 35 members including volunteer-curators who work under guidance of the expert members. Curation of childhood cancer variants is conducted in collaboration with the Clinical Interpretation of Variants in Cancer (CIViC) team at Washington University in Saint Louis, using the CIViC knowledgebase (civicdb.org) and the ClinVar database as open-access curation and data-sharing platforms. Diagnostic, prognostic, and therapeutic evidence is tiered according to the AMP/ASCO/CAP guidelines for the clinical interpretation of somatic variants. PCT members are assigned specific genetic variant-tumor type associations for curation, which are then reviewed in monthly conferences to finalize assertions in CIViC. Results: The PCT has prioritized 40 genetic alterations relevant to pediatric cancer for curation based on their clinical relevance and the lack of sufficient existing curated evidence in clinical knowledgebases. To date, 4 assertions have been created and added to the database: HEY1-NCOA2 fusion in mesenchymal chondrosarcoma, KIAA1549-BRAF fusion and ACVR1 p.G328V variant in pediatric glioma, and EBF1-PDGFRB fusion in pediatric B-cell precursor acute lymphoblastic leukemia. Active curation has been initiated for NTRK fusions agnostic of tissue histology, targetable kinase fusions in Ph-like B-lymphoblastic leukemia, and common variants in selected pediatric sarcomas and brain tumors, focusing heavily on driver gene fusions in childhood cancers. 119 evidence items have been created in CIViC by the members. The PCT also works to implement more standardized and accurate classification of pediatric cancers in CIViC and other cancer resources, and to enhance search for pediatric-specific data through appropriate tagging of evidence using ontology terms. Conclusions: As molecular alterations are increasingly relevant to the care of children with cancer, the ClinGen PCT will work to develop standards, processes, and resources for efficient and accurate determination of clinical relevance of pediatric cancer variants. Citation Format: Alanna J. Church, Shruti Rao, Deborah Ritter, Arpad Danos, Kilann Krysiak, Laura B. Corson, Kevin E. Fisher, Matthew Hiemenz, Katherine A. Janeway, Jianling Ji, Chimene A. Kesserwan, Theodore W. Laetsch, Donald W. Parsons, Ryan J. Schmidt, Kristen L. Sund, Wan-Hsin Lin, Malachi Griffith, Obi L. Griffith, Shashikant Kulkarni, Subha Madhavan, Angshumoy Roy, Gordana Raca. Curation of pediatric cancer variants within the Clinical Genome Resource (ClinGen) [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A58.
Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices
Gupta, Samir , Rogan, Peter K. , Griffith, Malachi , Griffith, Obi L. , Madhavan, Subha , Pitel, Beth, Griffith, Malachi , Griffith, Obi L , Rao, Shruti , Pitel, Beth A. , Wagner, Alex H. , Boca, Simina Maria , McCoy, Matthew , King, Ian F. G. , Park, Ben Ho , Warner, Jeremy L. , Chen, James , Chakravarty, Debyani

JCO Clinical Cancer Informatics | July 9, 2020 | Volume: No volume available | Issue: 4 | Pages: 602-613

10.1200/cci.19.00169 Get It

PURPOSE The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning. METHODS In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards. RESULTS Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence. CONCLUSION Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.
An informatics research agenda to support precision medicine: seven key areas
Tenenbaum, Jessica D. , Avillach, Paul , Benham‐Hutchins, Marge , Breitenstein, Matthew K. , Crowgey, Erin L. , Hoffman, Mark A. , Jiang, Xia , Madhavan, Subha , Mattison, John , Nagarajan, Radhakrishnan , Ray, Bisakha, Shin, Dmitriy , Visweswaran, Shyam , Freimuth, Robert R. , Zhao, Zhongming , Hoffman, Mark A , Freimuth, Robert R

Journal of the American Medical Informatics Association | April 24, 2016 | Volume: 23 | Issue: 4 | Pages: 791-795

10.1093/jamia/ocv213 Get It

AbstractThe recent announcement of the Precision Medicine Initiative by President Obama has brought precision medicine (PM) to the forefront for healthcare providers, researchers, regulators, innovators, and funders alike. As technologies continue to evolve and datasets grow in magnitude, a strong computational infrastructure will be essential to realize PM’s vision of improved healthcare derived from personal data. In addition, informatics research and innovation affords a tremendous opportunity to drive the science underlying PM. The informatics community must lead the development of technologies and methodologies that will increase the discovery and application of biomedical knowledge through close collaboration between researchers, clinicians, and patients. This perspective highlights seven key areas that are in need of further informatics research and innovation to support the realization of PM.
TRANSLATIONAL BIOINFORMATICS 101
Tenenbaum, Jessica D. , Madhavan, Subha , Frey, Lewis J. , Freimuth, Robert R. , Denny, Joshua C.

Biocomputing 2016 | November 19, 2015 | Volume: No volume available | Issue: No issue available | Pages: 552-556

10.1142/9789814749411_0050 Get It