Rao, Shruti

Abstract Therapeutic resistance in ovarian cancer is frequently driven by persistent replication stress, yet the molecular mechanisms that convert replication stress into a therapeutically exploitable vulnerability remain incompletely understood. Here, we identify drug-induced nuclear cathepsin L (nCTSL) as a previously unrecognized regulator of replication stress and DNA repair. Clofarabine (CLF) combined with the ATR inhibitor AZD6738, or the CHK1 inhibitor prexasertib promoted nuclear accumulation of CTSL, where it remodeled the replication machinery through degradation of CCNE1, MCM3, MCM6, and geminin, accompanied by loss of RAD51 and 53BP1 and increased γH2AX and phospho-RPA2. DNA fiber analysis demonstrated marked inhibition of replication fork progression following CLF-based combinations, whereas CTSL depletion accelerated fork progression and abolished therapy-induced replication stress. Reconstitution with the nuclear M1F CTSL isoform restored replication restraint, confirming a direct role for nuclear CTSL in regulating replication dynamics. GFP-based DNA repair reporter assays further revealed that CLF-based combinations suppress DNA repair competence in a CTSL-dependent manner, indicating that nuclear CTSL couples replication stress amplification with functional inhibition of repair pathways. Functionally, CLF-based combinations selectively targeted transformed fallopian tube secretory epithelial cells while sparing non-transformed counterparts, demonstrated broad activity in patient-derived ovarian cancer ascites spheroids, and significantly inhibited tumor growth and prolonged survival in vivo . Collectively, our findings identify nuclear CTSL as a mechanistic driver of replication stress that remodels the replication machinery, impairs DNA repair, and creates a therapeutically exploitable vulnerability in ovarian cancer. We propose that nuclear CTSL promotes a transition from replication competence to replication catastrophe, thereby establishing a conceptual framework for biomarker-guided therapeutic strategies targeting CTSL-dependent replication stress.

Abstract CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC’s functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications.

Abstract Clinical significance of somatic gene variants needs to be comprehensively characterized for their diagnostic, prognostic and/or therapeutic actionability in patient management. However, challenges remain due to discrepancies in interpretation and reporting of these somatic variants among different testing labs. Therefore, standardized curation, clinical interpretation and reporting of somatic variants in hematologic cancers is critical. To address this issue, the Hematologic Cancer Taskforce (HCT), composed of 52 multi-disciplinary experts including oncologists, molecular pathologists, lab directors, genomic scientists and biocurators, was formed in January 2020 within the ClinGen Somatic Cancer Clinical Domain Working Group (CDWG) with a goal to undertake systematic curation and evidence-based clinical interpretation of genes/somatic variants associated with hematologic malignancies. In collaboration with the Clinical Interpretation of Variants in Cancer (CIViC) (civicdb.org) knowledgebase, HCT members curate, edit, and verify Evidence Items for each variant extracted from peer-reviewed publications. Monthly discussions based on these Evidence Items lead to the preparation of variant Assertions, which summarize the state of the field consensus variant interpretation and include tiering based on the AMP/ASCO/CAP guidelines (PMID: 27993330). FMS-like tyrosine kinase 3 (FLT3) encodes a class III receptor tyrosine kinase expressed in hematopoietic cells. FLT3 mutations, including both internal tandem duplication (ITD) and mutations in the tyrosine kinase domain (TKD), are the most common mutations in acute myeloid leukemia (AML), occurring in approximately 30% of all AML cases. Implementing FLT3 tyrosine kinase inhibitors (TKIs) in different treatment regimens for FLT3 mutated AML patients has led to significantly improved overall survival. Type I FLT3 inhibitors, including midostaurin, gilteritinib, sunitinib, lestaurtinib, and crenolanib, bind to the ATP-binding site when the receptor is in active conformation. Type II FLT3 inhibitors, including sorafenib, ponatinib, and quizartinib, interact with a hydrophobic region directly adjacent to the ATP-binding domain that is only accessible when the receptor is inactive, which prevents receptor activation. Generally in AML cells, type I FLT3 inhibitors prevent activity for both ITD and TKD mutations, while Type II inhibitors target ITD but lack efficiency against TKD mutations. The development of TKD mutations in AML cells with ITD have proved to be a mechanism of acquired, or secondary resistance to Type II FLT3 inhibitors. The HCT is piloting curation assessments of FLT3 alterations, including ITD, TKD and non-TKD variants, in AML. So far, the HCT has curated 75 evidence items for FLT3 somatic variants. FLT3-ITD, as well as D835 and I836 were asserted as tier 1 level A variants based on the prediction of response to gilteritinib in relapsed/refractory AML (PMIDs: 27993330, 31665578, 28645776, 28516360, 27908881). Recent curation activities are focused on FLT3 D839G and N676K, as clinical trials using large AML patient cohorts are lacking in their ability to validate drug response/resistance associations of these two TKD variants due to their low frequency. Functional studies showed both variants result in increased proliferation and protection from apoptosis, supporting the oncogenic potential of these two variants (PMIDs: 26891877, 2468088). FLT3 D839G combined with ITD confers resistance to pexidartinib and ponatinib, both Type II FLT3 inhibitors (PMIDs: 25847190, 23430109). FLT3 N676K predicts response to the Type I FLT3 inhibitor, gilteritinib, when N676K is present alone or in combination with ITD. Interestingly, FLT3 N676K in the absence of ITD predicts response to sorafenib, a Type II FLT3 inhibitor (PMIDs: 32040554, 32984009). However, these results are mostly derived from in vitro studies. Two separate Tier II, Level D Assertions have been submitted for FLT3-ITD&D839G for its response to pexidartinib and ponatinib, and more evidence is being collected to form an Assertion for FLT3 N676K. The complexity of the prediction of response/resistance associated with FLT3 D839G and N676K supports the importance of evidence-based curation and collection for these variants in the context of the overall mutation profile, disease context and specific FLT3 TKIs to clearly define their clinical impact. Disclosures Pullarkat: Stemline Therapeutics: Honoraria.

Abstract Childhood cancers are driven by unique profiles of somatic genetic alterations, with a significant contribution from predisposing germline variants. Understanding the genomic landscape of pediatric cancers is complicated by their rarity, the heterogeneity of variation within a given disease, and the complex forms of structural variation they contain. Variants in childhood disease may differ from those in adult versions of the same cancer type, or may have different clinical significance. Currently, pediatric variants are underrepresented in cancer variant databases, and an urgent need exists for their publicly available expert curation. To address this, the Pediatric Cancer Taskforce (PCT) was formed within the Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group (CDWG) (https://www.clinicalgenome.org/working-groups/somatic/). The PCT is a multi-institutional group of 39 members with broad experience in childhood cancer and variant curation, whose work consists of standardization and classification of genetic variants in pediatric cancers. The CIViC knowledgebase (www.civicdb.org) is a freely available resource for Clinical Interpretation of Variants in Cancer, which leverages public curation and expert moderation to address the problem of annotating the large volume of clinically actionable cancer variants. PCT curators work together with PCT expert members and the CIViC team on variant curation, and have submitted over 230 Evidence Items and over 10 Assertions to CIViC. To further address issues specific to pediatric curation, the PCT is working with CIViC to develop new pediatric-specific CIViC features and modifications of the data model that will aid in pediatric curation. A pediatric user interface, as well as representation of large scale structural and copy number variation are being developed for version two of CIViC, expected to be released in 1-2 years, which will enable curation of a new class of structural variants often encountered in pediatric cancer. A novel standard operating procedure for childhood cancer curation in CIViC is being developed by PCT experts, curators and the CIViC team. This SOP will cover topics including curation of structural variants, as well as pediatric-specific variant tiering guidelines which take into account the sparse nature of evidence in pediatric cases. A companion resource, CIViCmine (http://bionlp.bcgsc.ca/civicmine/), will be further developed to incorporate pediatric data. These and other joint efforts of the PCT and CIViC will significantly enhance pediatric variant representation for public use, to support the care of children with cancer. Citation Format: Arpad Danos, Wan-Hsin Lin, Jason Saliba, Angshumoy Roy, Alanna J. Church, Shruti Rao, Deborah Ritter, Kilannin Krysiak, Alex Wagner, Erica Barnell, Lana Sheta, Adam Coffman, Susanna Kiwala, Joshua F. McMichael, Laura Corson, Kevin Fisher, Heather E. Williams, Matthew Hiemenz, Katherine A. Janeway, Jianling Ji, Kesserwan A. Chimene, Laura Fuqua, Lisa Dyer, Huiling Xu, Jeffrey Jean, Laveniya Satgunaseelan, Liying Zhang, Ted W. Laetsch, Donald W. Parsons, Ryan Schmidt, Lynn M. Schriml, Kristen L. Sund, Shashikant Kulkarni, Subha Madhavan, Xinjie Xu, Rashmi Kanagal-Shamana, Marian Harris, Yasmine Akkari, Nurit Paz Yacov, Panieh Terraf, Malachi Griffith, Obi L. Griffith, Gordana Raca. Advancing knowledgebase representation of pediatric cancer variants through ClinGen/CIViC collaboration [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 210.

Abstract The Clinical Interpretation of Variants in Cancer (CIViC) knowledgebase (civicdb.org) is an open access, centralized hub for structured, community curated and expertly moderated relationships between genomic variants and cancer. Evidence is curated from peer-reviewed, published literature and is classified into one of five Types: Predisposing, Diagnostic, Prognostic, Predictive (therapeutic), or Functional. The robustness of the Evidence is conveyed through the assignment of Levels with the first three derived from patient studies (Validated, Clinical, Case Study), Preclinical, generated from in vivo or in vitro data, and Inferential, which describes indirect associations. Each Evidence Item requires an Evidence Statement written in the curator's own words summarizing the source's results regarding the variant's clinical impact. Collaborations with groups like ClinGen have generated a significant influx of new curators, increasing the demand for detailed principles regarding data prioritization in the Evidence Statement in order to streamline the curation process. The curation community would benefit from simpler, visual guides through the complex decisions needed to appropriately and consistently curate Evidence Items. We are devoting significant effort to continue the development of straightforward Evidence curation algorithms (decision trees) similar to those used in clinical molecular testing labs to aid CIViC curators. Previously published guidelines on development of these statements are the basis of our Evidence algorithms. Obvious inflection points for curators are clearly identified with specific details noted for each to optimize decision efficiency. As the predominant Evidence Type comprising 57% of all CIViC submissions, 58% of referenced patient trials, and 92% of Preclinical submissions, Predictive Evidence is the initial focus of our pilot guidelines with Diagnostic and Prognostic to follow. Within the Predictive Evidence Type, clinical trials, case studies, and preclinical Levels each require vastly different Evidence Statement details and ultimately the creation of three separate, uniquely modeled algorithms. The implementation of these algorithms will assist in streamlining both curation and the expert review process. Notably, a template is not being created, as the preservation of curator style and voice is important to maintain the community feel of the database. To ensure the highest level of clarity, our team is utilizing specific novice and experienced curators to assist with the development process. As these algorithms pass the pilot phase, they are being tested as curator training tools. Ultimately, these guidelines will be used to encourage independence in curators and to enhance the Evidence already contained in CIViC. Citation Format: Jason Saliba, Lana Sheta, Kilannin Krysiak, Arpad Danos, Alex Marr, Erica Barnell, Shahil Pema, Wan-Hsin Lin, Panieh Terraf, Joshua F. McMichael, Cameron J. Grisdale, Shruti Rao, Susanna Kiwala, Adam Coffman, Alex Wagner, Obi L. Griffith, Malachi Griffith. Development of Evidence Statement curation algorithms to aid cancer variant interpretation [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 208.

Hematological malignancies comprise a genetically heterogeneous spectrum of diseases caused by abnormal proliferation or maturation of a variety of hematological cell lineages. Genomic abnormalities including chromosomal translocations, copy number variations and sequence level gene mutations underlie the pathogenesis of these disorders and frequently serve as important diagnostic, prognostic and/or therapeutic markers. However, the substantial discrepancy in interpretation and reporting of these genomic abnormalities among testing labs creates challenges for patient management. Therefore, standardizing the curation, clinical interpretation and reporting of somatic alterations within the context of their diagnostic, prognostic and therapeutic significance in hematological cancers is critical. In January 2020, the ClinGen Somatic Cancer Clinical Domain working group formed the Hematological Cancer Taskforce (HCT) with a goal to undertake systematic curation and evidence-based clinical interpretation of genes/somatic variants associated with hematological malignancies. The HCT has recruited 32 multi-disciplinary experts including oncologists, molecular pathologists, clinical lab directors, genomic scientists and biocurators with expertise in hematological malignancies. In collaboration with the Clinical Interpretation of Variants in Cancer (CIViC) (civicdb.org) knowledgebase, variants from peer-reviewed publications are curated with editor review for clinical utility as evidence items. Monthly discussions based on these evidence items lead to the creation of summary variant assertions using the AMP/ASCO/CAP guidelines (Li M, et al., Journal of Molecular Diagnostics, 2017). The HCT is currently focused on expert curation and clinical interpretation of somatic variants in FLT3 (internal tandem duplication, tyrosine kinase domain and non tyrosine kinase domain variants) in acute myeloid leukemia (AML). Expert curation of gene fusions in Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) in collaboration with the ClinGen somatic pediatric cancer taskforce is currently underway. To date, the HCT has curated 45 evidence items from clinical and pre-clinical studies on the aforementioned genes/variants. In addition, three AMP Tier I, level A variant assertions of FLT3-ITD, D835 and I836, which predict response to Gilteritinib, an FDA-approved drug for relapsed or refractory AML, have been curated. In the future, the HCT plans to extend its focus on curation of BCR-ABL1 kinase domain mutations in chronic myeloid leukemia (CML). Based on the initial pilot curation phase, the HCT will develop gene-specific recommendations to standardize the reporting and interpretation of somatic variants to better assist clinical decisions and apply to become official ClinGen Somatic Expert Panels in each of these gene-disease domains. Disclosures Blombery: Novartis: Consultancy; Invivoscribe: Honoraria; Amgen: Consultancy; Janssen: Honoraria.

Venetoclax is an oral, highly selective, BCL2 inhibitor approved by the FDA for use in chronic lymphocytic leukemia/small lymphocytic lymphoma and acute myeloid leukemia. Despite favorable responses, multiple biological mechanisms lead to treatment resistance. One such mechanism includes somatic mutations in the BCL2 gene. Multiple lines of evidence suggest that hot-spot mutations in BCL2 such as Gly101Val induce treatment resistance by disrupting the binding of BCL2 to the BCL2 inhibitors such as venetoclax. Further, widespread use of high-throughput NGS technologies has identified multiple BCL2 mutations and additional concurrent molecular alterations at various variant allele frequencies in patients with progression while undergoing venetoclax therapy. In order to understand and determine the clinical significance of each of these mutations, careful expert curation and integration into somatic variant annotation AMP/ASCO/CAP guidelines is needed. Further, curation of those somatic variants that may not have sufficient functional evidence in literature may benefit from additional tools such as in silico analysis. To address these issues, we have undertaken an effort to integrate the contributions of a multidisciplinary expert panel (clinical laboratory diagnosticians, oncologists, biomedical informaticians and lab-based researchers) for curation of BCL2 variants in hematological malignancies under the umbrella of ClinGen, an NIH/NHGRI funded consortium to establish standards and centralized resources for assessing the clinical significance of gene variants. Within the ClinGen Somatic Cancer Clinical Domain Working Group (CDWG) ((https://www.clinicalgenome.org/working-groups/somatic/), the somatic hematological malignancy taskforce has identified 56 peer-reviewed publications on BCL2 inhibitors (Jan 2014 to June 2020). The functional evidence contained within these publications was curated using CIViC (Clinical Interpretation of Variants in Cancer, civicdb.org), an open access, crowdsourced aggregation of expert curated evidence. Only a fraction of the somatic variants identified in BCL2 has established functional evidence on variant induced disruption to Venetoclax inhibition. Curation of these remaining variants of unknown significance (VUS) only have in silico functional assays to provide evidence on their potential resistance to Venetoclax. The current curation guidelines do not consider in silico prediction as a strong line of evidence for the interpretation of somatic sequence variants, however this recommendation is meant to interpret generalized in silico predictors and not robust computational models of specific protein function. The latter are more comparable to an experimental functional assay, and provide curators with more trustworthy computational assessments of disruption to protein specific functions. In order to assess their potential to integrate and supplement experimental evidence, the interaction of Ventoclax with several drug resistant BCL2 variants was simulated using AutoDock Vina (J Comput Chem. 2010;31(2):455-61). Facilitated by the SNP2SIM workflow (BMC Bioinformatics. 2019;20(1):171), the relative impact on binding energy was compared to the wildtype system. The in silico binding assay accurately predicted resistance (Fig 1), and demonstrates the utility of applying these methods to the large number of VUS in BCL2. In conclusion, the evidence-based expert curation of BCL2 variants provides a standardized approach for reporting and interpretation across all labs. For those variants (Tier 3) with limited published evidence, computational models that can predict specific changes to functional protein interactions can provide additional tools to the expert curators. Development and incorporation of these tools into curation guidelines requires the refinement of the predictive models through focused validation studies. Disclosures No relevant conflicts of interest to declare.

Abstract Comprehensive interpretation of a patient's cancer genome is a cross-disciplinary process requiring the expertise of oncologists, molecular pathologists, genetic counselors, genomic scientists, and bioinformaticians. The Variant Interpretation for Cancer Consortium (VICC) has created a non-clinical forum for the variant interpretation process by connecting experts from multiple academic institutions and industry to create a Virtual Molecular Tumor Board (VMTB). During VICC-VMTB sessions, experts retrospectively discuss de-identified, challenging patient cases in the context of genomic interpretation guidelines to evaluate a patient's profile across several distinct components: genomic variants; disease context; therapeutic history; family history; demographic information; genomic assay information; and variant allele frequency. These components are processed through the prism of publically available knowledge and expertise of VMTB members, resulting in a broad spectrum of clinically relevant assertions about the patient's disease that may be of prognostic, diagnostic, or predictive relevance. Through these evaluations, the VICC-VMTB primarily works as a means of illuminating challenges in genomic interpretation and advancing the objectives of domain-specific VICC working groups. Examples of challenges that have been highlighted by the VICC-VMTB forum include: 1) inconsistent disease and therapy ontologies across resources are being addressed by Disease Harmonization & Drug Harmonization working groups, respectively; 2) use of machine-learning and natural language processing into clinical-grade variant interpretation are being addressed by the AI-Assisted Curation working group; 3) aggregation and harmonization of knowledgebase data into a centralized resource is being addressed by the Data Licensing and Variant Harmonization working groups; 4) inefficiencies in knowledgebase search functions are being addressed by the Search working group; 5) determination of accurate prediction of biological consequences of rare variants is being addressed by the In Silico Interpretation working group; and 6) standardization of genomic variant curation is being addressed by the Knowledge Curation and Interpretation Standards working group. These VICC working groups provide dedicated expert assemblies intended to specifically tackle these challenges, further increasing the breadth for which genomic information can be made useful in cancer variant interpretation. The VICC-VMTB has been a pertinent link between cancer genomes and clinical interpretation. We are confident VICC-VMTB will continue to be a gateway of acceleration and progress needed in the field of cancer interpretation to provide accurate and efficient answers for our patients in the future. Citation Format: Beth A. Pitel, Shruti Rao, Catherine Del Vecchio Fitz, Subha Madhavan, Rodrigo Dientsmann, Peter Horak, Ian King, Susan M. Mockus, Gordana Raca, Damian T. Rieke, Peter Rogan, Dmitriy Sonkin, David Tamborero, Ioannis S. Vlachos, Brian Walsh, Jeremy L. Warner, Malachi Griffith, Obi L. Griffith, Debyani Chakravarty, Alex H. Wagner. The Virtual Molecular Tumor Board of the Variant Interpretation for Cancer Consortium: A systematic gateway connecting cancer genome interpretation and progress in genomic knowledgebases in cancer [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 3222.

Abstract The Clinical Genome (ClinGen) Resource is a US National Human Genome Research Institute (NHGRI)-funded program dedicated to building an expert curated and freely available central resource that defines the clinical relevance of genes and variants for use in precision medicine. Teams of experts in various clinical domains come together as working groups within ClinGen to facilitate the interpretation, annotation and utilization of genes-variants for clinical application. Somatic Cancer is one such ClinGen Clinical Domain Working Group (CDWG) that consists of over 90 members worldwide, including clinicians, clinical laboratory diagnosticians, genomic scientists and bioinformaticians. Members of this CDWG identify high priority somatic variants in different cancer types that require expert curation and consensus in their clinical interpretation. In order to accurately implement practice guidelines/standards for variant interpretation, the Somatic Cancer CDWG recently established a somatic Variant Curation Expert Panel (VCEP) approval process. Based on their interest and clinical domain expertise, a subset of the CDWG members formed somatic VCEPs to perform authoritative curation on the shortlisted genes-somatic variants within the context of a disease, therapeutic indication or biological pathway. Expert curation within these VCEPs is performed by utilizing guidelines such as those recommended by AMP/ASCO/CAP (Li et al. 2017) and the Somatic Cancer CDWG (Ritter et al. 2016). Wherever necessary, the somatic VCEPs will develop: 1) gene- and disease-specific modifications to address gaps in existing variant assessment guidelines, 2) quantitative approaches for variant interpretation, and 3) implement standardized protocols for annotating somatic variants in genes for a specific disease, drug or biological pathway. Furthermore, ClinGen recently formed the Cancer Variant Interpretation (CVI) committee to provide support, review and feedback on the provisional somatic variant interpretation proposals developed by the VCEPs. The CVI provides somatic VCEPs with a preliminary approval before the final approval by the ClinGen CDWG oversight committee and ultimately ‘expert panel' status in ClinVar, an NCBI-maintained database of clinically relevant gene variants. NTRK fusions in cancer is the first Somatic VCEP going through the ClinGen Somatic Expert Panel approval process. Alterations in the FGFR pathway in GU cancers is the second somatic VCEP under consideration. The Somatic CDWG uses the CIViC (Clinical Interpretation of Variants in Cancer) platform for curation of somatic variants. To date, the CDWG has curated 268 evidence items relating to cancer variants in CIViC, 6 assertions, and 33 evidence source suggestions. The ultimate goal of the Somatic CDWG is to enhance the usability, dissemination and implementation of cancer somatic changes in the ClinGen resource and other cancer variant knowledgebases. Citation Format: Shruti Rao, Deborah Ritter, Arpad Danos, Gordana Raca, Angshumoy Roy, Kilannin Krysiak, Wan-Hsin Lin, Erica Barnell, Matthew McCoy, Beth Pitel, Dmitriy Sonkin, Jue Wang, Seyed Ali Hosseini, Shamini Selvarajah, Ian King, Rashmi Kanagal-Shamana, Xinjie Xu, Jeremy L. Warner, Funda Meric-Bernstam, Jason D. Merker, Marilyn Li, Alex H. Wagner, Malachi Griffith, Obi L. Griffith, Shashikant Kulkarni, Subha Madhavan. ClinGen somatic cancer working group: Disseminating standardized cancer molecular diagnostic data and evidence through global collaboration and expert curation [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 3215.

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.