Cancer Variant Interpretation Research Articles

EP055: The Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group

Interpretation of the clinical significance of somatic variants in cancer remains a major challenge in cancer diagnosis, prognosis and treatment response prediction. Here, we report on progress and plans of the Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group (CDWG). The CDWG membership consists of over 150 multi-disciplinary experts in cancer biology, oncology, pathology, genetics, genomics, and informatics. The mission of the ClinGen Somatic Cancer CDWG is to facilitate the development of data curation guidelines and standards to determine the clinical significance of somatic alterations in cancer, thereby enhancing the usability, dissemination and implementation of cancer somatic variant interpretations in the ClinGen resource and other knowledgebases including the Clinical Interpretations of Variants in Cancer (CIViC), ClinVar, and the Variant Interpretation for Cancer Consortium (VICC) MetaKB.

38. Oncogenic evidence in the CIViC data model

CIViC (www.civicdb.org) is a free, open knowledgebase for clinical interpretations of variants in cancer, with no restrictions on data use. CIViC utilizes public curation and expert moderation. Clinical variant annotation in CIViC consists of 6 types: Predictive, Prognostic, Diagnostic, Predisposing, Functional, and the recently added Oncogenic. Literature derived evidence supporting a given annotation is curated into CIViC in the form of Evidence Items (EIDs), which follow a structured model. Multiple EIDs written for a variant can be summarized into a clinical Assertion, which links back to supporting EIDs along with resources such as population frequency databases, to create a general evaluation of variant pathogenicity or clinical actionability.

43. Adapting CIViC, a cancer variant interpretation knowledgebase, to support variants in disorders of somatic mosaicism

Disorders of somatic mosaicism (DoSM) describe a range of diseases caused by post-zygotically acquired variants that drive clinically-identifiable overgrowth and include syndromes such as PIK3CA-related overgrowth spectrum, Cowden syndrome, and rasopathies. These multi-system manifestations are driven by the overproliferation or enhanced survival of cells harboring variants in a number of genes typically associated with cancer, including: PIK3CA, KRAS, TEK, IDH1/2 and BRAF.

Expert Curation of Somatic FLT3 Variants By the Clingen Somatic Hematologic Cancer Taskforce (ClinGen HCT)

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. DisclosuresPullarkat: Stemline Therapeutics: Honoraria.

Abstract 206: CIViC knowledgebase adapts to field experts and community input

Abstract CIViC (civicdb.org) is an open access, expertly moderated knowledgebase for crowdsourcing Clinical Interpretations of Variants in Cancer. Stakeholders globally-including those in government, academia, industry and medicine-use CIViC to find and curate actionable interpretations of genomic variants in their therapeutic, prognostic, predisposing, diagnostic and functional contexts. Through engagement with curators and leaders in the field, CIViC has implemented several features including Assertions, Organizations and expanded help documentation. The foundational unit of CIViC is the Evidence Item, which describes the clinical relevance of a specific variant curated from a single published source within peer-reviewed literature or ASCO abstract. Assertions aggregate Evidence Items for a given variant-disease or variant-disease-therapy combination. In response to the 2017 AMP-ASCO-CAP guidelines and collaborations with ClinGen, Assertions were modified to integrate ACMG variant pathogenicity classifications, AMP-ASCO-CAP tier designations and associations with NCCN guidelines and FDA approvals to provide a ‘state of the field' interpretation. At present, 12 Assertions spanning eight variants have been submitted by CIViC to ClinVar with one-star submitter status (Submitter ID: 506594), and CIViC has been cited as supporting information in two variants. Assertions exemplify CIViC's responsiveness to new field guidelines, expert collaborators' recommendations and its contributions to other resources. To enhance community involvement, CIViC created Organization-attributed actions. Each action performed by a curator is tagged with their Organization. Curators may switch between Organizations if they belong to more than one. Currently, nine Organizations are recognized in CIViC, the largest being ClinGen with 79 members, 4 sub-organizations and over 24,000 actions. Organizations enable groups to prominently display and track their submissions, activity, and users. CIViC's wide adoption has necessitated the development of robust educational material. CIViC has created nine YouTube videos, one of which is linked by the NIH ITCR homepage. CIViC has migrated help documents to a stand alone site (civic.readthedocs.io) and has made over 60 page modifications since 2019. Help documentation expansion was fueled by user feedback via the CIViC interface, collaborator meetings and in-person events (Curation Jamborees). Improved documentation allows CIViC to grow at scale, unhindered by the need for direct training. CIViC's rapid adaptation to the needs of the community is derived from its open access nature, commitment to data provenance, active connection with users, and abundance of educational material. CIViC rapidly integrates the guidelines, regulatory standards and community recommendations in a freely accessible resource that is flexible enough to evolve with the dynamic field of cancer genomics. Citation Format: Lana M. Sheta, Arpad M. Danos, Jason Saliba, Kilannin Krysiak, Alex H. Wagner, Erica K. Barnell, Susanna Kiwala, Joshua F. McMichael, Adam Coffman, Shahil Pema, Lynzey Kujan, Kelsy C. Cotto, Cody Ramirez, Zachary L. Skidmore, Cameron J. Grisdale, Shruti Rao, Subha Madhaven, Malachi Griffith, Obi L. Griffith. CIViC knowledgebase adapts to field experts and community input [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 206.

Abstract 210: Advancing knowledgebase representation of pediatric cancer variants through ClinGen/CIViC collaboration

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 208: Development of Evidence Statement curation algorithms to aid cancer variant interpretation

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.

Knowledge bases and software support for variant interpretation in precision oncology.

Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools. For the wider set of knowledge bases, access options vary across different parts of the diagnostic process. Programmatic access is limited for information regarding clinical classifications of variants and for therapy recommendations. The main issue for databases used for biological classification of pathogenic variants and pathway context information is the lack of standardized interfaces. There is no single cancer variant interpretation tool that integrates all identified knowledge bases. Specialized tools are available and need to be further developed for different steps in the diagnostic process.

OP052 - Harnessing national pan-laboratory data for accurate quantitation of PS4 in cancer susceptibility genes: Cancer Variant Interpretation Group UK (CanVIG-UK)

OP052 - Harnessing national pan-laboratory data for accurate quantitation of PS4 in cancer susceptibility genes: Cancer Variant Interpretation Group UK (CanVIG-UK)

Combining evidence for and against pathogenicity for variants in cancer susceptibility genes: CanVIG-UK consensus recommendations

Accurate classification of variants in cancer susceptibility genes (CSGs) is key for correct estimation of cancer risk and management of patients. Consistency in the weighting assigned to individual elements of...

Expert Variant Curation Combined with in-Silico analysis for Clinical Interpretation of BCL2 variants in Resistance to BCL2 Inhibitors in Chronic Lymphocytic Leukemia/ Small Lymphocytic Lymphoma

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.

Expert Curation of Somatic Variants in Hematological Malignancies By the Clingen Somatic Hematological Cancer Taskforce (ClinGen HCT)

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.

Abstract 3215: ClinGen somatic cancer working group: Disseminating standardized cancer molecular diagnostic data and evidence through global collaboration and expert curation

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 2136: RegTools: Integrative analysis of genomic and transcriptomic data to identify splice altering mutations across 35 cancer types

Abstract The interpretation of variants in cancer is often focused on genomic alterations that have a known coding consequence. This analysis strategy excludes somatic mutations in non-coding regions of the genome and even exonic mutations may have unidentified non-coding consequences. To address this issue, we created RegTools, a free, open-source software package that integrates analysis of variant calls from genomic data with evidence of expressed splice junctions from transcriptomic data to efficiently identify variants that may cause aberrant splicing in tumors. To date, we have applied RegTools to over 9,000 samples from TCGA and the McDonnell Genome Institute in an effort to identify somatic variants that are associated with alternative splicing patterns within these tumors. For each mutation, we defined a set of control samples in the same cancer cohort that lacked the particular mutation. We then determined putative splicing-relevant mutations by identifying novel splice isoforms whose expression was significantly elevated in the presence of the associated mutation. To further characterize these somatic variants and their associated splice isoforms, we annotated them with the Variant Effect Predictor (VEP), SpliceAI, and Genotype-Tissue Expression (GTEx) junction counts. While some of these mutations would have been predicted by VEP or SpliceAI to be splicing relevant, our analysis provides additional detail by specifically associating a mutation with an altered junction or junctions, including ones not predicted by VEP/SpliceAI or observed within GTEx normal tissue data. RegTools is freely available and open source (www.regtools.org) and all analysis scripts are provided within the project's GitHub repo (https://github.com/griffithlab/regtools). Citation Format: Kelsy C. Cotto, Yang-Yang Feng, Zachary L. Skidmore, Avinash Ramu, Jason Kunisaki, Donald F. Conrad, Yiing Lin, William Chapman, Ravindra Uppaluri, Ramaswamy Govindan, Obi L. Griffith, Malachi Griffith. RegTools: Integrative analysis of genomic and transcriptomic data to identify splice altering mutations across 35 cancer types [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 2136.

Abstract 184: SureSelect sequencing panels and algorithms to detect copy number variations (CNVs), DNA rearrangements, microsatellite Instability and tumor mutational burden (TMB) in FFPE specimens

Abstract Background: The current standard of genomic profiling of cancer tissues relies upon multiple separate technologies to aid in tumor characterization. Here we describe an NGS panel and analysis workflow for cancer samples that can detect single nucleotide polymorphisms (SNPs), insertions and deletions (INDEL), somatic copy number alterations (SCNAs), and translocations (TLs), Tumor Mutation Burden (TMB) and Microsatellite Instability (MSI) in a single assay. Methods: We have developed a SureSelect target enrichment sequencing panels for comprehensive profiling of single nucleotide variations (SNP/INDEL), gene copy number variations (CNV), and DNA translocations (TL) and relevant microsatellite regions in a single assay. The TMB panel gene list was curated based on genes found in cancer gene databases such as Clinical Interpretations of Variants in Cancer (CIViC), Cancer Genome Interpreter (CGIdb), Catalog of Somatic Mutations in Cancer Census (COSMIC), Precision Oncology Knowledge Base (OncoKB). An accompanying data analysis pipeline will provide highly sensitive and accurate detection of variants and allows for the determination TMB and MSI status. Probes have been selected for over 500 genes to detect SCNAs and translocation in several cancer subtypes. The probes are optimized with the SureSelect XTHS protocol, which enables sensitive and accurate detection of rare mutation events within a heterogeneous sample with molecular barcode-mediated error correction. The SCNAs probes target regions in the genome that help in decreasing the noise for SCNAs calling. The data analysis utilizes either a matched normal or standard control DNA to compute read depth log ratios. Aberrant regions of constant ploidy are first identified followed by the application of a variational streaming algorithm on log ratio and SNP allele frequencies to determine the major clones present in the tumor. Translocation detection was verified on lung cancer samples by analyzing split reads across the fusion breakpoints. Results: By diluting samples with known copy-number aberrations into normal DNA, a limit of detection of ⇐2.3 copies/cell was demonstrated, equivalent to the detection of 3 copies at 30% tumor fraction. A similar approach demonstrated an ability to detect EML4-ALK and SLC24A2-ROS1 translocations at 3% allele frequency. Performance of the assay was further evaluated using 100+ FFPE samples harboring rearrangements, gene amplifications, and SNP/Indels. Concordance to the reference methods (FISH, WES, WGS) was >90%. TMB and MSI algorithms were benchmarked using in silico analysis of TCGA data and performance of the assay was evaluated on FFPE samples with orthogonally-determined MSI/TMB status. Conclusions: This work represents an important advancement in the development of a single assay to detect copy number variation, DNA rearrangement and mutations, TMB and MSI status of a FFPE sample. Citation Format: Arjun Vadapalli, Akanksha Khare, Hanjun Shin, Ashutosh Ashutosh, Linus Forsmark, Anne Lucas, Scott Happe, Gilbert Amparo, Carlos Pabon, Jayati Ghosh, Tracy Liu, Jimmy Jin, Mike Ruvolo, Douglas Roberts. SureSelect sequencing panels and algorithms to detect copy number variations (CNVs), DNA rearrangements, microsatellite Instability and tumor mutational burden (TMB) in FFPE specimens [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 184.

Abstract 3211: Evolution of the CIViC knowledgebase for community driven curation of clinical variants in cancer

Abstract With increasing adoption of next generation sequencing into clinical practice, the problem of clinical interpretation of tumor variants arises as a bottleneck for patient care, as effective annotation of these variants draws from a constantly increasing body of largely unstructured clinical and preclinical results. One model to sustain clinical variant curation is to house variant annotation behind a paywall, using access fees to fund further curation effort. An alternate approach is to leverage public curation and expert moderation to create a free public resource to house and distribute this knowledge. The Clinical Interpretation of Variants in Cancer (CIViC, www.civicdb.org) knowledgebase employs the latter approach, and is a free and open-access public resource with an intuitive user interface and flexible public API for programmatic access to all content, which is available to the public with no restrictions on usage. All data is available for retrieval without login, while registration with a free account is required to contribute curation. The provenance of all curation and revision in CIViC is viewable through the web interface, and curators may also leave public comments on all content. Selected expert editors review and revise submitted content, which is clearly labeled as accepted once it has fully undergone moderation. All content in CIViC adheres to a structured data model which follows a published standard operating procedure for curation. This data model incorporates ontologies, standards and guidelines from across the field to promote interoperability and compatibility with other efforts. The CIViC interface also allows curators and organizations to track and display summary statistics of all their activity. CIViC currently has a community of over 190 curators and 16,000 clinical and research users around the world. CIViC continually develops and improves both new and existing features in response to user feedback as well as collaborative and internal development goals. Recently, the drugs and treatment terms used in predictive/therapeutic annotation have been normalized to the NCI Thesaurus. A conflict of interest (COI) statement is now required for all CIViC Editors, and functionality for writing and displaying the COI has been built into the interface. CIViC employs Predictive (Therapeutic), Prognostic, Diagnostic, Predisposing evidence types, and we highlight the recently introduced Functional evidence type, which has seen continued development. We will present the rationale for these changes including demonstrating how adding a Dominant Negative term better supports curation of functional genomics data sets. A focus of functional curation has been TP53, with over 50 evidence items to date. With multiple use cases for this type of data including targeted therapeutics, identification of relevant hotspots, or characterization of cancer driver mechanisms, functional evidence can be used to support conventional concepts of clinical utility and expand the CIViC data model. These developments provide a mechanism for discussion and integration of functional data into somatic variant interpretation guidelines, an area being explored but lacking expert consensus. Citation Format: Arpad Danos, Kilannin Krysiak, Erica K. Barnell, Adam C. Coffman, Joshua F. McMichael, Susanna Kiwala, Nicholas C. Spies, Lana M. Sheta, Shahil P. Pema, Lynzey Kujan, Kaitlin A. Clark, Sydney Anderson, Amber Wollam, Brian Li, Justin Guerra, Shruti Rao, Deborah I. Ritter, Cameron J. Grisdale, Gordana Raca, Alex H. Wagner, Subha Madhavan, Malachi Griffith, Obi L. Griffith. Evolution of the CIViC knowledgebase for community driven curation of clinical variants 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 3211.

Abstract 5469: iCVA- A knowledge-based cancer variation annotation application

Abstract A typical genomic sequencing experiment results in a long list of statistically significant variant candidates among protein-coding genes without any unifying biological theme. This leads to a daunting task of identifying the causal variants and genes to accurately diagnose the disease for clinical or research utility. While a number of downstream tools exist to aid in cancer genome annotation and interpretation, including Clinical Interpretations of Variants in Cancer (CIViC), ClinGen, Database of Curated Mutations (DoCM), Oncotator, and Variant Interpretation for Cancer (VIC), these only provide selective information (somatic/germline/gene-variant specific) or are time/resource consuming. To address this challenge, we developed a software called iCVA using the following methodology: 1) we obtained a priori defined gene sets for different cancer-inducing mechanisms such as pro-oncogenesis, tumor-suppression, DNA repair, angiogenesis, inflammation, metabolism, hypoxia, cell cycle and immune system. 2) genomic variation data were integrated from 1000 Genome, Exome Sequencing Project, Exome Aggregation Consortium (ExAC), ClinVar, dbSNP, GNOMAD, The Cancer Genome Atlas (TCGA), the Catalogue of Somatic Mutations in Cancer (COSMIC) and the International Cancer Gene Census (ICGC), and re-classified into a consensus classification according to ACMG guidelines. 3) Finally, we devised a reporting system to process mutation data from a sequencing experiment to utilize the harmonized pathway and mutational information integrated in a local database to identify and classify cancer-specific gene mutations. The iCVA reporting system classifies mutations as germline or somatic and then sub-classifies these into different cancer-specific mechanisms, including those known to be targetable through existing therapies. To our knowledge, iCVA is the first tool to provide a comprehensive report on cancer variants in a simplified and faster manner, to accelerate the genomic characterization of cancer samples analyzed by high-throughput DNA sequencing. Citation Format: Gaurav Kumar, Melanie Kelly, Paolo Fortina, Adam Ertel. iCVA- A knowledge-based cancer variation annotation application [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 5469.

Abstract 3222: 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 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 A58: Curation of pediatric cancer variants within the Clinical Genome Resource (ClinGen)

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.

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer

Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.