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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.

Harmonization of cancer variant representation, efficient communication, and free distribution of clinical variant‐associated knowledge are central problems that arise with increased usage of clinical next‐generation sequencing. The Clinical Genome Resource (ClinGen) Somatic Working Group (WG) developed a minimal variant level data (MVLD) representation of cancer variants, and has an ongoing collaboration with Clinical Interpretations of Variants in Cancer (CIViC), an open‐source platform supporting crowdsourced and expert‐moderated cancer variant curation. Harmonization between MVLD and CIViC variant formats was assessed by formal field‐by‐field analysis. Adjustments to the CIViC format were made to harmonize with MVLD and support ClinGen Somatic WG curation activities, including four new features in CIViC: (1) introduction of an assertions feature for clinical variant assessment following the Association of Molecular Pathologists (AMP) guidelines, (2) group‐level curation tracking for organizations, enabling member transparency, and curation effort summaries, (3) introduction of ClinGen Allele Registry IDs to CIViC, and (4) mapping of CIViC assertions into ClinVar submission with automated submissions. A generalizable workflow utilizing MVLD and new CIViC features is outlined for use by ClinGen Somatic WG task teams for curation and submission to ClinVar, and provides a model for promoting harmonization of cancer variant representation and efficient distribution of this information.

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.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinomas (PDAC) are characterized by fibrosis and an abundance of cancer-associated fibroblasts (CAFs). We investigated strategies to disrupt interactions among CAFs, the immune system, and cancer cells, focusing on adhesion molecule cadherin 11 (CDH11), which has been associated with other fibrotic disorders and is expressed by activated fibroblasts. METHODS: We compared levels of CDH11 mRNA in human pancreatitis and pancreatic cancer tissues and cells, compared with normal pancreas, and measured levels of CDH11 protein in human and mouse pancreatic lesions and normal tissues. We crossed p48-Cre;LSL-Kras(G12D/+);LSL-Trp53(R172H/+) (KPC) mice with CDH11-knockout mice and measured survival times of offspring. Pancreata were collected and analyzed by histology, immunohistochemistry, and (single-cell) RNA sequencing; RNA and proteins were identified by imaging mass cytometry. Some mice were given injections of PD1 antibody or gemcitabine and survival was monitored. Pancreatic cancer cells from KPC mice were subcutaneously injected into Cdh11(+/+) and Cdh11(−/−) mice and tumor growth was monitored. Pancreatic cancer cells (mT3) from KPC mice (C57BL/6), were subcutaneously injected into Cdh11(+/+) (C57BL/6J) mice and mice were given injections of antibody against CDH11, gemcitabine, or small molecule inhibitor of CDH11 (SD133) and tumor growth was monitored. RESULTS: Levels of CDH11 mRNA and protein were significantly higher in CAFs than in pancreatic cancer epithelial cells, human or mouse pancreatic cancer cell lines, or immune cells. KPC/Cdh11(+/−) and KPC/Cdh11(−/−) mice survived significantly longer than KPC/Cdh11(+/+) mice. Markers of stromal activation entirely surrounded pancreatic intraepithelial neoplasias in KPC/Cdh11(+/+) mice and incompletely in KPC/Cdh11(+/−) and KPC/Cdh11(−/−) mice, whose lesions also contained fewer FOXP3(+) cells in the tumor center. Compared with pancreatic tumors in KPC/Cdh11(+/+) mice, tumors of KPC/Cdh11(+/−) mice had increased markers of antigen processing and presentation; more lymphocytes and associated cytokines; decreased extracellular matrix components; and reductions in markers and cytokines associated with immunosuppression. Administration of the PD1 antibody did not prolong survival of KPC mice with 0, 1, or 2 alleles of Cdh11. Gemcitabine extended survival only of KPC/Cdh11(+/−) and KPC/Cdh11(−/−) mice or reduced subcutaneous tumor growth in mT3 engrafted Cdh11(+/+) mice given in combination with the CDH11 antibody. A small molecule inhibitor of CDH11 reduced growth of pre-established mT3 subcutaneous tumors only if T and B cells were present in mice. CONCLUSIONS: Knockout or inhibition of CDH11, which is expressed by CAFs in the pancreatic tumor stroma, reduces growth of pancreatic tumors, increases their response to gemcitabine, and significantly extends survival of mice. CDH11 promotes immunosuppression and extracellular matrix deposition, and might be developed as a therapeutic target for pancreatic cancer.

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.

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.

A growing number of academic and community clinics are conducting genomic testing to inform treatment decisions for cancer patients (1). In the last 3–5 years, there has been a rapid increase in clinical use of next generation sequencing (NGS) based cancer molecular diagnostic (MolDx) testing (2). The increasing availability and decreasing cost of tumor genomic profiling means that physicians can now make treatment decisions armed with patient-specific genetic information. Accumulating research in the cancer biology field indicates that there is significant potential to improve cancer patient outcomes by effectively leveraging this rich source of genomic data in treatment planning (3). To achieve truly personalized medicine in oncology, it is critical to catalog cancer sequence variants from MolDx testing for their clinical relevance along with treatment information and patient outcomes, and to do so in a way that supports large-scale data aggregation and new hypothesis generation. One critical challenge to encoding variant data is adopting a standard of annotation of those variants that are clinically actionable. Through the NIH-funded Clinical Genome Resource (ClinGen) (4), in collaboration with NLM’s ClinVar database and >50 academic and industry based cancer research organizations, we developed the Minimal Variant Level Data (MVLD) framework to standardize reporting and interpretation of drug associated alterations (5). We are currently involved in collaborative efforts to align the MVLD framework with parallel, complementary sequence variants interpretation clinical guidelines from the Association of Molecular Pathologists (AMP) for clinical labs (6). In order to truly democratize access to MolDx data for care and research needs, these standards must be harmonized to support sharing of clinical cancer variants. Here we describe the processes and methods developed within the ClinGen’s Somatic WG in collaboration with over 60 cancer care and research organizations as well as CLIA-certified, CAP-accredited clinical testing labs to develop standards for cancer variant interpretation and sharing.

Pancreatic ductal adenocarcinoma (PDAC) is the 3rd leading cause of cancer related deaths in the U.S. Recent advances in understanding RNA biology in PDAC have shed light on post-transcriptional regulation of genes and pathways through RNA binding proteins (RBP). Our lab has demonstrated that HuR, an RBP, is overexpressed in PDAC cells and stabilizes pro-survival mRNAs. Additionally, our work and others have demonstrated that this level of gene regulation can support drug resistance in PDAC cells. A synthetic lethal strategy employing Poly-ADP ribose polymerase inhibitors (PARPi) in a subset of patients with DNA repair deficient pancreatic cancers has been gaining interest. However, the success of PARPi is often hindered by the emergence of drug resistance in patients who initially respond. We have published that short-term PARPi treatment of PDAC cells causes activation of HuR where it stabilizes a DNA repair enzyme, PAR-glycohydrolase, and mediates acute PARPi resistance. In this study, we generated olaparib acquired resistant pancreatic cancer cells in vitro and acquired pancreatic patient derived xenograft cell lines (pre- and post PARPi) to understand acute versus acquired resistant mechanism(s). In characterising the acquired resistant model of PARPi resistance, we found that these cells are >20 fold more resistant to olaparib and platinums and >5 fold resistant to other PARPi like rucaparib and veliparib, compared to parental cells. No cross resistance was seen with other chemotherapeutics like gemcitabine. Additionally, we also found acquired resistant cells lost PARP-1 protein expression compared to parental cells. Bioinformatic analyses on HuR-RNA immunoprecipitation-microarray (RIP-microarray) data from acutely treated olaparib cells show enrichment of pro-survival mRNAs. Interestingly, these mRNAs are significantly downregulated in acquired resistant cells compared to control cells (i.e., negative log2 fold changes, p Citation Format: Aditi Jain, Matthew McCoy, Lebaron A. Agostini, Yuriy Gusev, Subha Madhavan, Michael Pishvaian, Sankar Addya, Eric Londin, Maria R. Gurevich, Chani Stossel, Talia Golan, Charles J. Yeo, Jonathan R. Brody. A global transcriptome analysis of pancreatic cancer cells distinguishes between acute and acquired PARP inhibitor resistance mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4764.