ALBERT

Description: Background: Over 300 somatic molecular variants in hematologic diseases are either specified as diagnostic criteria in the World Health Organization (WHO) Classification of Tumors of Hematopoietic and Lymphoid Tissues, recognized as potentially actionable biomarkers in the National Comprehensive Cancer Network (NCCN) compendia, or supported by published well-powered clinical studies. Moreover, new molecular alterations with potential clinical implications in hematologic disease are continuously emerging in the scientific literature. These have critical use for a wide spectrum of clinicians, including hematopathologists who diagnose patient-specific hematologic malignancies, heme-oncologists who direct patient care, and clinical trial nurses who assist patients in finding appropriate clinical trials. Importantly, the utility of this information critically depends on the clinician's ability to interpret the significance of variants in a point-of-care setting. Therefore, there is an urgent and unmet need for a clinical decision support system that 1) distills the clinical implications associated with molecular alterations into a standardized and easily interpretable format and 2) democratizes access of this information to all members of the heme-oncology community. Methods: OncoKB is an established expert-guided precision oncology knowledge base that annotates the oncogenic effect and therapeutic implications of somatic molecular alterations (Chakravarty, D. et al., JCOPO, 2017). Previously, OncoKB was focused primarily on solid tumor mutation annotation. Recently, we expanded OncoKB to include alterations in hematologic malignancies. The heme-specific annotation efforts were guided by heme-oncology and hematopathology physician scientists at Memorial Sloan Kettering (MSK). Supplementing the previously published therapeutic levels of evidence (Fig. 1a), we further added level of evidence systems for diagnostic and prognostic implications (Fig. 1b, c). These three sets of evidence levels are consistent with the criteria set forth by the joint consensus of the ASCO/CAP/AMP guidelines (Li, MM. et al., J Mol Diagn, 2017). We assigned the newly curated heme-specific molecular alterations with diagnostic, prognostic or therapeutic levels of evidence, when applicable. Finally, we annotated and analyzed 1569 hematologic tumor samples from the AACR Project GENIE (release 6.1) with these levels of evidence. Results: In addition to alterations with both solid and heme clinical implications already curated in OncoKB, we annotated 288 unique heme-specific mutations, fusions, and copy number alterations in 156 newly curated cancer-associated genes. Based on MSK-expert consensus, the WHO and NCCN guidelines, and the scientific literature, we identified a total of 192 alterations with unique diagnostic levels of evidence, 65 alterations with unique prognostic levels of evidence and 55 alterations with unique therapeutic levels of evidence across 13 major hematologic tumor types (Fig. 2). To test the utility of OncoKB, we annotated all genomic events in 1569 heme cancer samples in 89 hematologic malignancies in the AACR GENIE cohort (V6.1) (Fig. 3a). Thirty-eight percent of samples harbored at least one potentially actionable alteration, and 8% were predictive of clinical benefit from an FDA-approved drug (Fig. 3b). Conclusions: OncoKB heme data is publicly available both through the web resource http://oncokb.org and through incorporation into the cBioPortal for Cancer Genomics. Heme-specific molecular alterations are used to make an accurate diagnosis, inform prognosis, optimize the use of stem cell transplant, and to link patients with the optimal mechanism-based therapies in the clinical trial setting and in routine clinical practice. This is the first study to annotate and analyze actionability of heme samples. In this proof-of-principle study, we demonstrate the ability to annotate clinical samples with their diagnostic, prognostic and therapeutic implications in a point-of-care setting. Disclosures Roshal: Celgene: Other: Provision of Services; Auron Therapeutics: Equity Ownership, Other: Provision of services; Physicians' Education Resource: Other: Provision of services. Ho:Invivoscribe, Inc.: Honoraria. Knorr:Fate Therapeutics: Patents & Royalties. LaFave:Epizyme: Patents & Royalties. Arcila:Invivoscribe, Inc.: Consultancy, Honoraria. Berger:Roche: Consultancy. Solit:Pfizer: Consultancy; Lilly Oncology: Honoraria; Vivideon Therapeutics: Consultancy; Loxo Oncology: Consultancy, Equity Ownership; Illumina: Consultancy. Dogan:Celgene: Consultancy; Seattle Genetics: Consultancy; Corvus Pharmaceuticals: Consultancy; Roche: Consultancy, Research Funding; Novartis: Consultancy; Takeda: Consultancy. Levine:C4 Therapeutics: Membership on an entity's Board of Directors or advisory committees; Qiagen: Membership on an entity's Board of Directors or advisory committees; Isoplexis: Membership on an entity's Board of Directors or advisory committees; Loxo: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Gilead: Consultancy; Imago Biosciences: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Lilly: Honoraria; Prelude Therapeutics: Research Funding; Roche: Consultancy, Research Funding.

Description: Background: Cancer-associated thrombosis (CAT) is a leading cause of death in cancer patients after cancer itself. Risk factors for CAT include tumor type/stage, body mass index (BMI), blood cell counts and chemotherapy exposure. These factors form the basis of prediction algorithms for CAT risk, including most notably the Khorana Risk Score. However, significant limitations exist with these currently-available risk prediction models. Emerging data suggest that a tumor's molecular profile can impact venous thromboembolism (VTE) risk. Mutations of ALK, EGFR, IDH1, ROS1, and KRAS for example have been shown to modulate the risk of CAT; however, these studies were limited by the number of mutations and specific tumor types analyzed. We hypothesized that extended molecular testing in a large patient cohort would allow for improved detection of molecular signatures associated with CAT. We analyzed deep-coverage targeted sequencing data (up to 341 genes) of tumor samples from 11,776 cancer patients to identify gene mutations associated with VTE. Methods: Adult patients with any solid tumor diagnosis who had their tumors sequenced using MSK-IMPACT from 1/2014 to 12/2016 were retrospectively assessed for CAT events using redundant algorithmic methods and individual chart reviews. The endpoint was defined as the first instance of cancer-associated pulmonary embolism and/or proximal/distal lower extremity deep vein thrombosis (DVT). An episode of upper extremity DVT was considered a competing event. The observation period was limited to 365 days after IMPACT blood control sampling. Cause-specific Cox proportional hazards regression was used to test for an association between gene and CAT risk, adjusting for clinical covariates including age, cancer type, cytotoxic chemotherapy (time-dependent), anticoagulant use, stage (metastatic/non-metastatic) and prior history of VTE. Separate multivariate models evaluated the association for the 60 most frequently-mutated genes identified, along with ALK, MET, ROS1 which were included based on existing literature suggesting an effect on VTE risk. Final p-values were adjusted for false discovery using the Benjamini-Hochberg procedure, and the threshold for statistical significance was set at 0.10. Patients with multiple cancer diagnoses were excluded. Results: Out of 11,776 individuals we observed 727 CAT events (6.2% of cohort). The most commonly represented tumor types were lung (18%), breast (15%) and colorectal cancer (10%); see Figure for a breakdown of CAT incidence by tumor type. Most (72%) of patients were metastatic at time of IMPACT testing and 4% were on anticoagulation therapy. Statistically significant predictors of CAT included cytotoxic chemotherapy (HR 1.61 [1.37-1.9]; p

Description: Cancer-associated venous thromboembolism (CAT) is a well-described complication of cancer and a leading cause of death in cancer patients. The purpose of this study was to assess potential associations of molecular signatures with CAT, including tumor-specific mutations and the presence of clonal hematopoiesis. We analyzed deep-coverage targeted DNA-sequencing data of 〉14,000 solid tumor samples using the MSK-IMPACT™ platform to identify somatic alterations associated with VTE. Endpoint was defined as the first instance of cancer-associated pulmonary embolism and/or proximal/distal lower extremity deep vein thrombosis. Cause-specific Cox proportional hazards regression was used, adjusting for pertinent clinical covariates. Of 11,695 evaluable individuals, 72% had metastatic disease at time of IMPACT. Tumor-specific mutations in KRAS (HR=1.34 [1.09-1.64]; adjusted p=0.08), STK11 (HR=2.12 [1.55-2.89]; adjusted p