Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal.

International cancer registries make real-world genomic and clinical data available, but their joint analysis remains a challenge. AACR Project GENIE, an international cancer registry collecting data from 19 cancer centers, makes data from >130,000 patients publicly available through the cBioPortal for Cancer Genomics (https://genie.cbioportal.org). For 25,000 patients, additional real-world longitudinal clinical data, including treatment and outcome data, are being collected by the AACR Project GENIE Biopharma Collaborative using the PRISSMM data curation model. Several thousand of these cases are now also available in cBioPortal. We have significantly enhanced the functionalities of cBioPortal to support the visualization and analysis of this rich clinico-genomic linked dataset, as well as datasets generated by other centers and consortia. Examples of these enhancements include (i) visualization of the longitudinal clinical and genomic data at the patient level, including timelines for diagnoses, treatments, and outcomes; (ii) the ability to select samples based on treatment status, facilitating a comparison of molecular and clinical attributes between samples before and after a specific treatment; and (iii) survival analysis estimates based on individual treatment regimens received. Together, these features provide cBioPortal users with a toolkit to interactively investigate complex clinico-genomic data to generate hypotheses and make discoveries about the impact of specific genomic variants on prognosis and therapeutic sensitivities in cancer. SIGNIFICANCE: Enhanced cBioPortal features allow clinicians and researchers to effectively investigate longitudinal clinico-genomic data from patients with cancer, which will improve exploration of data from the AACR Project GENIE Biopharma Collaborative and similar datasets.

Comprehensive Molecular Characterization of Gallbladder Carcinoma and Potential Targets for Intervention.

PURPOSE: Gallbladder carcinoma (GBC) is an uncommon and aggressive disease, which remains poorly defined at a molecular level. Here, we aimed to characterize the molecular landscape of GBC and identify markers with potential prognostic and therapeutic implications. EXPERIMENTAL DESIGN: GBC samples were analyzed using the MSK-IMPACT (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets) platform (targeted NGS assay that analyzes 505 cancer-associated genes). Variants with therapeutic implications were identified using OncoKB database. The associations between recurrent genetic alterations and clinicopathologic characteristics (Fisher exact tests) or overall survival (univariate Cox regression) were evaluated. P values were adjusted for multiple testing. RESULTS: Overall, 244 samples (57% primary tumors and 43% metastases) from 233 patients were studied (85% adenocarcinomas, 10% carcinomas with squamous differentiation, and 5% neuroendocrine carcinomas). The most common oncogenic molecular alterations appeared in the cell cycle (TP53 63% and CDKN2A 21%) and RTK_RAS pathways (ERBB2 15% and KRAS 11%). No recurrent structural variants were identified. There were no differences in the molecular landscape of primary and metastasis samples. Variants in SMAD4 and STK11 independently associated with reduced survival in patients with metastatic disease. Alterations considered clinically actionable in GBC or other solid tumor types (e.g., NTRK1 fusions or oncogenic variants in ERBB2, PIK3CA, or BRCA1/2) were identified in 35% of patients; 18% of patients with metastatic disease were treated off-label or enrolled in a clinical trial based on molecular findings. CONCLUSIONS: GBC is a genetically diverse malignancy. This large-scale genomic analysis revealed alterations with potential prognostic and therapeutic implications and provides guidance for the development of targeted therapies.

OncoTree: A Cancer Classification System for Precision Oncology.

PURPOSE: Cancer classification is foundational for patient care and oncology research. Systems such as International Classification of Diseases for Oncology (ICD-O), Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), and National Cancer Institute Thesaurus (NCIt) provide large sets of cancer classification terminologies but they lack a dynamic modernized cancer classification platform that addresses the fast-evolving needs in clinical reporting of genomic sequencing results and associated oncology research. METHODS: To meet these needs, we have developed OncoTree, an open-source cancer classification system. It is maintained by a cross-institutional committee of oncologists, pathologists, scientists, and engineers, accessible via an open-source Web user interface and an application programming interface. RESULTS: OncoTree currently includes 868 tumor types across 32 organ sites. OncoTree has been adopted as the tumor classification system for American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE), a large genomic and clinical data-sharing consortium, and for clinical molecular testing efforts at Memorial Sloan Kettering Cancer Center and Dana-Farber Cancer Institute. It is also used by precision oncology tools such as OncoKB and cBioPortal for Cancer Genomics. CONCLUSION: OncoTree is a dynamic and flexible community-driven cancer classification platform encompassing rare and common cancers that provides clinically relevant and appropriately granular cancer classification for clinical decision support systems and oncology research.