A platform for oncogenomic reporting and interpretation

Abstract

Manual interpretation of variants remains rate limiting in precision oncology. The increasing scale and complexity of molecular data generated from comprehensive sequencing of cancer samples requires advanced interpretative platforms as precision oncology expands beyond individual patients to entire populations. To address this unmet need, we introduce a Platform for Oncogenomic Reporting and Interpretation (PORI), comprising an analytic framework that facilitates the interpretation and reporting of somatic variants in cancer. PORI integrates reporting and graph knowledge base tools combined with support for manual curation at the reporting stage. PORI represents an open-source platform alternative to commercial reporting solutions suitable for comprehensive genomic data sets in precision oncology. We demonstrate the utility of PORI by matching 9,961 pan-cancer genome atlas tumours to the graph knowledge base, calculating therapeutically informative alterations, and making available reports describing select individual samples.

A comprehensive personal omics clinical interpreter based on genomic and transcriptomic profiles

“…4a ), where over 39.4% of patients can obtain the reliable drug prioritizations of Level A and Level B. In the TCGA cohort, POI exhibited comparable performance to the latest platform, PORI [12], with drug prioritizations available for approximately 96% of patients. Additionally, in the MSK-IMPACT cohort, POI significantly improved the prioritized drug ratios compared to the original report from MSKCC [26], providing drug prioritizations for approximately 94.7% of patients.…”

“…These platforms employ diverse strategies to analyze genomic and transcriptomic characteristics, underscoring the significant potential of multi-dimensional data interpretation in identifying actionable therapeutic alterations. Despite these advancements, existing platforms still exhibit certain limitations, including incomplete coverage of interpreted data types (e.g., RNA expression and genotype data), limited exploration of cross-omics features, and constrained capabilities in therapeutic recommendations, such as chemotherapy, beyond targeted therapies [12, 16, 17]. Thus, achieving an accurate interpretation of multi-dimensional molecular changes remains a substantial challenge in advancing precision medicine.…”

CIViCdb 2022: evolution of an open-access cancer variant interpretation knowledgebase

“…Due to its unrestricted licensing and open API, CIViC data consumers are not required to register their use; therefore, the complete picture of CIViC’s impact cannot be determined. However, numerous established collaborations and self-identified data clients illustrate several types of integration and diverse stakeholder engagement (Figure 2 ) ( 4 , 9–11 ). Most groups and individuals that interact with CIViC consume the data without creating new content.…”

“…Anyone can create a login and contribute, and those who comment, submit new content, or suggest revisions to existing content are referred to as CIViC Curators ( N = 328 as of 15 August 2022, Supplemental Figure S1 ). The majority of these Curators are individuals from outside of the Washington University in Saint Louis (WashU) community (only 55 of 328 active Curators have a WashU affiliation, the site of CIViC’s initial development) ( Supplemental Figure S2 ), and represent academic, governmental and commercial organizations ( 9 , 12 ). Curator contributions take many forms and require varying degrees of effort, which supports curation activities from individuals with a wide range of interests and expertise ( Supplemental Figure S3 ).…”

CCAS: One-stop and comprehensive annotation system for individual cancer genome at multi-omics level

“…PCAWG-Scout ( Goldman et al, 2020a ), UCSC Xena ( Goldman et al, 2020b ), and OpenCRAVAT ( Pagel et al, 2020 ) were designed for complex visualization and analysis services of large scale cancer datasets. PCGR ( Nakken et al, 2018 ), GenomeChronicler ( Guerra-Assuncao et al, 2020 ), and PORI ( Reisle et al, 2022 ) were developed for cancer genome annotation at the individual patient level, providing many useful functions, such as mutation signature analysis, mutation burden analysis, drug interactions, as well as clinical trials analysis. However, these tools are more focused on parsing genomic level data, while lacking comprehensive annotations based on the integration of multiple cancer-related databases, or have limitations in data analysis at the individual patient level.…”