The mutational landscape of the SCAN‐B real‐world primary breast cancer transcriptome. Issue 10 (14th September 2020) - Brueffer, Christian; Gladchuk, Sergii; Winter, Christof; Vallon‐Christersson, Johan; Hegardt, Cecilia; Häkkinen, Jari; George, Anthony M; Chen, Yilun; Ehinger, Anna; Larsson, Christer; Loman, Niklas; Malmberg, Martin; et al.
Abstract: Breast cancer is a disease of genomic alterations, of which the panorama of somatic mutations and how these relate to subtypes and therapy response is incompletely understood. Within SCAN‐B (ClinicalTrials.gov : NCT02306096), a prospective study elucidating the transcriptomic profiles for thousands of breast cancers, we developed a RNA‐seq pipeline for detection of SNVs/indels and profiled a real‐world cohort of 3, 217 breast tumors. We describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population‐based cohort and relate it to patient survival. We demonstrate that RNA‐seq can be used to call mutations in genes such as PIK3CA, TP53, and ERBB2, as well as the status of molecular pathways and mutational burden, and identify potentially druggable mutations in 86.8% of tumors. To make this rich dataset available for the research community, we developed an open source web application, the SCAN‐B MutationExplorer (http://oncogenomics.bmc.lu.se/MutationExplorer ). These results add another dimension to the use of RNA‐seq as a clinical tool, where both gene expression‐ and mutation‐based biomarkers can be interrogated in real‐time within 1 week of tumor sampling. Synopsis: A bioinformatics pipeline was developed for detection of single nucleotide variants and small insertions/deletions from RNA sequencing (RNA‐seq) data. The mutational landscape of 3, 217 primary breast cancer transcriptomes in relation to patient survival was made available through a public web portal. An optimized pipeline for detection of single nucleotide variants and short insertions and deletions from RNA‐seq data was developed and applied to 3, 217 primary breast tumors. The mutational portraits identified mutations in clinically important genes, including mutations in one or more potentially druggable genes in 85.3% percent of cases. Mutational portraits revealed significant relationships to patient outcome within specific treatment groups, including treatment resistance mutations. This rich dataset was made publicly available via our open source web‐based application, the SCAN‐B MutationExplorer, accessible at http://oncogenomics.bmc.lu.se/MutationExplorer . Abstract : A bioinformatics pipeline was developed for detection of single nucleotide variants and small insertions/deletions from RNA sequencing (RNA‐seq) data. The mutational landscape of 3, 217 primary breast cancer transcriptomes in relation to patient survival was made available through a public web portal.