Showing papers by "Oliver Hofmann published in 2018"
University of Glasgow1, VU University Medical Center2, Beatson West of Scotland Cancer Centre3, University College Hospital4, Queen Mary University of London5, Barts Health NHS Trust6, Guy's Hospital7, Manchester Academic Health Science Centre8, University of Manchester9, University of Edinburgh10, Northwood University11, Imperial College London12, AstraZeneca13, University of Melbourne14, University of Cambridge15
TL;DR: It is shown that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration, and copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse.
Abstract: The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.
275 citations
Journal Article•
TL;DR: The bcbioRNASeq package as mentioned in this paper is a Bioconductor package that provides ready-to-render templates, objects and wrapper functions to post-process RNA sequencing output data, facilitating quality control analyses, identification of differentially expressed genes and functional enrichment analyses.
Abstract: RNA-seq analysis involves multiple steps, from processing raw sequencing data to identifying, organizing, annotating, and reporting differentially expressed genes. bcbio is an open source, community-maintained framework providing automated and scalable RNA-seq methods for identifying gene abundance counts. We have developed bcbioRNASeq, a Bioconductor package that provides ready-to-render templates, objects and wrapper functions to post-process bcbio RNA sequencing output data. bcbioRNASeq helps automate the generation of high-level RNA-seq reports, facilitating the quality control analyses, identification of differentially expressed genes and functional enrichment analyses.
1 citations