上海科技大学知识管理系统

Genome alteration signatures reflect recurring patterns caused by distinct endogenous or exogenous mutational events during the evolution of cancer. Signatures of single base substitution (SBS) have been extensively studied in different types of cancer. Copy number alterations are important drivers for the progression of multiple cancer. However, practical tools for studying the signatures of copy number alterations are still lacking. Here, a user-friendly open source bioinformatics tool sigminer has been constructed for copy number signature extraction, analysis and visualization. This tool has been applied in prostate cancer (PC), which is particularly driven by complex genome alterations. Five copy number signatures are identified from human PC genome with this tool. The underlying mutational processes for each copy number signature have been illustrated. Sample clustering based on copy number signature exposure reveals considerable heterogeneity of PC, and copy number signatures show improved PC clinical outcome association when compared with SBS signatures. This copy number signature analysis in PC provides distinct insight into the etiology of PC, and potential biomarkers for PC stratification and prognosis. Author summary Genomic DNA alteration signatures are recurring genomic patterns that are the imprints of mutagenic processes accumulated over the lifetime of cancer cell. Copy number alteration is a key driver for the progression of multiple cancer, including prostate cancer, which is particularly driven by complex genome alterations. However, practical tools for studying the signatures of copy number alterations are still lacking. Here a novel bioinformatics tool for copy number signature analysis has been constructed. With this newly developed bioinformatics tool sigminer, we performed the first copy number signature analysis in prostate cancer, and an unprecedentedly clear map connecting genome alteration driving factors and prostate cancer clinical outcomes have been illustrated. These analyses provide novel insight into the mutational processes and clinical outcomes of prostate cancer.