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De, S.

Publications and source records attributed to De, S..

74 records · Page 5Linked to original sources

Conserved patterns of somatic mutations in human peripheral blood cells

With growing interest in monitoring mutational processes in normal tissues, tumor heterogeneity, and cancer evolution under therapy, the ability to accurately and economically detect ultra-rare mutations is becoming increasingly important. However, this capability has often been compromised by significant sequencing, PCR and DNA preparation error rates. Here, we describe FERMI (Fast Extremely Rare Mutation Identification) - a novel method designed to eliminate majority of these sequencing and library preparation errors in order to significantly improve rare somatic mutation detection. This method leverages barcoded targeting probes to capture and sequence DNA of interest with single copy resolution. The variant calls from the barcoded sequencing data then further filtered in a position-dependent fashion against an adaptive, context-aware null model in order to distinguish true variants. As a proof of principle, we employ FERMI to probe bone marrow biopsies from leukemia patients, and show that rare mutations and clonal evolution can be tracked throughout cancer treatment, including during historically intractable periods like minimum residual disease. Importantly, FERMI is able to accurately detect nascent clonal expansions within leukemias in a manner that may facilitate the early detection and characterization of cancer relapse.

genetics↗

A computational framework for detecting signatures of accelerated somatic evolution in cancer genomes

By accumulation of somatic mutations, cancer genomes evolve, diverging away from the genome of the host. It remains unclear to what extent somatic evolutionary divergence is comparable across different regions of the cancer genome versus concentrated in specific genomic elements. We present a novel computational framework, SASE-mapper, to identify genomic regions that show signatures of accelerated somatic evolution (SASE) in a subset of samples in a cohort, marked by accumulation of an excess of somatic mutations compared to that expected based on local, context-aware background mutation rates in the cancer genomes. Analyzing tumor whole genome sequencing data for 365 samples from 5 cohorts we detect recurrent SASE at a genome-wide scale. The SASEs were enriched for genomic elements associated with active chromatin, and regulatory regions of several known cancer genes had SASE in multiple cohorts. Regions with SASE carried specific mutagenic signatures and often co-localized within the 3D nuclear space suggesting their common basis. A subset of SASEs was frequently associated with regulatory changes in key cancer pathways and also poor clinical outcome. While the SASE-associated mutations were not necessarily recurrent at base-pair resolution, the SASEs recurrently targeted same functional regions, with similar consequences. It is likely that regulatory redundancy and plasticity promote prevalence of SASE-like patterns in the cancer genomes.

bioinformatics↗