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Poulsgaard, G. A.

Publications and source records attributed to Poulsgaard, G. A..

2 recordsLinked to original sources

Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns

DNA repair deficiencies in cancers may result in characteristic mutational patterns, as exemplified by deficiency of BRCA1/2 and efficacy prediction for PARP-inhibitors. We trained and evaluated predictive models for loss-of-function (LOF) of 145 individual DDR genes based on genome-wide mutational patterns, including structural variants, indels, and base-substitution signatures. We identified 24 genes whose deficiency could be predicted with good accuracy, including expected mutational patterns for BRCA1/2, MSH3/6, TP53, and CDK12 LOF variants. CDK12 is associated with tandem-duplications, and we here demonstrate that this association can accurately predict gene deficiency in prostate cancers (area under the ROC curve=0.97). Our novel associations include mono- or biallelic LOF variants of ATRX, IDH1, HERC2, CDKN2A, PTEN, and SMARCA4, and our systematic approach yielded a catalogue of predictive models, which may provide targets for further research and development of treatment, and potentially help guide therapy.

genomics↗

Sequence dependencies and mutation rates of localized mutational processes in cancer

BackgroundCancer mutations accumulate through replication errors and DNA damage coupled with incomplete repair. Individual mutational processes often show strong sequence and regional preferences. As a result, some sequence contexts mutate at much higher rates than others. Mutational hotspots, with recurrent mutations across cancer samples, represent genomic positions with elevated mutation rates, often caused by highly localized mutational processes. ResultsWe analyze the mutation rates of all 11-mer genomic sequence contexts using the PCAWG set of 2,583 pan-cancer whole genomes. We further associate individual mutations and contexts to mutational signatures and estimate their relative mutation rates. We show that hotspots generally identify highly mutable sequence contexts. Using these, we show that some mutational signatures are enriched in hotspot sequence contexts, corresponding to well-defined sequence preferences for the underlying localized mutational processes. This includes signature 17b (of unknown etiology) and signatures 62 (POLE), 7a (UV), and 72 (linked to lymphomas). In some cases, the mutation rate increases further when focusing on certain genomic regions, such as signature 62 in poised promoters, where the mutation is increased several thousand folds over the overall data set average. ConclusionWe summarize our findings in a catalog of localized mutational processes, their sequence preferences, and their estimated mutation rates.

cancer biology↗