Somatic mutations occurring in many cancer types are associated with well-understood processes, such as exposure to tobacco smoking or to ultraviolet (UV) light, but also with mutational processes of so far unknown etiology. Mutational processes can be described in terms of so-called mutational signatures, most often represented as vectors of mutation probabilities which indicate what mutation types are preferentially induced by the mutational processes. In this paper we propose a framework to identify which mutational processes are more likely to harm binding sites of a given transcription factor. Our method starts from the binding site motif and assigns to each mutational signature both a hit score, i.e., the likelihood that the mutational process mutates a binding sequence in at least one nucleotide, and a measure of deleteriousness, i.e., the likelihood that a binding site can be disrupted by mutations belonging to the signature. In a final step, the determined scores can be adjusted according to the strengths with which individual mutational signatures have contributed to the observed mutational load of a tumor. We apply the method to CTCF, a transcription factor that is a core architectural protein dictating the dimensional structure of the genome. Our analysis concentrates on melanoma (skin cancer), for which we show that our framework predicts the disruption of CTCF binding sites by specific UV-light associated mutational signatures, confirming our biological expectations.
Deleterious impact of mutational processes on transcription factor binding sites in human cancer
Pinoli P.;Stamoulakatou E.;Ceri S.;Piro R. M.
2019-01-01
Abstract
Somatic mutations occurring in many cancer types are associated with well-understood processes, such as exposure to tobacco smoking or to ultraviolet (UV) light, but also with mutational processes of so far unknown etiology. Mutational processes can be described in terms of so-called mutational signatures, most often represented as vectors of mutation probabilities which indicate what mutation types are preferentially induced by the mutational processes. In this paper we propose a framework to identify which mutational processes are more likely to harm binding sites of a given transcription factor. Our method starts from the binding site motif and assigns to each mutational signature both a hit score, i.e., the likelihood that the mutational process mutates a binding sequence in at least one nucleotide, and a measure of deleteriousness, i.e., the likelihood that a binding site can be disrupted by mutations belonging to the signature. In a final step, the determined scores can be adjusted according to the strengths with which individual mutational signatures have contributed to the observed mutational load of a tumor. We apply the method to CTCF, a transcription factor that is a core architectural protein dictating the dimensional structure of the genome. Our analysis concentrates on melanoma (skin cancer), for which we show that our framework predicts the disruption of CTCF binding sites by specific UV-light associated mutational signatures, confirming our biological expectations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.