Mutational processes in cancer preferentially affect binding of particular transcription factors

Abstract Protein binding microarrays provide comprehensive information about the DNA binding specificities of transcription factors (TFs), and can be used to quantitatively predict the effects of DNA sequence variation on TF binding. There has also been substantial progress in dissecting the pattern...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Mo Liu, Arnoud Boot, Alvin W. T. Ng, Raluca Gordân, Steven G. Rozen
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
R
Q
Acceso en línea:https://doaj.org/article/bf8428da735448df9592fa79a3a34db2
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:bf8428da735448df9592fa79a3a34db2
record_format dspace
spelling oai:doaj.org-article:bf8428da735448df9592fa79a3a34db22021-12-02T14:11:29ZMutational processes in cancer preferentially affect binding of particular transcription factors10.1038/s41598-021-82910-02045-2322https://doaj.org/article/bf8428da735448df9592fa79a3a34db22021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82910-0https://doaj.org/toc/2045-2322Abstract Protein binding microarrays provide comprehensive information about the DNA binding specificities of transcription factors (TFs), and can be used to quantitatively predict the effects of DNA sequence variation on TF binding. There has also been substantial progress in dissecting the patterns of mutations, i.e., the "mutational signatures", generated by different mutational processes. By combining these two layers of information we can investigate whether certain mutational processes tend to preferentially affect binding of particular classes of TFs. Such preferential alterations of binding might predispose to particular oncogenic pathways. We developed and implemented a method, termed "Signature-QBiC", that integrates protein binding microarray data with the signatures of mutational processes, with the aim of predicting which TFs’ binding profiles are preferentially perturbed by particular mutational processes. We used Signature-QBiC to predict the effects of 47 signatures of mutational processes on 582 human TFs. Pathway analysis showed that binding of TFs involved in NOTCH1 signaling is strongly affected by the signatures of several mutational processes, including exposure to ultraviolet radiation. Additionally, toll-like-receptor signaling pathways are also vulnerable to disruption by this exposure. This study provides a novel overview of the effects of mutational processes on TF binding and the potential of these processes to activate oncogenic pathways through mutating TF binding sites.Mo LiuArnoud BootAlvin W. T. NgRaluca GordânSteven G. RozenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Mo Liu
Arnoud Boot
Alvin W. T. Ng
Raluca Gordân
Steven G. Rozen
Mutational processes in cancer preferentially affect binding of particular transcription factors
description Abstract Protein binding microarrays provide comprehensive information about the DNA binding specificities of transcription factors (TFs), and can be used to quantitatively predict the effects of DNA sequence variation on TF binding. There has also been substantial progress in dissecting the patterns of mutations, i.e., the "mutational signatures", generated by different mutational processes. By combining these two layers of information we can investigate whether certain mutational processes tend to preferentially affect binding of particular classes of TFs. Such preferential alterations of binding might predispose to particular oncogenic pathways. We developed and implemented a method, termed "Signature-QBiC", that integrates protein binding microarray data with the signatures of mutational processes, with the aim of predicting which TFs’ binding profiles are preferentially perturbed by particular mutational processes. We used Signature-QBiC to predict the effects of 47 signatures of mutational processes on 582 human TFs. Pathway analysis showed that binding of TFs involved in NOTCH1 signaling is strongly affected by the signatures of several mutational processes, including exposure to ultraviolet radiation. Additionally, toll-like-receptor signaling pathways are also vulnerable to disruption by this exposure. This study provides a novel overview of the effects of mutational processes on TF binding and the potential of these processes to activate oncogenic pathways through mutating TF binding sites.
format article
author Mo Liu
Arnoud Boot
Alvin W. T. Ng
Raluca Gordân
Steven G. Rozen
author_facet Mo Liu
Arnoud Boot
Alvin W. T. Ng
Raluca Gordân
Steven G. Rozen
author_sort Mo Liu
title Mutational processes in cancer preferentially affect binding of particular transcription factors
title_short Mutational processes in cancer preferentially affect binding of particular transcription factors
title_full Mutational processes in cancer preferentially affect binding of particular transcription factors
title_fullStr Mutational processes in cancer preferentially affect binding of particular transcription factors
title_full_unstemmed Mutational processes in cancer preferentially affect binding of particular transcription factors
title_sort mutational processes in cancer preferentially affect binding of particular transcription factors
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/bf8428da735448df9592fa79a3a34db2
work_keys_str_mv AT moliu mutationalprocessesincancerpreferentiallyaffectbindingofparticulartranscriptionfactors
AT arnoudboot mutationalprocessesincancerpreferentiallyaffectbindingofparticulartranscriptionfactors
AT alvinwtng mutationalprocessesincancerpreferentiallyaffectbindingofparticulartranscriptionfactors
AT ralucagordan mutationalprocessesincancerpreferentiallyaffectbindingofparticulartranscriptionfactors
AT stevengrozen mutationalprocessesincancerpreferentiallyaffectbindingofparticulartranscriptionfactors
_version_ 1718391866677788672