Prognostic importance of splicing-triggered aberrations of protein complex interfaces in cancer.


Journal

NAR genomics and bioinformatics
ISSN: 2631-9268
Titre abrégé: NAR Genom Bioinform
Pays: England
ID NLM: 101756213

Informations de publication

Date de publication:
Sep 2024
Historique:
received: 09 06 2024
revised: 30 08 2024
accepted: 13 09 2024
medline: 27 9 2024
pubmed: 27 9 2024
entrez: 27 9 2024
Statut: epublish

Résumé

Aberrant alternative splicing (AS) is a prominent hallmark of cancer. AS can perturb protein-protein interactions (PPIs) by adding or removing interface regions encoded by individual exons. Identifying prognostic exon-exon interactions (EEIs) from PPI interfaces can help discover AS-affected cancer-driving PPIs that can serve as potential drug targets. Here, we assessed the prognostic significance of EEIs across 15 cancer types by integrating RNA-seq data with three-dimensional (3D) structures of protein complexes. By analyzing the resulting EEI network we identified patient-specific perturbed EEIs (i.e., EEIs present in healthy samples but absent from the paired cancer samples or vice versa) that were significantly associated with survival. We provide the first evidence that EEIs can be used as prognostic biomarkers for cancer patient survival. Our findings provide mechanistic insights into AS-affected PPI interfaces. Given the ongoing expansion of available RNA-seq data and the number of 3D structurally-resolved (or confidently predicted) protein complexes, our computational framework will help accelerate the discovery of clinically important cancer-promoting AS events.

Identifiants

pubmed: 39328266
doi: 10.1093/nargab/lqae133
pii: lqae133
pmc: PMC11426328
doi:

Types de publication

Journal Article

Langues

eng

Pagination

lqae133

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.

Auteurs

Khalique Newaz (K)

Institute for Computational Systems Biology and Center for Data and Computing in Natural Sciences, Universität Hamburg, 22761 Hamburg, Germany.

Christoph Schaefers (C)

Department of Oncology, Hematology and Bone Marrow Transplantation with Division of Pneumology, Universitätsklinikum Hamburg-Eppendorf, 20251 Hamburg, Germany.

Katja Weisel (K)

Department of Oncology, Hematology and Bone Marrow Transplantation with Division of Pneumology, Universitätsklinikum Hamburg-Eppendorf, 20251 Hamburg, Germany.

Jan Baumbach (J)

Institute for Computational Systems Biology and Center for Data and Computing in Natural Sciences, Universität Hamburg, 22761 Hamburg, Germany.
Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.

Dmitrij Frishman (D)

Department of Bioinformatics, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.

Classifications MeSH