Evidence map›Paper›PMID 39328266›Full record

ArticleNAR genomics and bioinformatics2024

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

Khalique Newaz, Christoph Schaefers, Katja Weisel, Jan Baumbach, Dmitrij Frishman

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Khalique NewazInstitute for Computational Systems Biology and Center for Data and Computing in Natural Sciences, Universität Hamburg, 22761 Hamburg, Germany.ORCID https://orcid.org/0000-0002-1192-8360
Christoph SchaefersDepartment of Oncology, Hematology and Bone Marrow Transplantation with Division of Pneumology, Universitätsklinikum Hamburg-Eppendorf, 20251 Hamburg, Germany.
Katja WeiselDepartment of Oncology, Hematology and Bone Marrow Transplantation with Division of Pneumology, Universitätsklinikum Hamburg-Eppendorf, 20251 Hamburg, Germany.
Jan BaumbachInstitute for Computational Systems Biology and Center for Data and Computing in Natural Sciences, Universität Hamburg, 22761 Hamburg, Germany.ORCID https://orcid.org/0000-0002-0282-0462
Dmitrij FrishmanDepartment of Bioinformatics, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID39328266
PMCPMC11426328

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.