When neighbors play a role: A systems-level analysis of protein interactions conditioning cancer driver mutation effects

Cancer is driven by the accumulation of somatic mutations, including driver mutations that confer a selective advantage to cancer cells. Driver proteins operate within complex interaction networks, and their activity is conditioned by neighbor proteins. Understanding the interplay between driver mutations and the expression of their neighbor proteins can provide insights into cancer biology and potential therapeutic targets. We assessed associations between expression of neighbor proteins and driver mutation status, comparing both between and within cancer types. We further evaluated if neighbors were enriched in significant associations with multiple drivers and characterized the impact of neighbor expression on overall survival for all cancer types. We found a significant correlation between the number of driver associations (DA) a neighbor gene has and the number of sign-coherent survival associations, particularly for neighbors enriched in positive associations, where high neighbor expression correlated with increased driver mutations and poorer survival. We identified 119 neighbors enriched in positive DA with at least two unfavorable survival associations and 25 neighbors enriched in negative DA with at least two favorable survival associations. Our study systematically identified neighbors associated with driver mutation status. Complementary evidence from survival analysis and the literature suggests that neighbors enriched in DA can be further explored as drug target candidates.

Authors

Institutions

Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2025-09-25
DOI
https://doi.org/10.1073/pnas.2501925122
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

When neighbors play a role: A systems-level analysis of protein interactions conditioning cancer driver mutation effects

Francisco Rodrigues Pinto, Margarida Carrolo, António de Carvalho Quintela, Marcia Vital et al.
Proceedings of the National Academy of Sciences
Bioinformatics and Genomic Networks
article

When neighbors play a role: A systems-level analysis of protein interactions conditioning cancer driver mutation effects

Francisco Rodrigues Pinto, Margarida Carrolo, António de Carvalho Quintela, Marcia Vital, João A. I. Miranda
article en

Abstract

Cancer is driven by the accumulation of somatic mutations, including driver mutations that confer a selective advantage to cancer cells. Driver proteins operate within complex interaction networks, and their activity is conditioned by neighbor proteins. Understanding the interplay between driver mutations and the expression of their neighbor proteins can provide insights into cancer biology and potential therapeutic targets. We assessed associations between expression of neighbor proteins and driver mutation status, comparing both between and within cancer types. We further evaluated if neighbors were enriched in significant associations with multiple drivers and characterized the impact of neighbor expression on overall survival for all cancer types. We found a significant correlation between the number of driver associations (DA) a neighbor gene has and the number of sign-coherent survival associations, particularly for neighbors enriched in positive associations, where high neighbor expression correlated with increased driver mutations and poorer survival. We identified 119 neighbors enriched in positive DA with at least two unfavorable survival associations and 25 neighbors enriched in negative DA with at least two favorable survival associations. Our study systematically identified neighbors associated with driver mutation status. Complementary evidence from survival analysis and the literature suggests that neighbors enriched in DA can be further explored as drug target candidates.

Proceedings of the National Academy of SciencesVol. 122(39)
University of Lisbon (PT), Centro Hospitalar Lisboa Norte (PT), Institute for Systems Engineering and Computers (PT), Hospital de Santa Maria (PT)
Openalex Percentile: Top 77%
Bioinformatics and Genomic Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.