Evidence map›Paper›PMID 40202958›Full record

ArticlePLoS computational biology2025

Comprehensive characterization of respiratory genes based on a computational framework in pan-cancer to develop stratified treatment strategies.

Caiyu Zhang, Chenyu Liu, Zhuoru Wang, Di Wang, Wenli Chen, Jian Li, Qianyi Lu, Jiajun Zhou, Yetong Chang, Peng Wang and 4 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. 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. Review
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

14 authors.

Caiyu ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Chenyu LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Zhuoru WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Di WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Wenli ChenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Jian LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Qianyi LuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Jiajun ZhouCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Yetong ChangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Peng WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Yue GaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Junwei WangDepartment of Respiratory Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Hui ZhiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.
Shangwei NingCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China.ORCID 0000-0003-4079-8945

Funding

Innovative Science Foundation of Harbin Medical UniversityNational Natural Science Foundation of ChinaOutstanding Youth Foundation of Heilongjiang Province of China
6 · The paper itself

Abstract

Abnormal cellular respiration plays a critical role in carcinogenesis. However, the molecular mechanisms underlying dysregulation of respiratory gene expression across different cancer types remain unclear. Here, we developed a computational framework that provides an analytical approach for exploring the molecular alterations and clinical relevance of respiratory genes in pan-cancer. We identified a total of 53 gene signatures in the three stages of respiration (including glycolysis, tricarboxylic acid cycle, and oxidative phosphorylation) through this framework and found that they were broadly differentially expressed and genetically altered across 33 cancer types. Pathway analysis manifested that the expression levels of almost all respiratory gene signatures were remarkably associated with the activation or inhibition of numerous oncogenic pathways, such as metabolism, angiogenesis, cell proliferation, and apoptosis. Survival analysis highlighted the oncogenic or tumor suppressor potential of the respiratory gene signatures. In particular, VCAN has shown significant oncogenic features in multiple cancer types. Finally, we identified a number of respiratory gene signatures that could be potential therapeutic targets, including VCAN. We also predicted small-molecule compounds targeting respiratory gene signatures or components of pathways regulated by them. Overall, our comprehensive analysis has greatly enhanced the understanding of molecular alterations of respiratory genes in tumorigenesis and progression, and provided insights into developing new therapeutic strategies.

Indexed as

Computational BiologyNeoplasmsCell RespirationGene Expression ProfilingGene Expression Regulation, NeoplasticGlycolysisHumansOxidative Phosphorylation

Identifiers

PMID40202958
PMCPMC11981224

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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 OpenQuestion graph.