Evidence map›Paper›PMID 40697926›Full record

ArticleFrontiers in medicine2025

Constructing a novel mitochondrial metabolism-related genes signature to evaluate tumor immune microenvironment and predict survival of colorectal cancer.

Hou Wang, Kai Zhang, Guang Ning

Abstract read
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Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Hou Wang *Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Kai Zhang *Department of Surgery, Shanghai Key Laboratory of Gastric Neoplasms, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Guang NingDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colorectal cancer (CRC) is a highly lethal gastrointestinal malignancy with substantial global health implications. Although mitochondrial metabolism genes play a crucial role in CRC development, their prognostic significance remains unclear. Methods: This study systematically analyzed the expression and prognostic value of mitochondrial metabolism-related genes in CRC patients, establishing a risk model using data from TCGA and GEO databases. We also investigated the tumor microenvironment (TME), immune cell infiltration, tumor mutation burden, microsatellite instability (MSI), and drug sensitivity. Core mitochondrial metabolism-related gene, TMEM86B was identified and its functions validated through cell-based assays and Results: Fifteen mitochondrial metabolism-related genes were identified, including HSD3B7, ORC1, GPSM2, NDUFA4L2, CHDH, LARS2, TMEM86B, FABP4, TNFAIP8L3, HMGCL, GDE1, ACOX1, ARV1, HDC, and GSR. The nomogram, which incorporates independent prognostic genes TMEM86B, TNFAIP8L3, HDC, and key clinical features pTNM stage (pathological Tumor-Node-Metastasis), age, was created to predict patient outcomes. Notable differences in immune cell infiltration were observed between risk groups. The risk score was associated with TME genes and immune checkpoints, indicating an immunosuppressive environment in high-risk groups. Furthermore, TIDE analysis revealed that integrating the risk score with immune score, stromal score, or microsatellite status improved the prediction of immunotherapy response across different CRC patient subgroups. Core mitochondrial metabolism-related gene, TMEM86B promotes colorectal cancer progression by enhancing cell proliferation, migration, and invasion, and its downregulation significantly inhibits tumor growth both Conclusion: Our findings indicate that the risk model associated with mitochondrial metabolism may serve as a dependable prognostic indicator, facilitating tailored therapeutic strategies for CRC patients. TMEM86B promotes colorectal cancer progression, and its downregulation inhibits tumor growth

Indexed as

colorectal cancerdrug susceptibilityimmunotherapymitochondrial metabolismprognostic biomarkertumor microenvironment

Identifiers

PMID40697926
PMCPMC12279720

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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.