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Comprehensive analysis of mitochondrial-related gene signature for prognosis, tumor immune microenvironment evaluation, and candidate drug development in colon cancer.

Hao Wu | Wentao Zhang | Jingjia Chang | Jin Wu | Xintong Zhang | Fengfeng Jia | Li Li | Ming Liu | Jianjun Zhu
Scientific reports | 2025

Colon adenocarcinoma (COAD), a common digestive system malignancy, involves crucial alterations in mitochondria-related genes influencing tumor growth, metastasis, and immune evasion. Despite limited studies on prognostic models for these genes in COAD, we established a mitochondrial-related risk prognostic model, including nine genes based on available TCGA and MitoCarta 3.0 databases, and validated its predictive power. We investigated the tumor microenvironment (TME), immune cell infiltration, complex cell communication, tumor mutation burden, and drug sensitivity of COAD patients using R language, CellChat, and additional bioinformatic tools from single-cell and bulk-tissue sequencing data. The risk model revealed significant differences in immune cell infiltration between high-risk and low-risk groups, with the strongest correlation found between tissue stem cells and macrophages in COAD. The risk score exhibited a robust correlation with TME signature genes and immune checkpoint molecules. Integrating the risk score with the immune score, microsatellite status, or TMB through TIDE analysis enhanced the accuracy of predicting immunotherapy benefits. Predicted drug efficacy offered options for both high- and low-risk group patients. Our study established a novel mitochondrial-related nine-gene prognostic signature, providing insights for prognostic assessment and clinical decision-making in COAD patients.

Pubmed ID: 39979377

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: Applied Basic Research Project of Shanxi Province,
    Id: 20210302124376
  • Agency: Applied Basic Research Project of Shanxi Province,
    Id: 202103021224228
  • Agency: National Outstanding Youth Science Fund Project of National Natural Science Foundation of China,
    Id: 81902513
  • Agency: China Postdoctoral Science Foundation,
    Id: 2023M732157
  • Agency: Applied Basic Research Project of Shanxi Province,
    Id: 202303021211114

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This is a list of tools and resources that we have found mentioned in this publication.


NCBI Epigenomics (tool)

RRID:SCR_006151

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19, 2022.

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Genomics of Drug Sensitivity in Cancer (tool)

RRID:SCR_011956

A genomics database project is an academic research program to identify molecular features of cancers that predict response to anti-cancer drugs.

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Genomic Data Commons Data Portal (GDC Data Portal) (tool)

RRID:SCR_014514

A unified data repository of the National Cancer Institute (NCI)'s Genomic Data Commons (GDC) that enables data sharing across cancer genomic studies in support of precision medicine. The GDC supports several cancer genome programs at the NCI Center for Cancer Genomics (CCG), including The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Cancer Genome Characterization Initiative (CGCI). The GDC Data Portal provides a platform for efficiently querying and downloading high quality and complete data. The GDC also provides a GDC Data Transfer Tool and a GDC API for programmatic access.

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MitoCarta (tool)

RRID:SCR_018165

Collection of genes encoding proteins with strong support of mitochondrial localization. Inventory of genes encoding mitochondrial-localized proteins and their expression across 14 mouse tissues. Database is based on human and mouse RefSeq proteins that are mapped to NCBI Gene loci. MitoCarta 2.0 inventory provides molecular framework for system-level analysis of mammalian mitochondria.

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quanTIseq (tool)

RRID:SCR_022993

Software pipeline for quantification of Tumor Immune contexture from human RNA-seq data.

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