Mendelian Randomization Analysis of Mitochondria-Related Genes and Screening of Prognostic Genes in Colorectal Cancer

IF 3.1 2区医学 Q2 ONCOLOGY

Cancer Medicine Pub Date : 2025-07-07 DOI:10.1002/cam4.71012

Limin Zhu, Xiaowei Huang, Fan Zhang, Jinzu Yang, Zhenye Xu

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引用次数: 0

Abstract

Background

Mitochondria have been linked with inflammatory colorectal cancer (CRC) development; however, the association between mitochondria-related genes (MRGs) and CRC remains unknown.

Aims

To explore the causal relationship between MRGs and CRC, screen prognostic genes, conduct drug prediction analyses, and investigate the correlations between prognostic genes and immune cells.

Materials and Methods

We obtained 1136 MRGs from the MitoCarta3.0 database and analyzed the causal relationship between MRGs expression, methylation, and protein abundance and CRC by Mendelian randomization and sensitivity testing. Prognostic genes were screened via protein–protein interaction networks, enrichment, multi-omics, and survival analyses. Selected key genes were subjected to drug prediction analyses. The prognostic genes and immune cell correlations were explored using Spearman‘s correlation.

Results

The results indicated that 44 MRGs showed causal relationships with CRC. Six genes (sterol carrier protein2 [SCP2], ATP binding cassette subfamily D member 3 [ABCD3], cytochrome coxidase assembly factor heme A: farnesyltransferase [COX10], mitochondrial contact site and cristae organizing system subunit 10 [MiCOS 10], glutaryl-Coenzyme A dehydrogenase [GCDH], and mitochondrial translational release factor 1-like [MTRF1L] were causally associated with CRC and showed better prognostic significance when their expression levels were high, and there were 106 drugs targeting them. SCP2, ABCD3, MICOS10, GCDH, and MTRF1L were associated with most immune cells, while COX10 was not associated with any of the 96 immune cells.

Discussion

The identification of causal MRGs and their prognostic significance provides new insights into mitochondria‘s role in CRC. Drug prediction and immune correlations may guide therapy, but validation in larger cohorts and models is needed.

Conclusion

This study reveals causal associations between specific MRGs and CRC, identifies prognostic genes with therapeutic potential, and clarifies immune cell relationships, advancing CRC pathogenesis understanding and treatment development.

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结直肠癌线粒体相关基因的孟德尔随机化分析及预后基因筛选

线粒体与炎症性结直肠癌（CRC）的发展有关；然而，线粒体相关基因（MRGs）与CRC之间的关系尚不清楚。目的探讨MRGs与CRC的因果关系，筛选预后基因，进行药物预测分析，探讨预后基因与免疫细胞的相关性。材料与方法我们从MitoCarta3.0数据库中获得1136个MRGs，通过孟德尔随机化和敏感性测试分析MRGs表达、甲基化和蛋白丰度与CRC的因果关系。通过蛋白相互作用网络、富集、多组学和生存分析筛选预后基因。选择关键基因进行药物预测分析。采用Spearman相关法探讨预后基因与免疫细胞的相关性。结果44个mrg与结直肠癌有因果关系。6个基因（甾醇载体蛋白2 [SCP2]、ATP结合盒亚家族D成员3 [ABCD3]、细胞色素氧化酶组装因子血红素A）：法尼基转移酶[COX10]、线粒体接触位点和嵴组织系统亚基10 [MiCOS 10]、戊二酰辅酶A脱氢酶[GCDH]、线粒体翻译释放因子1样[MTRF1L]表达水平高时与结直肠癌有因果关系，且表达水平高时具有较好的预后意义，目前已有106种药物靶向它们。SCP2、ABCD3、MICOS10、GCDH和MTRF1L与大多数免疫细胞相关，而COX10与96个免疫细胞均不相关。因果MRGs的鉴定及其预后意义为线粒体在结直肠癌中的作用提供了新的见解。药物预测和免疫相关性可以指导治疗，但需要在更大的队列和模型中进行验证。结论本研究揭示了特异性MRGs与CRC之间的因果关系，鉴定了具有治疗潜力的预后基因，阐明了免疫细胞的关系，促进了对CRC发病机制的认识和治疗的发展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.