Novel mitochondrial-related gene signature predicts prognosis and immunological status in glioma.

IF 1.5 4区医学 Q4 ONCOLOGY

Translational cancer research Pub Date : 2024-07-31 Epub Date: 2024-07-26 DOI:10.21037/tcr-23-2072

Yongsheng Liu, Lize Cai, Hao Wang, Lin Yao, Kai Zhang, Guangliang Chen, Youxin Zhou

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引用次数: 0

Abstract

Background: Mitochondria are the center of cellular metabolism. The relationship between mitochondria and diseases has also been studied for a long time. However, the prognostic role of mitochondrial-related genes (MRGs) in patients with glioma and their biological effects are still unclear. The aim of the study was to construct a mitochondria-related model to assess prognosis and potential biological effects like immune infiltration, gene pathway and mutation, and give some predictive chemotherapeutic agents.

Methods: The data of 675 patients from The Cancer Genome Atlas (TCGA) database were used to identify MRG signature and construct a prognostic model. After validating its robustness in Chinese Glioma Genome Atlas (CGGA), two risk groups derived from the prognostic model were then conducted with Gene Set Enrichment Analysis (GSEA), immune status, mutation status and chemotherapeutic agents prediction.

Results: The prognostic model built from six gene signatures can successfully predict the prognosis and reflect clinicopathological characteristics. Patients in high-risk group displayed significantly worse overall survival (OS), immunosuppression effects, and mutation markers with worse prognosis. Twelve chemotherapeutic agents with strongly correlated sensitivity and risk scores were selected as potential agents.

Conclusions: The novel MRG signatures (TYMP, TSFM, MGME1, BOLA3, TRMT5, NDUFA9) can predict prognosis and immunological status in glioma.

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新的线粒体相关基因特征可预测胶质瘤的预后和免疫状态。

背景：线粒体是细胞新陈代谢的中心：线粒体是细胞新陈代谢的中心。线粒体与疾病的关系也被研究了很长时间。然而，线粒体相关基因（MRGs）在胶质瘤患者中的预后作用及其生物学效应仍不清楚。该研究旨在构建线粒体相关模型，以评估预后和潜在的生物学效应，如免疫浸润、基因通路和突变，并给出一些预测性化疗药物：方法：利用癌症基因组图谱（TCGA）数据库中675例患者的数据识别MRG特征并构建预后模型。在中国胶质瘤基因组图谱（CGGA）中验证其稳健性后，对预后模型得出的两个风险组进行了基因组富集分析（GSEA）、免疫状态、突变状态和化疗药物预测：结果：根据六个基因特征建立的预后模型可以成功预测预后并反映临床病理特征。高危组患者的总生存期（OS）、免疫抑制效应和突变标志物均明显较差，预后较差。12种敏感性与风险评分密切相关的化疗药物被选为潜在药物：结论：新型MRG特征（TYMP、TSFM、MGME1、BOLA3、TRMT5、NDUFA9）可预测胶质瘤的预后和免疫状态。

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

Translational cancer research ONCOLOGY-

CiteScore

2.10

自引率

0.00%

发文量

252

期刊介绍： Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.