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鉴定线粒体通透性转换相关长链非编码RNA作为乳腺癌预后和治疗的定量生物标志物。

Identification of mitochondrial permeability transition-related lncRNAs as quantitative biomarkers for the prognosis and therapy of breast cancer.

作者信息

Lin Zhongshu, Wang Xinlu, Hua Guanxiang, Zhong Fangmin, Cheng Wangxinjun, Qiu Yuxiang, Chi Zhe, Zeng Huan, Wang Xiaozhong

机构信息

Jiangxi Province Key Laboratory of Immunology and Inflammation, Jiangxi Provincial Clinical Research Center for Laboratory Medicine, Department of Clinical Laboratory, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.

School of Biological and Behavioural Science, Queen Mary University of London, London, United Kingdom.

出版信息

Front Genet. 2025 Mar 26;16:1510154. doi: 10.3389/fgene.2025.1510154. eCollection 2025.

Abstract

Breast cancer (BC) continues to pose a global health threat and presents challenges for treatment due to its high heterogeneity. Recent advancements in the understanding of mitochondrial permeability transition (MPT) and the regulatory roles of long non-coding RNAs (lncRNAs) offer potential insights for the stratification and personalized treatment of BC. Although the association between MPT and lncRNAs has not been widely studied, a few research studies have indicated a regulatory impact of lncRNAs on MPT, further deepening the understanding of the tumor. To identify reliable biomarkers associated with MPT for managing BC, bulk RNA-seq data of MPT-related lncRNAs acquired from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project were utilized to assess BC patients. A scoring system, termed the MPT-related score (MPTRscore), was developed using LASSO-Cox regression on data from 1,029 BC patients from TCGA-BRCA. Meanwhile, the superior prognostic accuracy of the MPTRscore was demonstrated by comparing it with biomarkers, including PAM50 subtyping for standardization. Subsequently, a clinical prediction model was created by incorporating the MPTRscore and clinical variables. This analysis revealed two distinct MPTRscore groups characterized by different biomolecular processes, tumor microenvironment (TME) patterns, and clinical outcomes. The MPTRscore was further investigated through unsupervised consensus clustering of TCGA-BRCA based on MPTRscore-related prognostic genes. Additionally, the MPTRscore was identified as an independent prognostic factor for BC and showed guiding utility in immunotherapy and chemotherapy response. Specifically, patients with a low MPTRscore exhibited better prognosis and treatment responses compared to those with a high MPTRscore. Significantly, the relevance of clustering results and MPTRscore was found to be mediated by lncRNA transcript RP11-573D15.8-018. In conclusion, MPTRscore-related clusters were identified in BC, and an integrative score was developed as a biomarker for predicting BC prognosis and therapeutic response. Additionally, molecular interactions underlying the relationship between MPTRscore-related clusters and MPTRscore were uncovered, proving insights for BC stratification. These findings may aid in prognosis determination and therapeutic decision-making for BC patients.

摘要

乳腺癌(BC)仍然是全球健康的一大威胁,因其高度异质性,在治疗方面也面临挑战。近期,在对线粒体通透性转换(MPT)以及长链非编码RNA(lncRNA)调控作用的理解上取得的进展,为BC的分层治疗和个性化治疗提供了潜在见解。尽管MPT与lncRNAs之间的关联尚未得到广泛研究,但一些研究表明lncRNAs对MPT有调控作用,这进一步加深了对肿瘤的认识。为了确定与MPT相关的可靠生物标志物以管理BC,利用从癌症基因组图谱(TCGA)和基因型-组织表达(GTEx)项目获取的MPT相关lncRNAs的批量RNA测序数据来评估BC患者。使用LASSO-Cox回归对来自TCGA-BRCA的1029例BC患者的数据开发了一种评分系统,称为MPT相关评分(MPTRscore)。同时,通过将MPTRscore与包括标准化的PAM50亚型在内的生物标志物进行比较,证明了MPTRscore具有更高的预后准确性。随后,通过纳入MPTRscore和临床变量创建了一个临床预测模型。该分析揭示了两个不同的MPTRscore组,其特征在于不同的生物分子过程、肿瘤微环境(TME)模式和临床结果。通过基于MPTRscore相关预后基因对TCGA-BRCA进行无监督一致性聚类,进一步研究了MPTRscore。此外,MPTRscore被确定为BC的独立预后因素,并在免疫治疗和化疗反应中显示出指导作用。具体而言,与高MPTRscore的患者相比,低MPTRscore的患者表现出更好的预后和治疗反应。值得注意的是,发现聚类结果与MPTRscore的相关性是由lncRNA转录本RP11-573D15.8-018介导的。总之,在BC中鉴定出了与MPTRscore相关的聚类,并开发了一种综合评分作为预测BC预后和治疗反应的生物标志物。此外,还揭示了与MPTRscore相关聚类和MPTRscore之间关系的分子相互作用,为BC分层提供了见解。这些发现可能有助于BC患者的预后判定和治疗决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e45d/11979797/4a7c3dcd5e0d/fgene-16-1510154-g001.jpg

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