Suppr超能文献

用于肾上腺皮质癌预后预测和治疗靶点的衰老相关基因特征

A Senescence-Associated Gene Signature for Prognostic Prediction and Therapeutic Targeting in Adrenocortical Carcinoma.

作者信息

Peng Hangya, Chen Qiujing, Ye Lei, Wang Weiqing

机构信息

Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.

Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.

出版信息

Biomedicines. 2025 Apr 8;13(4):894. doi: 10.3390/biomedicines13040894.

Abstract

: Cellular senescence plays a critical role in tumorigenesis, immune cell infiltration, and treatment response. Adrenocortical carcinoma (ACC) is a malignant tumor that lacks effective therapies. This study aimed to construct and validate a senescence-related gene signature as an independent prognostic predictor for ACC and explore its impact on the tumor microenvironment, immunotherapy, and chemotherapy response. : Data were collected from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Using Kaplan-Meier survival analysis, LASSO penalized Cox regression and multivariable Cox regression, we identified a prognostic model with four senescence-related genes (HJURP, CDK1, FOXM1, and CHEK1). The model's prognostic value was validated through survival analysis, risk score curves, and receiver operating characteristic (ROC) curves. Tumor mutation burden was assessed with maftools, and the tumor microenvironment was analyzed using CIBERSORT and ESTIMATE. Immune and chemotherapeutic responses were assessed through Tumor Immune Dysfunction and Exclusion (TIDE) and OncoPredict. : The risk score derived from our model showed a strong association with overall survival (OS) in ACC patients ( < 0.001, HR = 2.478). Higher risk scores were correlated with more advanced tumor stages and a greater frequency of somatic mutations. Differentially expressed genes (DEGs) that were downregulated in the high-risk group were significantly enriched in immune-related pathways. Furthermore, high-risk patients were predicted to have reduced sensitivity to immunotherapy ( = 0.02). Bioinformatics analysis identified potential chemotherapeutic agents, including BI-2536 and MIM1, as more effective treatment options for high-risk patients. : Our findings indicate that this prognostic model may serve as a valuable tool for predicting overall survival (OS) and treatment responses in ACC patients, including those receiving chemotherapy and immunotherapy.

摘要

细胞衰老在肿瘤发生、免疫细胞浸润和治疗反应中起关键作用。肾上腺皮质癌(ACC)是一种缺乏有效治疗方法的恶性肿瘤。本研究旨在构建并验证一种与衰老相关的基因特征作为ACC的独立预后预测指标,并探讨其对肿瘤微环境、免疫治疗和化疗反应的影响。:数据收集自癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)。使用Kaplan-Meier生存分析、LASSO惩罚Cox回归和多变量Cox回归,我们确定了一个包含四个与衰老相关基因(HJURP、CDK1、FOXM1和CHEK1)的预后模型。通过生存分析、风险评分曲线和受试者工作特征(ROC)曲线验证了该模型的预后价值。使用maftools评估肿瘤突变负荷,并使用CIBERSORT和ESTIMATE分析肿瘤微环境。通过肿瘤免疫功能障碍和排除(TIDE)以及OncoPredict评估免疫和化疗反应。:我们模型得出的风险评分与ACC患者的总生存期(OS)密切相关(<0.001,HR = 2.478)。较高的风险评分与更晚期的肿瘤分期和更高的体细胞突变频率相关。在高风险组中下调的差异表达基因(DEG)在免疫相关途径中显著富集。此外,预测高风险患者对免疫治疗的敏感性降低(= 0.02)。生物信息学分析确定了潜在的化疗药物,包括BI-2536和MIM1,作为高风险患者更有效的治疗选择。:我们的研究结果表明,这种预后模型可能是预测ACC患者总生存期(OS)和治疗反应的有价值工具,包括接受化疗和免疫治疗的患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ca1/12025298/1f6799d6e687/biomedicines-13-00894-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验