Alternative Polyadenylation Regulatory Factors Signature for Survival Prediction in Kidney Renal Cell Carcinoma.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Cancer Informatics Pub Date : 2024-04-12 eCollection Date: 2024-01-01 DOI:10.1177/11769351231180789

Xiaoyu Wang, Yao Lin, Zheng Li, Yueqi Li, Mingcong Chen

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Abstract

Background: Alternative polyadenylation (APA) plays a vital regulatory role in various diseases. It is widely accepted that APA is regulated by APA regulatory factors.

Objective: Whether APA regulatory factors affect the prognosis of renal cell carcinoma remains unclear, and this is the main topic of this study.

Methods: We downloaded the transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database. We used the Lasso regression system to construct an APA model for analyzing the relationship between common APA regulatory factors and renal cell carcinoma. We also validated our APA model using independent GEO datasets (GSE29609, GSE76207).

Results: It was found that the expression levels of 5 APA regulatory factors (CPSF1, CPSF2, CSTF2, PABPC1, and PABPC4) were significantly associated with tumor gene mutation burden (TMB) score in renal clear cell carcinoma, and the risk score constructed using the expression level of 5 key APA regulatory factors could be used to predict the outcome of renal clear cell carcinoma. The TMB score is associated with the remodeling of the immune microenvironment.

Conclusions: By identifying key APA regulatory factors in renal cell carcinoma and constructing risk scores for key APA regulatory factors, we showed that key APA regulators affect prognosis of renal clear cell carcinoma patients. In addition, the risk score level is associated with TMB, indicating that APA may affect the efficacy of immunotherapy through immune microenvironment-related genes. This helps us better understand the mRNA processing mechanism of renal clear cell carcinoma.

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用于肾脏肾细胞癌生存预测的替代多腺苷酸化调控因子图谱

背景：替代多腺苷酸化（APA）在各种疾病中发挥着重要的调控作用。人们普遍认为，APA受APA调节因子的调控：APA调节因子是否影响肾细胞癌的预后仍不清楚，这是本研究的主要课题：我们从癌症基因组图谱（TCGA）数据库中下载了转录组和临床数据。方法：我们从癌症基因组图谱（TCGA）数据库中下载了转录组和临床数据，并使用 Lasso 回归系统构建了一个 APA 模型，用于分析常见 APA 调控因子与肾细胞癌之间的关系。我们还利用独立的 GEO 数据集（GSE29609、GSE76207）验证了我们的 APA 模型：结果发现，5个APA调控因子（CPSF1、CPSF2、CSTF2、PABPC1和PABPC4）的表达水平与肾透明细胞癌的肿瘤基因突变负荷（TMB）评分显著相关，利用5个关键APA调控因子的表达水平构建的风险评分可用于预测肾透明细胞癌的预后。TMB评分与免疫微环境的重塑有关：通过识别肾细胞癌的关键APA调控因子并构建关键APA调控因子的风险评分，我们发现关键APA调控因子会影响肾透明细胞癌患者的预后。此外，风险评分水平与TMB相关，表明APA可能通过免疫微环境相关基因影响免疫治疗的疗效。这有助于我们更好地理解肾透明细胞癌的mRNA处理机制。

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 Informatics Medicine-Oncology

CiteScore

3.00

自引率

5.00%

发文量

审稿时长

8 weeks

期刊介绍： The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.