Prognostic Value of Fatty Acid Metabolism-related Genes in Patients with Bladder Cancer.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2024-01-01 DOI:10.2174/1574892818666230516143945

Qiuzheng Huang, Zhijia Li, Chao Liu

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引用次数: 0

Abstract

Introduction: This study aimed to explore the expression profiles of fatty acid metabolism- related genes (FAMRGs) in patients with bladder cancer (BLCA).

Methods: The corresponding clinicopathological features of BLCA patients and RNA sequencing data were downloaded from TCGA and GSE13507. Univariate Cox regression was used to determine the prognostic value of FRGS in BLCA patients. LASSO regression analysis was then performed to select potential risk genes and eliminate genes that might overfit the model. Based on the independent prognostication-related FRGs, the nomogram survival model was established using the root mean square value of the R packet to predict the 1-year, 3-year, and 5-year survival rates of BLCA patients. By determining the area under the curve (AUC) value, the time-dependent receiver operating characteristic curve (ROC) was used to evaluate the prognostic efficiency of our model.

Results: A total of 243 DEFRGs were identified. Twenty FRGs were found to be related to the prognosis of BLCA in the TCGA database. Survival curves showed that high-risk patients had significantly shorter OS than low-risk cases (p < 0.001). The AUC of risk was 0.784, which was superior to age, sex, and stage, suggesting that the risk score was more favorable in predicting OS than traditional pathologic prognostic factors. The AUC was 0.757 at 1 year, 0.732 at 3 years, and 0.733 at 5 year-OS.

Conclusion: In this study, we demonstrated that a FAMRG prognosis biomarker is associated with the tumor immune microenvironment in patients with BLCA.

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脂肪酸代谢相关基因在膀胱癌患者中的预后价值

本研究旨在探讨脂肪酸代谢相关基因（FAMRGs）在癌症（BLCA）患者中的表达谱。从TCGA和GSE13507下载了BLCA患者相应的临床病理特征和RNA测序数据。单变量Cox回归用于确定FRGS对BLCA患者的预后价值。然后进行LASSO回归分析，以选择潜在的风险基因并消除可能过度拟合模型的基因。基于独立的预测相关FRG，使用R数据包的均方根值建立列线图生存模型，以预测BLCA患者的1年、3年和5年生存率。通过确定曲线下面积（AUC）值，使用与时间相关的受试者工作特征曲线（ROC）来评估我们模型的预后效率。共发现243个DEFRG。在TCGA数据库中发现20个FRG与BLCA的预后有关。生存曲线显示，高危患者的OS明显短于低危患者（P<0.001）。风险AUC为0.784，优于年龄、性别和分期，表明风险评分在预测OS方面比传统的病理预后因素更有利。AUC在1年时为0.757，在3年时为0.732，在5年-OS时为0.733。在本研究中，我们证明了FAMRG预后生物标志物与BLCA患者的肿瘤免疫微环境相关。

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

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464

期刊介绍： ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.