Identification of PI3K-AKT Pathway-Related Genes and Construction of Prognostic Prediction Model for ccRCC

IF 1.9 Q4 ONCOLOGY Cancer reports Pub Date : 2024-09-05 DOI:10.1002/cnr2.70010

Shaowen Hu, Xiaoli Zhang, Huiru Xin, Mingjie Guo, Yafei Xiao, Zhongwei Chang, Qingyang Luo, Yang Li, Chaoyang Zhu

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Abstract

Background

Clear cell renal cell carcinoma (ccRCC), the predominate histological type of renal cell carcinoma (RCC), has been extensively studied, with poor prognosis as the stage increases. Research findings consistently indicated that the PI3K-Akt pathway is commonly dysregulated across various cancer types, including ccRCC. Targeting the PI3K-Akt pathway held promise as a potential therapeutic approach for treating ccRCC. Development and validation of PI3K-Akt pathway-related genes related biomarkers can enhance healthcare management of patients with ccRCC.

Purpose

This study aimed to identify the key genes in the PI3K-Akt pathway associated with the diagnosis and prognosis of CCRCC using data mining from the Cancer Genome Atlas (TCGA) and Gene Expression Synthesis (GEO) datasets.

Methods

The purpose of this study is to use bioinformatics methods to screen data sets and clinicopathological characteristics associated with ccRCC patients. The exhibited significantly differential expressed genes (DEGs) associated with the PI3K-Akt pathway were examined by KEGG. In addition, Kaplan–Meier (KM) analysis used to estimate the survival function of the differential genes by using the UALCAN database and graphPad Prism 9.0. And exploring the association between the expression levels of the selected genes and the survival status and time of patients with ccRCC based on SPSS22.0. Finally, a multigene prognostic model was constructed to assess the prognostic risk of ccRCC patients.

Results

A total of 911 genes with common highly expressed were selected based on the GEO and TCGA databases. According to the KEGG pathway analysis, there were 42 genes enriched in PI3K-Akt signalling pathway. And seven of highly expressed genes were linked to a poor prognosis in ccRCC. And a multigene prognostic model was established based on IL2RG, EFNA3, and MTCP1 synergistic expression might be utilized to predict the survival of ccRCC patients.

Conclusions

Three PI3K-Akt pathway-related genes may be helpful to identify the prognosis and molecular characteristics of ccRCC patients and to improve therapeutic regimens, and these risk characteristics might be further applied in the clinic.

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鉴定 PI3K-AKT 通路相关基因并构建 ccRCC 预后预测模型

背景：透明细胞肾细胞癌（ccRCC）是肾细胞癌（RCC）的主要组织学类型，已被广泛研究，随着分期的增加，预后较差。研究结果一致表明，PI3K-Akt通路在包括ccRCC在内的各种癌症类型中普遍失调。靶向 PI3K-Akt 通路有望成为治疗 ccRCC 的潜在疗法。目的：本研究旨在利用癌症基因组图谱（TCGA）和基因表达合成（GEO）数据集的数据挖掘，确定与CCRCC诊断和预后相关的PI3K-Akt通路关键基因：本研究的目的是利用生物信息学方法筛选与ccRCC患者相关的数据集和临床病理特征。通过 KEGG 方法研究了与 PI3K-Akt 通路相关的差异表达基因（DEGs）。此外，还利用 UALCAN 数据库和 graphPad Prism 9.0 进行了 Kaplan-Meier (KM) 分析，以估计差异基因的生存功能。并基于 SPSS22.0 探索所选基因的表达水平与 ccRCC 患者生存状态和时间之间的关联。最后，构建了一个多基因预后模型来评估ccRCC患者的预后风险：结果：基于 GEO 和 TCGA 数据库，共筛选出 911 个常见高表达基因。根据KEGG通路分析，有42个基因富集在PI3K-Akt信号通路中。其中7个高表达基因与ccRCC的不良预后有关。根据IL2RG、EFNA3和MTCP1的协同表达建立的多基因预后模型可用于预测ccRCC患者的生存期：结论：三个PI3K-Akt通路相关基因可能有助于识别ccRCC患者的预后和分子特征，并改进治疗方案，这些风险特征可能会进一步应用于临床。

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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