Prognostic value and immune infiltration analysis of a novel lactylation-related gene signature in endometrial cancer

IF 2.2 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Liqin Gu , Chunnian Zhang , Minjuan Xu , Fang Peng , Ruo-Hui Huang , Deping Luo
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引用次数: 0

Abstract

Background

Lactylation has been implicated in tumor growth, proliferation, and metastasis; however, its precise relationship with cancer remains poorly understood. This study aims to elucidate the role of lactylation-related genes (LRGs) in the development of endometrial cancer (EC).

Methods

We utilized data from The Cancer Genome Atlas (TCGA) database to analyze the expression and mutation patterns of LRGs in EC. Univariate Cox regression analysis and Lasso-Cox regression analysis were employed to identify prognosis-related genes and construct a risk model. EC samples were stratified into high-risk and low-risk groups based on the risk values derived from the model. These groups were validated using both training and validation cohorts. Additionally, we assessed differences in the immune microenvironment, tumor mutation burden (TMB), and drug response between the high-risk and low-risk groups.

Results

Differentially expressed genes (DEGs) between EC and control samples were identified, and their intersection with LRGs yielded differentially expressed lactylation-related genes (DLRGs). A total of six prognostic DLRGs (PFKM, H3C1, SIRT3, VIM, WAS, and LSP1) were selected and used to construct an EC risk model. Significant differences in prognosis, immune microenvironment, TMB, and drug sensitivity were observed between the high-expression and low-expression groups.

Conclusion

LRGs play a significant role in endometrial cancer by influencing cell growth, the immune microenvironment, and drug response. The six DLRGs included in the risk model may serve as potential prognostic markers and therapeutic targets for EC.
一种新的乳酸化相关基因标记在子宫内膜癌中的预后价值和免疫浸润分析
乳酸化与肿瘤生长、增殖和转移有关;然而,它与癌症的确切关系仍然知之甚少。本研究旨在阐明乳酸化相关基因(LRGs)在子宫内膜癌(EC)发生发展中的作用。方法利用美国癌症基因组图谱(TCGA)数据库的数据,分析LRGs在EC中的表达和突变模式。采用单因素Cox回归分析和Lasso-Cox回归分析鉴定预后相关基因,构建风险模型。根据模型得出的风险值,将EC样本分为高风险组和低风险组。使用训练组和验证组对这些组进行验证。此外,我们评估了免疫微环境、肿瘤突变负担(TMB)和药物反应在高危组和低危组之间的差异。结果鉴定出EC与对照样品的差异表达基因(DEGs),并与LRGs交叉产生差异表达的乳酸化相关基因(DLRGs)。共选择6个预后DLRGs (PFKM、H3C1、SIRT3、VIM、WAS和LSP1)构建EC风险模型。高表达组与低表达组在预后、免疫微环境、TMB、药物敏感性等方面存在显著差异。结论lrgs通过影响子宫内膜癌细胞生长、免疫微环境和药物反应等在子宫内膜癌中发挥重要作用。风险模型中包含的6种DLRGs可作为EC的潜在预后标志物和治疗靶点。
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
Biochemistry and Biophysics Reports
Biochemistry and Biophysics Reports Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
4.60
自引率
0.00%
发文量
191
审稿时长
59 days
期刊介绍: Open access, online only, peer-reviewed international journal in the Life Sciences, established in 2014 Biochemistry and Biophysics Reports (BB Reports) publishes original research in all aspects of Biochemistry, Biophysics and related areas like Molecular and Cell Biology. BB Reports welcomes solid though more preliminary, descriptive and small scale results if they have the potential to stimulate and/or contribute to future research, leading to new insights or hypothesis. Primary criteria for acceptance is that the work is original, scientifically and technically sound and provides valuable knowledge to life sciences research. We strongly believe all results deserve to be published and documented for the advancement of science. BB Reports specifically appreciates receiving reports on: Negative results, Replication studies, Reanalysis of previous datasets.
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