ORIGINAL RESEARCH article
Front. Genet.
Sec. Cancer Genetics and Oncogenomics
Volume 16 - 2025 | doi: 10.3389/fgene.2025.1604113
This article is part of the Research TopicClinical prediction models in cancer through bioinformaticsView all 17 articles
Developing prognostic models for cholesterol related gene linked with immune infiltration in prostate cancer
Provisionally accepted
- School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China
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Background: Prostate cancer has a high incidence and a low five-year survival rate. We aimed to combine cholesterol and immune-related genes to screen prostate cancer prognosis-related genes and construct prognostic risk model. Methods: We obtained clinical data of prostate cancer through publicly released the cancer genome atlas (TCGA). Cholesterol and immune-related genes were separately collected from mSigDB and ImmPort database. The prognostic model based on immune-cholesterol-related differentially expressed mRNAs (DEmRNAs) network was constructed by univariate and multivariate Cox regression methods. Furthermore, gene set enrichment analysis (GSEA), mutation landscape analysis, and immune infiltration analysis were carried out to investigate the role of immune-cholesterol-related DEmRNAs in prostate cancer. Results: We identified eleven immune-cholesterogenic-related DEmRNAs (C2orf88, TRPM4, SAPCD2, RHPN1, RAC3, APOF, PTGS2, TSPAN1, KLK4, ENTPD5, and C1orf64) as risk factors that were related to the occurrence and development of prostate cancer by bioinformatics analysis. Immune infiltration analysis suggested immune-cholesterol-related DEmRNAs may act as an immunomodulatory role for treatment decisions. Proportion of plasma cells, memory resting CD4 T cells and neutrophils in low-risk group was significantly higher than that in high-risk group (p < 0.05). The GSEA analysis revealed DEmRNAs were enriched in 58 KEGG pathways, consisting of hematopoietic cell lineage, hypertrophic cardiomyopathy, jak stat signaling pathway. The gleason score of the high-risk group showed a significant difference compared with the low-risk group after clinical data analysis (p < 0.05). Conclusion: The prognostic risk model and nomogram constructed based on the immune-cholesterol-related genes had a great prognostic performance for prostate cancer.
Keywords: prostate cancer, immune-related genes, Cholesterol, Immunity, prognosis
Received: 01 Apr 2025; Accepted: 28 Aug 2025.
Copyright: © 2025 Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jie Wu, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China
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