Construction of a risk prediction model for prostate cancer recurrence based on cholesterol metabolism-related genes

doi:10.3760/cma.j.issn.2095-8757.2025.01.005

Abstract

Abstract:

Objective

To analyze the expression changes of cholesterol metabolism-related genes in prostate cancer， and to construct a risk prediction model for prostate cancer recurrence.

Methods

RNA sequencing data and clinical data of prostate cancer case samples were obtained from the Cancer Genome Atlas database， and cholesterol metabolism-related genes were retrieved from the molecular characteristics database. Cholesterol metabolism-related genes as biomarkers of prostate cancer recurrence were identified by differential expression analysis and weighted gene co-expression network analysis. univariate Cox analysis and LASSO algorithm were used to further screen the genes， and a risk prediction model for prostate cancer recurrence was established and validated. The association between risk scores and clinical characteristics of prostate cancer patients were analyzed， and the univariate and multivariate Cox regression analyses were performed to identify independent predictors of prostate cancer recurrence. A nomogram was developed based on the independent predictors， and its predictive performance was evaluated using calibration curves.

Results

Three cholesterol metabolism-related genes， COMP， MYOCD and ACTC1， were identified as biomarkers for prostate cancer recurrence. The risk model was constructed， and the high-risk group had a significantly higher probability of recurrence than the low-risk group （P ＜ 0.05）. The area under the curve for predicting 1-， 3-， and 5-year recurrence in prostate cancer patients exceeded 0.6. The nomogram incorporating the risk score and T-stage demonstrated excellent predictive accuracy， with calibration curve slopes approaching 1， indicating satisfactory predictive performance.

Conclusion

This study confirms the potential of cholesterol metabolism-related genes as biomarkers for prostate cancer recurrence and lays the foundation for the establishment of a novel risk model with powerful stratification capabilities and clinical utility for personalized treatment.

Key words: Prostate cancer, Recurrence, Cholesterol metabolism, Transcriptomic, RNA sequencing, Biomarkers

Jikai Shi, Ping Wang, Jun Chen. Construction of a risk prediction model for prostate cancer recurrence based on cholesterol metabolism-related genes[J]. Chinese Journal of Geriatrics Research(Electronic Edition), 2025, 12(01): 22-29.

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URL: https://zhlnbyjdzzz.cma-cmc.com.cn/EN/10.3760/cma.j.issn.2095-8757.2025.01.005

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References 26

［1］	Blas L， Onozawa M， Shiota M， et al. Long-term outcomes of androgen deprivation therapy in prostate cancer among Japanese men over 80 years old［J］. Cancer Sci， 2021， 112（8）：3074-3082.
［2］	Rawla P. Epidemiology of prostate cancer［J］. World J Oncol，2019， 10（2）：63-89.
［3］	Siegel R， Ma J， Zou Z， et al. Cancer statistics， 2014［J］. CA Cancer J Clin， 2014， 64（1）：9-29.
［4］	Banuelos CA， Tavakoli I， Tien AH， et al. Sintokamide a is a novel antagonist of androgen receptor that uniquely binds activation function-1 in its amino-terminal domain［J］. J Biol Chem， 2016，291（42）：22231-22243.
［5］	Jetty S， Loftus JR， Patel A， et al. Prostate cancer-PET imaging update［J］. Cancers （Basel）， 2023， 15（3）：796.
［6］	Macedo-Silva C， Benedetti R， Ciardiello F， et al. Epigenetic mechanisms underlying prostate cancer radioresistance［J］. Clin Epigenetics， 2021， 13（1）：125.
［7］	Giunchi F， Fiorentino M， Loda M. The Metabolic Landscape of Prostate Cancer［J］. Eur Urol Oncol， 2019， 2（1）：28-36.
［8］	Twiddy AL， Leon CG， Wasan KM. Cholesterol as a potential target for castration-resistant prostate cancer［J］. Pharm Res， 2011，28（3）：423-437.
［9］	Xu H， Zhou S， Tang Q， et al. Cholesterol metabolism： New functions and therapeutic approaches in cancer［J］. Biochim Biophys Acta Rev Cancer， 2020，1874（1）：188394.
［10］	Heir T， Falk RS， Robsahm TE， et al. Cholesterol and prostate cancer risk： A long-term prospective cohort study［J］. BMC Cancer，2016， 16：643.
［11］	Wei C， Tian L， Jia B， et al. Association between Serum Triglycerides and Prostate Specific Antigen （PSA） among U.S. males： National health and nutrition examination survey（NHANES）， 2003-2010［J］. Nutrients， 2022，14（7）.
［12］	Hänzelmann S， Castelo R， Guinney J. GSVA： Gene set variation analysis for microarray and RNA-seq data［J］. BMC Bioinformatics， 2013， 14：7.
［13］	Russo GI， Asmundo MG， Lo Giudice A， et al. Is there a role of warburg effect in prostate cancer aggressiveness？Analysis of expression of enzymes of lipidic metabolism by immunohistochemistry in prostate cancer patients （DIAMOND Study）［J］. Cancers （Basel）， 2023， 15（3）.
［14］	Dambal S， Howard LE， Allott EH， et al. Serum lipids prior to starting androgen deprivation therapy and risk of castration resistant prostate cancer and metastasis： Results from the SEARCH database［J］. J Urol， 2020， 203（1）：120-127.
［15］	Han W， Gao S， Barrett D， et al. Reactivation of androgen receptorregulated lipid biosynthesis drives the progression of castrationresistant prostate cancer. Oncogene［J］. 2018， 37（6）：710-721.
［16］	Revilla G， Cedó L， Tondo M， et al. LDL， HDL and endocrinerelated cancer： From pathogenic mechanisms to therapies［J］.Semin Cancer Biol， 2021， 73：134-157.
［17］	Kosacka J， Nowicki M， Klöting N， et al. COMP-angiopoietin-1 recovers molecular biomarkers of neuropathy and improves vascularisation in sciatic nerve of ob/ob mice［J］. PLoS One， 2012，7（3）：e32881.
［18］	Xia XD， Yu XH， Chen LY， et al. Myocardin suppression increases lipid retention and atherosclerosis via downregulation of ABCA1 in vascular smooth muscle cells［J］. Biochim Biophys Acta Mol Cell Biol Lipids， 2021， 1866（4）：158824.
［19］	Gu C， Yang Z， Tan H， et al. Decreased plasma COMP and increased plasma CTX-II levels in a Chinese pseudoachondroplasia family with novel COMP mutation［J］. Biomed Res Int， 2017，2017：5809787.
［20］	Chen J， Xi J， Tian Y， et al. Identification， prioritization， and evaluation of glycoproteins for aggressive prostate cancer using quantitative glycoproteomics and antibody-based assays on tissue specimens［J］. Proteomics， 2013， 13（15）：2268-2277.
［21］	Zhou L， Liu Y， Lu L， et al. Cardiac gene activation analysis in mammalian non-myoblasic cells by Nkx2-5， Tbx5， Gata4 and Myocd［J］. PLoS One， 2012， 7（10）：e48028.
［22］	Tong X， Wang S， Lei Z， et al. MYOCD and SMAD3/SMAD4 form a positive feedback loop and drive TGF-β-induced epithelialmesenchymal transition in non-small cell lung cancer［J］.Oncogene， 2020， 39（14）：2890-2904.
［23］	Shi X， Feng D， Han P， et al. Ferroptosis-related ACSL3 and ACTC1 predict metastasis-free survival for prostate cancer patients undergoing radical radiotherapy［J］. Asian J Surg， 2023，46（6）：2489-2290.
［24］	Jiang HK， Qiu GR， Li-Ling J， et al. Reduced ACTC1 expression might play a role in the onset of congenital heart disease by inducing cardiomyocyte apoptosis［J］. Circ J， 2010， 74（11）：2410-2418.
［25］	Dong P， Flores J， Pelton K， et al. Prohibitin is a cholesterolsensitive regulator of cell cycle transit［J］. J Cell Biochem， 2010，111：1367-1374.
［26］	Huang L， Xu Z， Xie Y， et al. Comprehensive characterization of ageing-relevant subtypes associated with different tumorigenesis and tumor microenvironment in prostate cancer［J］. Front Mol Biosci， 2022， 9：803474.

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