前列腺癌
组蛋白
生物
癌症研究
比例危险模型
肿瘤科
癌症
基因表达
内科学
基因
医学
遗传学
作者
Zhou Sun,Jie Wang,Qiang Zhang,Xiangdi Meng,Zhaosen Ma,Jiqiang Niu,Rui Guo,Lisa Jia Tran,Jing Zhang,Yunfei Liu,Fangdie Ye,Baoluo Ma
摘要
Abstract Introduction Prostate cancer is a common cancer among male population. The aberrant expression of histone modifiers has been identified as a potential driving force in numerous cancer types. However, the mechanism of histone modifiers in the development of prostate cancer remains unknown. Methods Expression profiles and clinical data were obtained from GSE70769, GSE46602, and GSE67980. Seruat R package was utilized to calculate the gene set enrichment of the histone modification pathway and obtain the Histone score. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were employed to identify marker genes with prognostic value. Kaplan–Meier survival analysis was conducted to assess the efficacy of the prognostic model. In addition, microenvironment cell populations counter (MCPcounter), single‐sample gene set enrichment analysis (ssGSEA), and xCell algorithms were employed for immune infiltration analysis. Drug sensitivity prediction was performed using oncoPredict R package. Results We screened differentially expressed genes (DEGs) between Histone‐high score (Histone‐H) and Histone‐low score (Histone‐L) groups, which were enriched in RNA splicing and DNA‐binding transcription factor binding pathways. We retained four prognostic marker genes, including TACC3, YWHAH, TAF1C and TTLL5 . The risk model showed significant efficacy in stratification of the prognosis of prostate cancer patients in both internal and external cohorts ( p < .0001 and p = .032, respectively). In addition, prognostic gene YWHAH was infiltrated in abundance of fibroblasts and highly correlated with Entinostat_1593 drug sensitivity score and the value of risk score. Conclusion We innovatively developed a histone modification‐related prognostic model with high prognostic potency and identified YWHAH as possible diagnostic and therapeutic biomarkers for prostate cancer. It provides novel insights to address prostate cancer and enhance clinical outcomes, thereby opening up a new avenue for customized treatment alternatives.
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