目的

探讨胆固醇生物合成相关基因（CBRG）在前列腺癌（PCa）中的预后和治疗意义。

方法

利用TCGA 数据库对胆固醇生物合成相关基因在PCa 和正常组织中的差异表达进行分析，并通过LASSO 及多因素Cox 回归分析构建风险评分预后模型。进一步通过单因素、多因素Cox 回归分析验证模型对PCa 的独立预后价值。根据风险评分的中位值将PCa 患者分为高风险组和低风险组。利用GSEA 分析观察高低风险组之间的差异富集通路。使用CIBERSORT 算法评估高低风险组肿瘤免疫细胞浸润情况。通过GDSC 数据库筛选与风险评分相关的潜在药物，并通过Spearman 检验分析风险评分与药物半数抑制浓度（IC50）的关联。Kaplan-Meier 比较特征基因高、低表达者的无病生存期（DFS）。Wilcoxon 检验特征基因在恩扎鲁胺耐药与未耐药中的表达差异。

结果

构建了包含PMVK、ACSL3、ABCG1、HMGCS2 和CYP11A1 基因的预后模型，该模型在预测1 年、3 年和5 年DFS 的AUC 分别为0.74、0.76 和0.72，在验证数据集中3 年和5 年的AUC 分别为0.70 和0.69。临床独立性分析发现该预后模型具有独立预测PCa 患者DFS 的能力，优于其他临床病理学特征。进一步分析PCa 患者高低风险组中肿瘤免疫细胞浸润水平的差异，结果表明在高风险组中CD8⁺ T 细胞、滤泡辅助性T 细胞和活化的NK 细胞的浸润水平显著降低，而初始B 细胞、静息状态的CD4⁺记忆T 细胞、调节性T 细胞和中性粒细胞浸润水平在高风险组显著升高。药物敏感性分析发现恩扎鲁胺、拉帕替尼等6 种药物的耐药性与风险评分呈正相关。GSEA 分析显示高风险主要富集的信号通路为氧化磷酸化、核糖体和蛋白酶体等。此外，生存分析发现HMGCS2 基因表达与患者的DFS 显著相关，对肿瘤预后有正向作用，且在恩扎鲁胺耐药患者中显著低表达。

结论

胆固醇生物合成相关特征基因是前列腺癌的独立预后标志物，HMGCS2 基因可能为潜在的治疗靶点，为前列腺癌的精准治疗提供了新思路。

Objective

To explore the prognostic and therapeutic significance of cholesterol biosynthesis-related genes （CBRG） in prostate cancer （PCa）.

Methods

The differential expression of cholesterol biosynthesis-related genes in PCa and normal tissues was analyzed using the TCGA database.A risk score prognostic model was constructed through LASSO and multivariate Cox regression analysis.The independent prognostic value of the model for PCa was further validated using univariate and multivariate Cox regression analyses.PCa patients were divided into high-risk and low-risk groups based on the median value of the risk score.GSEA analysis was used to observe the differentially enriched pathways between the high-risk and low-risk groups.The CIBERSORT algorithm was employed to assess tumor immune cell infiltration in the high-risk and low-risk groups.Potential drugs associated with the risk score were screened using the GDSC database，and the correlation between the risk score and the half-maximal inhibitory concentration （IC50） of the drugs was analyzed using the Spearman test.Kaplan-Meier analysis compared the disease-free survival （DFS） of patients with high and low expression of characteristic genes.The Wilcoxon test was used to analyze the expression differences of characteristic genes in enzalutamideresistant versus non-resistant cases.

Results

A prognostic model was constructed that included the genes PMVK，ACSL3，ABCG1，HMGCS2，and CYP11A1.This model had areas under the curve （AUC） of 0.74，0.76，and 0.72 for predicting 1-year，3-year，and 5-year DFS，respectively，with AUCs of 0.70 and 0.69 in the validation dataset for 3-year and 5-year DFS，respectively.Clinical independence analysis revealed that this prognostic model has the ability to independently predict DFS in PCa patients，outperforming other clinical pathological features.Further analysis of tumor immune cell infiltration levels in high-risk and lowrisk groups of PCa patients showed that the infiltration levels of CD8⁺ T cells，follicular helper T cells，and activated NK cells were significantly reduced in the high-risk group，while the infiltration levels of naïve B cells，resting CD4⁺ memory T cells，regulatory T cells，and neutrophils were significantly increased.Drug sensitivity analysis found that the resistance to six drugs，including enzalutamide and lapatinib，was positively correlated with the risk score.GSEA analysis indicated that the high-risk group was primarily enriched in pathways related to oxidative phosphorylation，ribosomes，and proteasomes.Additionally，survival analysis revealed a significant correlation between the expression of the HMGCS2 gene and patients' DFS，indicating a positive effect on tumor prognosis，and it was significantly downregulated in enzalutamide-resistant patients.

Conclusion

Cholesterol biosynthesis-related characteristic genes are independent prognostic markers for prostate cancer，and the HMGCS2 gene may serve as a potential therapeutic target，providing new insights for precision treatment of prostate cancer.