前列腺癌中的免疫微环境浸润景观和免疫相关亚型。

BACKGROUND: The tumor microenvironment (TME) primarily comprises cancer cells, cancer-infiltrating immune cells, and stromal cells. The tumor cells alter the TME by secreting signaling molecules to induce immune tolerance. The immune cell infiltrating the TME influences the prognosis of patients with cancers. However, immune cell infiltration (ICI) in the TME of patients with prostate cancer (PC) has not yet been studied. METHODS: In this study, we used Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and Estimation of Stromal and Immune cells in Malignant Tumors using Expression data (ESTIMATE) algorithms to identify three ICI clusters based on 1,099 genes associated with ICI in the TME. The patients were classified into three distinct ICI gene clusters based on overlapping differentially expressed genes in ICI clusters. Furthermore, the ICI scores were calculated using principal component analysis. RESULTS: The results revealed that patients with high ICI scores had poor prognoses and reduced expression of immune-checkpoint genes and immune-related genes. Furthermore, the transforming growth factor-beta (TGF-β) and WNT-β signaling pathways were enriched in the high ICI score subgroup, which suggests that suppression of T cells could contribute to poor prognosis of patients with PC. A positive correlation was observed between the high-ICI-score subgroup and the high tumor mutation burden (TMB) value. Patients with low ICI scores could benefit from immunotherapy, indicating that the ICI score could be used to predict the efficacy of immunotherapeutic response. CONCLUSIONS: In summary, we provide a comprehensive overview of the landscape of ICI in PC, which could aid in designing the strategies for immunotherapy for patients with PC.

背景：肿瘤微环境（TME）主要由癌细胞、浸润肿瘤的免疫细胞和基质细胞组成。癌细胞通过分泌信号分子诱导免疫耐受来改变 TME。浸润 TME 的免疫细胞影响癌症患者的预后。然而，前列腺癌（PC）患者 TME 中的免疫细胞浸润尚未得到研究。

方法：在这项研究中，我们使用 Cell-type identification by Estimating Relative Subsets of RNA Transcripts（CIBERSORT）和 Estimation of Stromal and Immune cells in Malignant Tumors using Expression data（ESTIMATE）算法，基于与 TME 中免疫浸润相关的 1099 个基因，鉴定出三个免疫浸润聚类。根据免疫浸润聚类中重叠的差异表达基因，将患者分为三个不同的免疫浸润基因聚类。此外，使用主成分分析计算免疫浸润评分。

结果：结果表明，高免疫浸润评分的患者预后较差，免疫检查点基因和免疫相关基因表达下调。此外，转化生长因子-β（TGF-β）和 WNT-β 信号通路在高免疫浸润评分亚组中富集，这表明抑制 T 细胞可能导致 PC 患者预后不良。高免疫浸润评分亚组与高肿瘤突变负荷（TMB）值呈正相关。低免疫浸润评分的患者可能受益于免疫治疗，这表明免疫浸润评分可用于预测免疫治疗反应的疗效。

结论：总之，我们全面概述了 PC 中的免疫浸润情况，这有助于为 PC 患者的免疫治疗策略设计提供参考。