Urology Department, Kunming Medical University Second Affiliated Hospital, Kunming, Yunnan, China.
Ann Med. 2024 Dec;56(1):2398195. doi: 10.1080/07853890.2024.2398195. Epub 2024 Sep 2.
Prostate cancer (PCa) has become the highest incidence of malignant tumor among men in the world. Tumor microenvironment (TME) is necessary for tumor growth. M2 macrophages play an important role in many solid tumors. This research aimed at the role of M2 macrophages' prognosis value in PCa.
Single-cell RNA-seq (scRNA-seq) data and mRNA expression data were obtained from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA). Quality control, normalization, reduction, clustering, and cell annotation of scRNA-seq data were preformed using the Seruat package. The sub-populations of the tumor-associated macrophages (TAMs) were analysis and the marker genes of M2 macrophage were selected. Differentially expressed genes (DEGs) in PCa were identified using limma and the immune infiltration was detected using CIBERSORTx. Then, a weighted correlation network analysis (WGCNA) was constructed to identify the M2 macrophage-related modules and genes. Integration of the marker genes of M2 macrophage from scRNA-seq data analysis and hub genes from WGCNA to select the prognostic gene signature based on Univariate and LASSO regression analysis. The risk score was calculated, and the DEGs, biological function, immune characteristics related to risk score were explored. And a predictive nomogram was constructed. CCK8, Transwell, and wound healing were used to verify cell phenotype changes after co-cultured.
A total of 2431 marker genes of M2 macrophage and 650 hub M2 macrophage-related genes were selected based on scRNA-seq data and WGCNA. Then, 113 M2 macrophage-related genes were obtained by overlapping the scRNA-seq data and WGCNA results. Nine M2 macrophage-related genes (SMOC2, PLPP1, HES1, STMN1, GPR160, ABCG1, MAZ, MYC, and EPCAM) were screened as prognostic gene signatures. M2 risk score was calculated, the DEGs, Immune score, stromal score, ESTIMATE score, tumor purity, and immune cell infiltration, immune checkpoint expression, and responses of immunotherapy and chemotherapy were identified. And a predictive nomogram was constructed. CCK8, Transwell invasion, and wound healing further verified that M2 macrophages promoted the proliferation, invasion, and migration of PCa ( < 0.05).
We uncovered that M2 macrophages and relevant genes played key roles in promoting the occurrence, development, and metastases of PCa and played as convincing predictors in PCa.
前列腺癌（PCa）已成为全球男性中发病率最高的恶性肿瘤。肿瘤微环境（TME）是肿瘤生长所必需的。M2 巨噬细胞在许多实体瘤中发挥重要作用。本研究旨在探讨 M2 巨噬细胞预后价值在 PCa 中的作用。
从基因表达综合数据库（GEO）和癌症基因组图谱（TCGA）中获取单细胞 RNA 测序（scRNA-seq）数据和 mRNA 表达数据。使用 Seruat 包对 scRNA-seq 数据进行质量控制、归一化、降维、聚类和细胞注释。分析肿瘤相关巨噬细胞（TAMs）的亚群，选择 M2 巨噬细胞的标记基因。使用 limma 识别 PCa 中的差异表达基因（DEGs），并使用 CIBERSORTx 检测免疫浸润。然后，构建加权相关网络分析（WGCNA）以识别 M2 巨噬细胞相关模块和基因。整合 scRNA-seq 数据分析中的 M2 巨噬细胞标记基因和 WGCNA 中的枢纽基因，基于单变量和 LASSO 回归分析选择预后基因特征。计算风险评分，探索与风险评分相关的 DEGs、生物学功能和免疫特征。并构建预测列线图。使用 CCK8、Transwell 和划痕愈合实验来验证共培养后细胞表型的变化。
基于 scRNA-seq 数据和 WGCNA 共筛选出 2431 个 M2 巨噬细胞标记基因和 650 个枢纽 M2 巨噬细胞相关基因，然后重叠 scRNA-seq 数据和 WGCNA 结果共获得 113 个 M2 巨噬细胞相关基因。筛选出 9 个 M2 巨噬细胞相关基因（SMOC2、PLPP1、HES1、STMN1、GPR160、ABCG1、MAZ、MYC 和 EPCAM）作为预后基因特征。计算 M2 风险评分，识别 DEGs、免疫评分、基质评分、ESTIMATE 评分、肿瘤纯度、免疫细胞浸润、免疫检查点表达以及免疫治疗和化疗的反应。并构建预测列线图。CCK8、Transwell 侵袭和划痕愈合实验进一步验证了 M2 巨噬细胞促进了 PCa 的增殖、侵袭和迁移（<0.05）。
本研究揭示了 M2 巨噬细胞和相关基因在促进 PCa 的发生、发展和转移中发挥关键作用，并作为 PCa 中令人信服的预测因子。
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