在肿瘤微环境中，肿瘤相关巨噬细胞（TAMs）与癌细胞相互作用，并促进实体肿瘤的进展。然而，TAM相关的生物标志物在前列腺癌（PCa）中的临床意义尚未得到充分探索。本研究旨在基于巨噬细胞标记物基因构建与预测PCa患者预后相关的巨噬细胞相关签名（MRS）。纳入了1056名带有RNA-Seq和随访数据的PCa患者组成的六个队列。基于单细胞RNA测序（scRNA-seq）分析确定巨噬细胞标记物基因，并应用单变量分析，最小绝对收缩选择算子（Lasso）-Cox回归和机器学习方法进行连续一致的MRS推导。采用受试者工作特征曲线（ROC）、一致性指数和决策曲线分析确认MRS的预测能力。MRS预测反复无效生存（RFS）的表现稳定而强大，超过传统临床变量。此外，高MRS分数的患者表现出丰富的巨噬细胞浸润和免疫检查点（CTLA4、HAVCR2和CD86）的高表达水平。在高MRS分数亚组中，突变频率相对较高。然而，低MRS分数的患者对免疫检查点阻滞（ICB）和去势剂辅助化疗的反应更好。值得注意的是，ATF3异常表达可能与PCa细胞中的紫杉醇和卡巴地新耐药性、T分期和格里森评分有关。本研究首次开发和验证了一种新型MRS，以准确预测患者生存结果，评估免疫特征，推断治疗效益，并为个体化治疗提供辅助工具。©2023年。作者（们）在Springer-Verlag GmbH Germany（Springer Nature的一部分）独家许可下发表。

In the tumor microenvironment, tumor-associated macrophages (TAMs) interact with cancer cells and contribute to the progression of solid tumors. Nonetheless, the clinical significance of TAM-related biomarkers in prostate cancer (PCa) is largely unexplored. The present study aimed to construct a macrophage-related signature (MRS) for predicting PCa patient prognosis based on macrophage marker genes. Six cohorts comprising 1056 PCa patients with RNA-Seq and follow-up data were enrolled. Based on macrophage marker genes identified by single-cell RNA-sequencing (scRNA-seq) analysis, univariate analysis, least absolute shrinkage and selection operator (Lasso)-Cox regression, and machine learning procedures were performed to derive a consensus MRS. Receiver operating characteristic curve (ROC), concordance index, and decision curve analyses were used to confirm the predictive capacity of the MRS. The predictive performance of the MRS for recurrence-free survival (RFS) was stable and robust, and the MRS outperformed traditional clinical variables. Furthermore, high-MRS-score patients presented abundant macrophage infiltration and high-expression levels of immune checkpoints (CTLA4, HAVCR2, and CD86). The frequency of mutations was relatively high in the high-MRS-score subgroup. However, the low-MRS-score patients had a better response to immune checkpoint blockade (ICB) and leuprolide-based adjuvant chemotherapy. Notably, abnormal ATF3 expression may be associated with docetaxel and cabazitaxel resistance in PCa cells, T stage, and the Gleason score. In this study, a novel MRS was first developed and validated to accurately predict patient survival outcomes, evaluate immune characteristics, infer therapeutic benefits, and provide an auxiliary tool for personalized therapy.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.