引言："无附属生长条件死亡"（Anoikis）是一种特定形式的程序性细胞死亡，与前列腺癌（PC）转移有关。本研究旨在开发一种可靠的与无附属生长条件相关的基因签名，以准确预测PC的预后。方法：基于无附属生长条件相关基因和癌症基因组图谱（TCGA）数据，鉴定出与无附属生长条件相关的分子亚型，并对其在无病生存（DFS）、干性、临床特征和免疫浸润模式上的差异进行比较。利用两个亚型的差异表达分析和加权基因共表达网络分析（WGCNA）来鉴定临床相关的无附属生长条件相关差异表达基因（DEGs），然后选择这些DEGs来构建预后签名。使用验证数据集GSE116918和GSE46602验证了该签名的临床效用。建立了一个判断患者生存的评分图。最后，发现不同风险组之间有不同富集的主要基因集。结果：鉴定出两种与无附属生长条件相关的分子亚型，集群1的预后较差，干性较高，临床特征较为先进，并且免疫细胞浸润存在差异。接下来，鉴定出了13个与无附属生长条件相关的临床相关DEGs，其中五个（CKS2，CDC20，FMOD，CD38和MSMB）被选择用于构建预后签名。该基因签名具有较高的预后价值。结合格利森分级、T分期和风险得分的评分图可以准确预测患者生存。此外，与DNA修复密切相关的基因集在不同风险组之间有差异表达。结论：一种新型、临床相关的五个与无附属生长条件相关的基因签名是PC的强有力的预后生物标志物。版权所有 © 2023 刘和王。

Introduction: Anoikis is a specific form of programmed cell death and is related to prostate cancer (PC) metastasis. This study aimed to develop a reliable anoikis-related gene signature to accurately forecast PC prognosis. Methods: Based on anoikis-related genes and The Cancer Genome Atlas (TCGA) data, anoikis-related molecular subtypes were identified, and their differences in disease-free survival (DFS), stemness, clinical features, and immune infiltration patterns were compared. Differential expression analysis of the two subtypes and weighted gene co-expression network analysis (WGCNA) were employed to identify clinically relevant anoikis-related differentially expressed genes (DEGs) between subtypes, which were then selected to construct a prognostic signature. The clinical utility of the signature was verified using the validation datasets GSE116918 and GSE46602. A nomogram was established to predict patient survival. Finally, differentially enriched hallmark gene sets were revealed between the different risk groups. Results: Two anoikis-related molecular subtypes were identified, and cluster 1 had poor prognosis, higher stemness, advanced clinical features, and differential immune cell infiltration. Next, 13 clinically relevant anoikis-related DEGs were identified, and five of them (CKS2, CDC20, FMOD, CD38, and MSMB) were selected to build a prognostic signature. This gene signature had a high prognostic value. A nomogram that combined Gleason score, T stage, and risk score could accurately predict patient survival. Furthermore, gene sets closely related with DNA repair were differentially expressed in the different risk groups. Conclusion: A novel, clinically relevant five-anoikis-related gene signature was a powerful prognostic biomarker for PC.Copyright © 2023 Liu and Wang.