失巢凋亡抵抗是肿瘤侵袭和转移的主要原因之一。前列腺癌（PCa）的生化复发（BCR）是其远处转移的先兆。然而，失巢凋亡在PCa生化复发中的作用尚未完全阐明。基于TCGA和GeneCards数据库，采用差异表达分析来鉴定失巢凋亡相关基因。利用 LASSO 回归、单变量和多变量 Cox 回归分析构建预后模型。此外，基因表达综合数据集（GSE70770 和 GSE46602）被用作验证队列。利用Gene Ontology、KEGG和GSVA探索生物学途径和分子机制。此外，使用 CIBERSORT、ssGSEA 和 TIDE 评估免疫特征，同时通过 GDSC 数据库分析抗癌药物敏感性。此外，使用在线数据库（人类蛋白质图谱和肿瘤免疫单细胞中心）检查了模型中的基因表达。发现了113个差异表达的失巢凋亡相关基因。选择四个基因（EEF1A2、RET、FOSL1、PCA3）用于构建预后模型。利用 Cox 回归分析的结果，我们将患者分为高风险组和低风险组。高危组预后较差，最大AUC为0.897。此外，高危组中记忆B细胞、CD8 T细胞、中性粒细胞和M1巨噬细胞的免疫浸润比例高于低危组，而高危组中活化的肥大细胞和树突状细胞的比例较高。 - 风险组较低。高危组的 TIDE 评分增加，表明 ICI 治疗的有效性降低。此外，化疗药物的IC50结果表明，低风险组对大多数药物更敏感。最后，根据HPA网站，基因EEF1A2、RET和FOSL1在PCa病例中表达。 TISCH数据库表明这四种ARG可能有助于PCa的肿瘤微环境。我们利用四种ARG创建了一个风险模型，可以有效预测PCa患者的BCR风险。这项研究为 BCR 前列腺癌患者的风险分层和预测生存结果奠定了基础。版权所有 © 2024 Kang、Ye、Yang、Lou、Zhao、Wang 和 Gau。

One of the primary reasons for tumor invasion and metastasis is anoikis resistance. Biochemical recurrence (BCR) of prostate cancer (PCa) serves as a harbinger of its distant metastasis. However, the role of anoikis in PCa biochemical recurrence has not been fully elucidated.Differential expression analysis was used to identify anoikis-related genes based on the TCGA and GeneCards databases. Prognostic models were constructed utilizing LASSO regression, univariate and multivariate Cox regression analyses. Moreover, Gene Expression Omnibus datasets (GSE70770 and GSE46602) were applied as validation cohorts. Gene Ontology, KEGG and GSVA were utilized to explore biological pathways and molecular mechanisms. Further, immune profiles were assessed using CIBERSORT, ssGSEA, and TIDE, while anti-cancer drugs sensitivity was analyzed by GDSC database. In addition, gene expressions in the model were examined using online databases (Human Protein Atlas and Tumor Immune Single-Cell Hub).113 differentially expressed anoikis-related genes were found. Four genes (EEF1A2, RET, FOSL1, PCA3) were selected for constructing a prognostic model. Using the findings from the Cox regression analysis, we grouped patients into groups of high and low risk. The high-risk group exhibited a poorer prognosis, with a maximum AUC of 0.897. Moreover, larger percentage of immune infiltration of memory B cells, CD8 Tcells, neutrophils, and M1 macrophages were observed in the high-risk group than those in the low-risk group, whereas the percentage of activated mast cells and dendritic cells in the high-risk group were lower. An increased TIDE score was founded in the high-risk group, suggesting reduced effectiveness of ICI therapy. Additionally, the IC50 results for chemotherapy drugs indicated that the low-risk group was more sensitive to most of the drugs. Finally, the genes EEF1A2, RET, and FOSL1 were expressed in PCa cases based on HPA website. The TISCH database suggested that these four ARGs might contribute to the tumor microenvironment of PCa.We created a risk model utilizing four ARGs that effectively predicts the risk of BCR in PCa patients. This study lays the groundwork for risk stratification and predicting survival outcomes in PCa patients with BCR.Copyright © 2024 Kang, Ye, Yang, Lou, Zhao, Wang and Gao.