■肿瘤侵袭和转移的主要原因之一是抗肛门凋亡。前列腺癌(PCa)的生化复发(BCR)是其远处转移的先兆。然而,失稳在PCa生化复发中的作用尚未完全阐明.
■根据TCGA和GeneCards数据库,使用差异表达分析来鉴定与失巢凋亡相关的基因。利用LASSO回归构建预后模型,单变量和多变量Cox回归分析。此外,应用基因表达综合数据集(GSE70770和GSE46602)作为验证群组。基因本体论,KEGG和GSVA用于探索生物学途径和分子机制。Further,使用CIBERSORT评估免疫谱,ssGSEA,和潮汐,同时通过GDSC数据库分析抗癌药物的敏感性。此外,使用在线数据库(人蛋白质图谱和肿瘤免疫单细胞中心)检查模型中的基因表达。
■发现了113个差异表达的失巢凋亡相关基因。四个基因(EEF1A2,RET,选择FOSL1,PCA3)构建预后模型。利用Cox回归分析的结果,我们将患者分为高危组和低危组.高危人群预后较差,最大AUC为0.897。此外,记忆B细胞的免疫浸润百分比较大,CD8T细胞,中性粒细胞,和M1巨噬细胞在高危组比在低危组观察到,而高风险组中激活的肥大细胞和树突状细胞的百分比较低。在高危人群中发现了增加的TIDE评分,提示ICI治疗的有效性降低。此外,化疗药物的IC50结果表明,低危组对大多数药物更敏感.最后,EEF1A2,RET,根据HPA网站,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的PCa患者的风险分层和生存结局预测奠定了基础。
UNASSIGNED: 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.
UNASSIGNED: 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).
UNASSIGNED: 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.
UNASSIGNED: 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.