Identification of recurrence marker associated with immune infiltration in prostate cancer with radical resection and build prognostic nomogram

识别与前列腺癌根治性切除术后免疫浸润相关的复发标志物并构建预后列线图

阅读:1

Abstract

BACKGROUND: Some historic breakthroughs have been made in immunotherapy of advanced cancer. However, there is still little research on immunotherapy in prostate cancer. We explored the relationship between immune cell infiltration and prostate cancer recurrence and tried to provide new ideas for the treatment of prostate cancer. METHODS: Prostate cancer RNA-seq data and clinical information were downloaded from the TCGA database and GEO database. The infiltration of 24 immune cells in tissues was quantified by ssGSEA. Univariate Cox regression analysis was used to screen for immune cell types associated with tumor recurrence, weighted gene co-expression network analysis (WGCNA) and LASSO were used to identify hub genes which regulate prognosis in patients through immune infiltration. Then, the nomogram was constructed based on the hub gene to predict the recurrence of prostate cancer, and the decision curve analysis (DCA) was used to compare the accuracy with the PSA and Gleason prediction models. RESULT: Analysis showed that Th2 cells and Tcm related to prostate cancer recurrence after radical prostatectomy, and they are independent protective factors for recurrence. Through WGCNA and Lasso, we identified that NDUFA13, UQCR11, and USP34 involved in the infiltration of Th2 cells and Tcm in tumor tissues, and the expression of genes is related to the recurrence of patients. Based on the above findings, we constructed a clinical prediction model and mapped a nomogram, which has better sensitivity and specificity for prostate cancer recurrence prediction, and performed better in comparison with PSA and Gleason's predictions. CONCLUSION: The immune cells Th2 cells and Tcm are associated with recurrence of PCa. Moreover, the genes NDUFA13, UQCR11, and USP34 may affect the recurrence of PCa by affecting the infiltration of Th2 cells and Tcm. Moreover, nomogram can make prediction effectively.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。