Research Paper Volume 13, Issue 12 pp 16024—16042

Identification of microenvironment related potential biomarkers of biochemical recurrence at 3 years after prostatectomy in prostate adenocarcinoma

Xiaoru Sun1,2, , Lu Wang1,2, , Hongkai Li1,2, , Chuandi Jin1,2, , Yuanyuan Yu1,2, , Lei Hou1,2, , Xinhui Liu1,2, , Yifan Yu1,2, , Ran Yan1,2, , Fuzhong Xue1,2, ,

  • 1 Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China
  • 2 Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China

Received: November 30, 2020       Accepted: May 11, 2021       Published: June 16, 2021      

https://doi.org/10.18632/aging.203121
How to Cite

Copyright: © 2021 Sun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Prostate adenocarcinoma is one of the leading adult malignancies. Identification of multiple causative biomarkers is necessary and helpful for determining the occurrence and prognosis of prostate adenocarcinoma. We aimed to identify the potential prognostic genes in the prostate adenocarcinoma microenvironment and to estimate the causal effects simultaneously. We obtained the gene expression data of prostate adenocarcinoma from TCGA project and identified the differentially expressed genes based on immune-stromal components. Among these genes, 68 were associated with biochemical recurrence at 3 years after prostatectomy in prostate adenocarcinoma. After adjusting for the minimal sets of confounding covariates, 14 genes (TNFRSF4, ZAP70, ERMN, CXCL5, SPINK6, SLC6A18, CHRM2, TG, CLLU1OS, POSTN, CTSG, NETO1, CEACAM7, and IGLV3-22) related to the microenvironment were identified as prognostic biomarkers using the targeted maximum likelihood estimation. Both the average and individual causal effects were obtained to measure the magnitude of the effect. CIBERSORT and gene set enrichment analyses showed that these prognostic genes were mainly associated with immune responses. POSTN and NETO1 were correlated with androgen receptor expression, a main driver of prostate adenocarcinoma progression. Finally, five genes were validated in another prostate adenocarcinoma cohort (GEO: GSE70770). These findings might lead to the improved prognosis of prostate adenocarcinoma.

Abbreviations

PRAD: prostate adenocarcinoma; TCGA: the Cancer Genome Atlas; GEO: Gene Expression Omnibus; GO: gene ontology; KEGG: the Kyoto Encyclopedia of Genes and Genomes; BCR: biochemical recurrence; TME: tumor microenvironment; DEG: differentially expressed gene; TMLE: targeted maximum likelihood estimation; AR: androgen receptor; FDR: false discovery rate.