Research Paper Volume 13, Issue 7 pp 9976—9990
Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis
- 1 Department of General Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
- 2 Department of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
- 3 Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
- 4 Central Lab, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
Received: August 8, 2020 Accepted: February 16, 2021 Published: March 26, 2021
https://doi.org/10.18632/aging.202754How to Cite
Copyright: © 2021 Chen 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
Pheochromocytoma and paraganglioma (PCPG) is a rare neuroendocrine tumor. This study aims to identify vital prognostic genes which were associated with PCPG tumor microenvironment (TME). We downloaded transcriptome data of PCPG from TCGA database and calculated the immune scores and stromal scores by using the ESTIMATE algorithm. DEGs related to TMB were then identified. We conducted WGCNA to further extract the TME-related modules. GO, KEGG pathway analysis, and PPI network were performed. Survival analysis was conducted to identify the hub genes associated with the prognosis of PCPG. A total of 150 PCPG samples were included in this study. We obtained 1507 and 2067 DEGs based on immune scores and stromal scores, respectively. WGCNA analysis identified the red module and brown module were correlated with immune sores while the turquoise module and red module were significantly associated with stromal scores. Functional enrichments analysis revealed that 307 TME-related genes were correlated with the inflammation or immune response. Survival analysis showed that three TME-relate genes (ADGRE1, CCL18, and LILRA6) were associated with PCPG prognosis. These three hub genes including ADGRE1, CCL18, and LILRA6 might be involved in the progression of PCPG and could serve as potential biomarkers and novel therapeutic targets.