Weighted gene co-expression network analysis reveals prognostic and diagnostic significance of PAQR4 in patients with early and late hepatocellular carcinoma

Tianhang Feng; Chunyou Lai; Deyuan Zhong; Le Luo; Haibo Zou; Guan Wang; Qinyan Yang; Yutong Yao; Xiaolun Huang

doi:10.21037/jgo-22-168

Weighted gene co-expression network analysis reveals prognostic and diagnostic significance of PAQR4 in patients with early and late hepatocellular carcinoma

J Gastrointest Oncol. 2022 Apr;13(2):768-779. doi: 10.21037/jgo-22-168.

Authors

Tianhang Feng^#¹, Chunyou Lai^#¹, Deyuan Zhong^#¹, Le Luo¹, Haibo Zou¹, Guan Wang¹, Qinyan Yang¹, Yutong Yao¹, Xiaolun Huang¹

Affiliation

¹ Department of Hepatobiliary and Pancreatic Surgery, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.

^# Contributed equally.

Abstract

Background: This study aimed to reveal novel markers for prognostic and diagnostic prediction of hepatocellular carcinoma (HCC).

Methods: We applied The Cancer Genome Atlas (TCGA) data to screen differentially expressed genes (DEGs). We identified hub modules and genes using weighted gene co-expression network analysis (WGCNA). After verification with the GSE36376 dataset, hub genes were further identified. The expression of progestin and adipoQ receptor 4 (PAQR4) was confirmed in HCC by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The diagnostic and prognosis value of PAQR4 was assessed. The expression of PAQR4 was verified using the GSE76427 dataset.

Results: A total of 803 DEGs were obtained between HCC and normal tissue. Through WGCNA, 7 hub modules were screened, among which the blue module was selected to identify the hub genes associated with the HCC. After overlapping all the DEGs with 837 genes of the blue module, we obtained 466 DEGs that were defined as hub genes. Among the hub genes, 239 were related to staging. After verifying with the GSE36376 dataset, PAQR4 was identified as the real hub gene of HCC. The results of qRT-PCR revealed that PAQR4 was upregulated between HCC and normal tissue. Furthermore, PAQR4 was related to the diagnosis and prognosis of patients with HCC. Moreover, the GSE76427 verification results of PAQR4 were consistent with our integration and qRT-PCR results. Ultimately, high expression of PAQR4 was significantly related to cell cycle, DNA replication, and the p53 signaling pathway.

Conclusions: The PAQR4 gene may be associated with the prognosis and diagnosis of HCC.

Keywords: Gene Expression Omnibus (GEO) dataset; Hepatocellular carcinoma (HCC); PAQR4; The Cancer Genome Atlas (TCGA); weighted gene co-expression network analysis (WGCNA).