RPL19 Is a Prognostic Biomarker and Promotes Tumor Progression in Hepatocellular Carcinoma

Benchen Rao; Jianhao Li; Tong Ren; Jing Yang; Guizhen Zhang; Liwen Liu; Haiyu Wang; Maoxin Huang; Zhigang Ren; Zujiang Yu

doi:10.3389/fcell.2021.686547

RPL19 Is a Prognostic Biomarker and Promotes Tumor Progression in Hepatocellular Carcinoma

Front Cell Dev Biol. 2021 Jul 19:9:686547. doi: 10.3389/fcell.2021.686547. eCollection 2021.

Authors

Benchen Rao^{1

2}, Jianhao Li^{1

2}, Tong Ren³, Jing Yang⁴, Guizhen Zhang^{1

2}, Liwen Liu^{1

2}, Haiyu Wang^{1

2}, Maoxin Huang⁵, Zhigang Ren^{1

2}, Zujiang Yu^{1

2}

Affiliations

¹ Department of Infectious Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
² Precision Medicine Center, Gene Hospital of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
³ Department of Breast Surgery, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
⁴ Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
⁵ Department of Dermatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Abstract

Background: Hepatocellular carcinoma (HCC) is one of the most common malignancies, and the therapeutic outcome remains undesirable due to its recurrence and metastasis. Gene dysregulation plays a pivotal role in the occurrence and progression of cancer, and the molecular mechanisms are largely unknown.

Methods: The differentially expressed genes of HCC screened from the GSE39791 dataset were used to conduct weighted gene co-expression network analysis. The selected hub genes were validated in The Cancer Genome Atlas (TCGA) database and 11 HCC datasets from the Gene Expression Omnibus (GEO) database. Then, a tissue microarray comprising 90 HCC specimens and 90 adjacent normal specimens was used to validate the hub genes. Moreover, the Hallmark, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to identify enriched pathways. Then, we conducted the immune infiltration analysis.

Results: A total of 17 co-expression modules were obtained by weighted gene co-expression network analysis. The green, blue, and purple modules were the most relevant to HCC samples. Four hub genes, RPL19, RPL35A, RPL27A, and RPS12, were identified. Interestingly, we found that all four genes were highly expressed in HCC and that their high expression was related to a poor prognosis by analyzing the TCGA and GEO databases. Furthermore, we investigated RPL19 in HCC tissue microarrays and demonstrated that RPL19 was overexpressed in tumor tissues compared with non-tumor tissues (p = 0.016). Moreover, overexpression of RPL19 predicted a poor prognosis in hepatocellular carcinoma (p < 0.0007). Then, enrichment analysis revealed that cell cycle pathways were significantly enriched, and bile acid metabolism-related pathways were significantly down-regulated when RPL19 was highly expressed. Furthermore, immune infiltration analysis showed that immune response was suppressed.

Conclusion: Our study demonstrates that RPL19 may play an important role in promoting tumor progression and is correlated with a poor prognosis in HCC. RPL19 may serve as a promising biomarker and therapeutic target for the precise diagnosis and treatment of HCC in the future.

Keywords: hepatocellular carcinoma; immune infiltration; prognostic biomarker; ribosomal protein L19; weighted gene co-expression network analysis.