Identification of cancer stem cell characteristics in liver hepatocellular carcinoma by WGCNA analysis of transcriptome stemness index.

Abstract

Cancer stem cells (CSCs) are characterized by self-renewal and -differential potential as compared to common cancer cells and play an important role in the development and therapeutic resistance of liver hepatocellular carcinoma (LIHC). However, the specific pathogenesis of LIHC stem cells is still unclear, and the genes involved in the stemness of LIHC stem cells are currently unknown. In this study, we investigated novel biomarkers associated with LIHC and explored the expression characteristics of stem cell-related genes in LIHC. We found that mRNA expression-based stemness index (mRNAsi) was significantly overexpressed in liver cancer tissues. Further, mRNAsi expression in LIHC increased with the tumor pathological grade, with grade 4 tumors harboring the greatest stem cell features. Upon establishing mRNAsi scores based on mRNA expression of every gene, we found an association with poor overall survival in LIHC. Moreover, modules of interest were determined based on weighted gene co-expression network analysis (WGCNA) inclusion criteria, and three significant modules (red, green, and brown) and 21 key genes (DCN, ECM1, HAND2, PTGIS, SFRP1, SRPX, COLEC10, GRP182, ADAMTS7, CD200, CDH11, COL8A1, FAP, LZTS1, MAP1B, NAV1, NOTCH3, OLFML2A, PRR16, TMEM119, and VCAN) were identified. Functional analysis of these 21 genes demonstrated their enrichment in pathways involved in angiogenesis, negative regulation of DNA-binding transcription factor activity, apoptosis, and autophagy. Causal relationship with proteins indicated that the Wnt, Notch, and Hypoxia pathways are closely related to LIHC tumorigenesis. To our knowledge, this is the first report of a novel CSC biomarker, mRNAsi, to predict the prognosis of LIHC. Further, we identified 21 key genes through mRNA expression network analysis, which could be potential therapeutic targets to inhibit the stemness of cancer cells in LIHC.

• Authors: Kun-Hao Bai, Si-Yuan He, Ling-Ling Shu, Wei-Da Wang, Shi-Yong Lin, Qian-Yi Zhang, Liang Li, Lei Cheng, Yu-Jun Dai
• Journal: Cancer medicine (Cancer Med) Vol. 9 Issue 12 Pg. 4290-4298 (06 2020) ISSN: 2045-7634 [Electronic] United States
• PMID: 32311840 (Publication Type: Journal Article)
• Copyright: © 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Chemical References

• Biomarkers, Tumor

Topics

• Biomarkers, Tumor (genetics, metabolism)
• Carcinoma, Hepatocellular (genetics, metabolism, pathology)
• Gene Expression Profiling
• Gene Expression Regulation, Neoplastic
• Gene Regulatory Networks
• Humans
• Liver Neoplasms (genetics, metabolism, pathology)
• Neoplastic Stem Cells (metabolism, pathology)
• Transcriptome