Integrative Analysis of Genes Associated With Cancer Stem Cell Characteristics via Stemness Indices Combined With Multi-Omics Data in Liver Cancer

Zhang J, Yu B, Chu H, Hu B, Chen L, Yang W, Zhang R, Zhao W.
Preprint from
Research Square
20 November 2020


Liver cancer (LC) is one of the most prevalent malignancies with a high morbidity and mortality. Cancer stem cells (CSCs) are capable of tumorigenicity, self-renewal and long-term survival. However, the relationship between LC and CSCs remains unclear.MethodsThe clinical data of LC patients and multi-omics data including mRNA-seq, lncRNA-seq, miRNA-seq, mRNA expression-based stemness index (mRNAsi), alternative splicing, DNA methylation and copy number variation (CNV) were obtained from The Cancer Genome Atlas (TCGA). Besides, the clinical data and RNA-seq of validation group were obtained from International Cancer Genome Consortium (ICGC). Integrative analysis of genes associated with CSCs characteristics were performed by stemness indices combined with multi-omics data in LC.ResultsThe stemness degree of cells in liver tumor group was higher than that of the normal group. The patients with high stemness degree of tumor tissue had significantly poorer overall survival. Besides, 6 methylation-driven genes and 4 CNV-driven genes related to CSCs characteristics were obtained. Alternative splicing factor regulatory network and ceRNA regulatory network were constructed respectively. Furthermore, the mRNAsi score of LC was negatively correlated with the tumor immune score. The proportion of CD8 T cell, activated memory CD4 T cell, follicular helper T cell and M1 macrophages was up-regulated in tumors with a higher degree of stemness. Finally, a prediction model was established, which has been proved to be a good predictor of prognosis by ICGC data.ConclusionsCancer cells with high degree of stemness aggravated the malignant progression of LC, which may be related to low immune infiltration. The proposed prediction model was a powerful predictor for patients and helpful to clinical work.