Implications of Stemness Features in 1059 Hepatocellular Carcinoma Patients from Five Cohorts: Prognosis, Treatment Response, and Identification of Potential Compounds

Abstract

Cancer stemness has been reported to drive hepatocellular carcinoma (HCC) tumorigenesis and treatment resistance. In this study, five HCC cohorts with 1059 patients were collected to calculate transcriptional stemness indexes (mRNAsi) by the one-class logistic regression machine learning algorithm. In the TCGA-LIHC cohort, we found mRNAsi was an independent prognostic factor, and 626 mRNAsi-related genes were identified by Spearman correlation analysis. The HCC stemness risk model (HSRM) was trained in the TCGA-LIHC cohort and significantly discriminated overall survival in four independent cohorts. HSRM was also significantly associated with transarterial chemoembolization treatment response and rapid tumor growth in HCC patients. Consensus clustering was conducted based on mRNAsi-related genes to divide 1059 patients into two stemness subtypes. On gene set variation analysis, samples of subtype I were found enriched with pathways such as DNA replication and cell cycle, while several liver-specific metabolic pathways were inhibited in these samples. Somatic mutation analysis revealed more frequent mutations of TP53 and RB1 in the subtype I samples. In silico analysis suggested topoisomerase, cyclin-dependent kinase, and histone deacetylase as potential targets to inhibit HCC stemness. In vitro assay showed two predicted compounds, Aminopurvalanol-a and NCH-51, effectively suppressed oncosphere formation and impaired viability of HCC cell lines, which may shed new light on HCC treatment.

Cell Pair Algorithm-Based Immune Infiltrating Cell Signature for Improving Outcomes and Treatment Responses in Patients with Hepatocellular Carcinoma

“…A study by Mai et al proved that HCCs with higher mRNAsi scores had significantly worse overall survival based on an HCC matrix of more than 1000 HCC patients [52]. In this paper, we concluded the ICRPI was positively associated with mRNAsi, acting as a risk factor for the survival of HCC patients, which was consistent with Mai et al [53]. HRD had been used as a biomarker for therapy decision making [54].…”

Development and Optimization of a Prognostic Model Associated with Stemness Genes in Hepatocellular Carcinoma

“…The main characteristics of tumor stemness are the strong self-renewal ability and increased tumor heterogeneity [ 3 – 4 ]. Many studies have shown that tumor stemness plays an important role in tumor metastasis, differentiation, and drug resistance [ 9 , 10 ]. For example, USP22 was reported to promote the stemness of HCC cells by HIF1a pathways [ 11 ].…”

Integrated analysis revealing a novel stemness-metabolism-related gene signature for predicting prognosis and immunotherapy response in hepatocellular carcinoma

“…Mai et al. developed an HCC stemness risk model as a potential indicator of TACE treatment response ( 17 ). Zhang et al.…”

“…Despite being small in number, CSCs are easily spread to distant organs, leading to HCC progression, recurrence ( 11 ) and metastasis ( 12 ). They are also implicated in therapy resistance, including sorafenib resistance ( 13 – 16 ), TACE refractoriness ( 17 ) and immunotherapy resistance ( 18 ). Moreover, CSCs could enhance immune evasion and induce an immunosuppressive microenvironment via the up-regulation of inhibitory molecules and the low expression of stimulatory molecules ( 19 ).…”