Identification of Biomarkers Associated with Hepatocellular Carcinoma Stem Cell Characteristics Based on Co-Expression Network Analysis of Transcriptome Data and Stemness Index.

Mounting evidence has revealed the key role of cancer stem cells in hepatocellular carcinoma (HCC) metastasis and therapy resistance, yet the genes maintaining HCC stem cell features remain to be explored. This study aimed to identify and validate the key biomarkers associated with HCC stemness. mRNA expression-based stemness index (mRNAsi) was calculating using one-class logistic regression algorithm. RNA-sequencing data and clinical information of HCC samples were downloaded from the cancer genome atlas (TCGA) and merged with the corresponding mRNAsi. We investigated the correlation between mRNAsi and HCC clinical characteristics, including tumor grades, pathologic stages, vascular invasion, and survival outcomes. Significant genes associated HCC stemness features were screened through weighted gene co-expression network analysis (WGCNA) and were functionally annotated using enrichment analysis. Protein-protein interaction network was constructed among significant genes and the key biomarkers were finally identified based on the maximal clique centrality (MCC) method. The expression of key biomarkers and its correlation with HCC clinical outcomes were validated using oncomine and gene expression omnibus (GEO) database. mR-NAsi was significantly higher in HCC tissues and gradually increased according to tumor grades and pathologic stages. Patients with vascular invasion or poor survival exhibited higher mRNAsi. Forty-four highly-correlated significant gens were screened through WGCNA and functionally related to cell cycle, cellular senescence, p53 signaling pathway, DNA replication, and mismatch repair. Four different GEO datasets confirmed that the expression levels of these 44 genes were notably higher in HCC tissues. We finally identified 15 key biomarkers (KIF4A, TTK, CCNB1, CDC20, NCAPG, CCNB2, CDC45, UBE2C, CENPA, AURKB, RRM2, CDCA8, BIRC5, TPX2, and KIF2C) through MCC method. The expression of these biomarkers was up-regulated in multiple types of cancers and showed a gradually increasing trend with HCC tumor grades. Furthermore, high expression levels of these biomarkers were also correlated with HCC metastasis, recurrence, sorafenib resistance, and poor overall survival. We identified 15 key biomarkers associated with HCC stemness features and these genes might serve as promising therapeutic targets for HCC.

Prognostic value of myosteatosis in patients with lung cancer: a systematic review and meta-analysis.

The prognostic value of myosteatosis has been widely investigated in lung cancer, yet conclusions remain controversial. The purpose of this meta-analysis was to illuminate this issue. Medline, Embase, Cochrane Library and Web of Science Core Collection online databases were systematically searched from inception to 24 September 2021. Newcastle-Ottawa Scale tool was applied to evaluate the quality of included studies. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) and progression-free survival (PFS) were used to examine prognostic value of myosteatosis. Subgroup analysis and sensitivity analysis were conducted to assess heterogeneity and stability of results. A total of 484 articles were screened from which 9 eligible studies involving 1667 patients were enrolled in this meta-analysis. Lung cancer patients with myosteatosis had significantly worse OS than patients without myosteatosis (HR 1.10, 95% CI 1.05-1.16, P < 0.001), both in six multivariate analysis (HR 1.46, 95% CI 1.16-1.85, P = 0.001) and in three univariate analysis (HR 1.08, 95% CI 1.03-1.14, P = 0.003). Pooled data from five studies using multivariate survival analysis also showed that patients with myosteatosis had a statistically significant unfavorable PFS (HR = 1.27, 95% CI 1.00-1.62, P = 0.049). Sensitivity analysis showed the result for OS was stable. But for PFS, the result was not robust. Myosteatosis might serve as an independent indicator of unfavorable survival outcomes for OS and PFS in lung cancer patients. Further studies are needed to confirm our results.