AUTHOR=Liu Yu , Li Rongkuan , Wang Xiaobo , Xue Zuguang , Yang Xiaozhou , Tang Bo 

TITLE=Comprehensive Analyses of MELK-Associated ceRNA Networks Reveal a Potential Biomarker for Predicting Poor Prognosis and Immunotherapy Efficacy in Hepatocellular Carcinoma

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.824938

DOI=10.3389/fcell.2022.824938

ISSN=2296-634X

ABSTRACT=Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world with high morbidity and mortality. Identifying specific molecular markers that can predict HCC prognosis is extremely important. MELK have been reported to play key roles in several types of human cancer and predict poor prognosis. This study aimed to explore the impact of MELK on HCC. 
Methods: A pan-cancer analysis of MELK was conducted by the The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) data. The prognosis of MELK in the various cancers was analyzed in the GEPIA. Then a ceRNA network of MELK was constructed based on the comprehensive consideration of the expression analysis, the correlation analysis and the survival analysis by the R software. The correlation of MELK and immune cell infiltration as analyzed by TIMER and CIBERSORT. Then the overall survival of differentially expressed immune cells was conducted. The correlation of MELK and immune checkpoints expression was analyzed by GEPIA.
Results: The MELK was overexpressed in 14 types of human cancers and its expression was significantly higher than that in both unmatched and paired normal samples in HCC. Higher MELK expression was correlated with poorer survival and advanced clinical stage, topography(T) stage and histological grade. We constructed a ceRNA network consisting of MELK, miR-101-3p and two lncRNAs (SNHG1 and SNHG6) after evaluating the expression and the impact on prognosis in HCC of RNAs. TIMER and CIBERSORT database indicated that MELK was correlated with various immune cells including the B cells, CD8+ T cells, CD4+ T cells, macrophage, neutrophil, and dendritic cells in HCC. Of them, B cells, CD4+ T cells, macrophage and neutrophil were related to the prognosis of HCC. In addition, the MELK was significantly positively correlated with the immune checkpoint genes.
Conclusions: MELK may be a novel potential biomarker for predicting prognosis and immunotherapy efficacy in patients with HCC.