Construction of a prognostic model based on genome-wide methylation analysis of miRNAs for hepatocellular carcinoma

Abstract

Aim: Using the methylation level of miRNA genes to develop a prognostic model for patients with hepatocellular carcinoma (HCC). Materials & methods: least absolute shrinkage and selection operator and multivariate Cox regression analyses were performed to develop a prognostic model. One miRNA in the model was selected for verification. Results: A prognostic model was developed using eight miRNAs. The areas under the curve for predicting overall survival at 1, 3 and 5 years were 0.75, 0.81 and 0.81. miR-223 was found to be hypomethylated in 160 HCC tissues, and its methylation level was associated with Barcelona Clinic Liver Cancer stages and the prognosis of patients with HCC. Conclusion: The prognostic model based on miRNA methylation levels has the capability to partially forecast the prognosis of patients with HCC.

Tweetable abstract

Our research has formulated a prognostic model using the methylation levels of eight miRNA genes for partially forecasting the overall survival rate of patients with hepatocellular carcinoma.

Summary points

• The research on the methylation status of miRNA genes in hepatocellular carcinoma (HCC) has mainly focused on individual miRNA genes.

• This study specifically aimed to conduct a comprehensive analysis of methylation across the genome of miRNA genes in patients with HCC.

• The study observed that the promoter region of miRNA genes in HCC typically shows increased methylation, whereas other regions exhibit decreased methylation.

• Additionally, the research found that the methylation levels of multiple miRNA genes were correlated with the prognosis of patients with HCC.

• A prognostic model was developed using the methylation levels of miRNA genes, which partially predicted the prognosis of patients with HCC.

• Furthermore, nomograms were created based on the methylation levels of miRNA genes and tumor stages, proving to be effective in predicting the survival rate of patients with HCC.

• Notably, one miRNA in the model, miR-223, was found to be hypomethylated in HCC tissues compared with adjacent nontumor tissues. The methylation level of the miR-223 gene promoter region was also associated with Barcelona Clinic Liver Cancer stages and prognosis of patients with HCC.

Keywords: :

• hepatocellular carcinoma
• methylation
• miR-223
• miRNA
• prognostic model

Author contributions

D Zhou and H Lin conceived and designed the analysis. D Li, X Fan and L He collected the data. Z Shi and X Liu performed the bioinformatics analysis, conduct the molecular biology experiments and wrote the paper. All authors read and approved the final manuscript.

Financial disclosure

This work was supported by the National Natural Science Foundation of China (82102105) and the National Science Foundation of Zhejiang Province (LQ22H160017).

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

This study was conducted in strict compliance with the Declaration of Helsinki (as revised in 2013) and was approved by the Clinical Research Ethics Boards of the Shanghai Eastern Hepatobiliary Surgery Hospital and Ethics Committee of Sir Run Run Shaw Hospital. Informed consent was obtained from all included patients.

Data sharing statement

The in-house dataset used during this study is available from the corresponding author on reasonable request. The online datasets are from The Cancer Genome Atlas database (https://xenabrowser.net/datapages/?dataset=TCGA-LIHC.methylation450.tsv&host=https%3A%2F%2Fgdc.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443) and the GEO database (GSE77269) (www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE77269).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (82102105) and the National Science Foundation of Zhejiang Province (LQ22H160017).