The identification of N6-methyladenosine-related miRNAs predictive of hepatocellular carcinoma prognosis and immunotherapy efficacy

Author:

Zou Renrui12,Liu Yaqian2,Qiu Sangsang3,Lu Ya1,Chen Yan1,Yu Hui1,Zhu Hangju1,Zhu Wenbo1,Zhu Longbiao4,Feng Jifeng1,Han Jing1

Affiliation:

1. Jiangsu Cancer Centre, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, Jiangsu, China

2. Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China

3. The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Jiangsu, China

4. Department of The Sixth Dental Division, The Affiliated Stomatological Hospital of Nanjing Medical University, Jiangsu Province Key Laboratory of Oral Diseases, Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Jiangsu, China

Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) has a high degree of malignancy and poor prognosis. N6-methyladenosine (m6A) modifications and microRNAs (miRNAs) play pivotal roles in tumorigenesis and development. However, the role of m6A-related miRNAs in HCC has not been clarified yet. This study aimed to identify the role of m6A-miRNAs in HCC prognosis through bioinformatics analysis. METHODS: The clinicopathological information and RNA sequencing data of 369 HCC tumor tissues and 49 tumor-adjacent tissues were downloaded from the TCGA database. A total of 23 m6A regulators were extracted to evaluated the m6A-related miRNAs using Pearson’s correlation analysis. Then, we selected prognosis-related m6A-miRNAs using a univariate Cox regression model and used the consensus cluster analysis to explore the characteristics of the m6A-miRNAs. The coefficient of the least absolute shrinkage and selection operator (LASSO) Cox regression was applied to construct a prognostic risk score model. The receiver operated characteristic (ROC) analysis was applied to evaluate the prognostic value of the signature. The biological functions of targeted genes were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Then, to validate the potential predictive value for prognosis, the miRNA expression profiles from the GSE76903 and GSE6857 were used. Single sample Gene Set Enrichment Analysis (ssGSEA) and Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) were applied to assess the immune microenvironment of HCC. Additionally, a meta-analysis was used to verify the prognostic value of the m6A-microRNAs. RT-PCR was applied to validated the expression of miRNAs in HCC tissues. Cell viability, transwell assay and RNA m6A dot blot assays of HCC cells was applied to access the function of miR-17-5p. RESULTS: The expression of 48 m6A-related miRNAs was identified and 17 prognostic m6A-miRNAs was discovered. The expression profile of those 17 miRNAs was divided into three clusters, and these clusters were associated with the tumor microenvironment (TME) and prognosis. The nine m6A-related miRNA signature was associated with the prognosis of HCC, the AUC of the ROC was 0.771(TCGA dataset), 0.788(GSE76903) and 0.646(GSE6857). The TME and the expression of immune checkpoint molecules were associated with the risk score. The meta-analysis also validated the prognostic value of the m6A-related miRNAs (miR182-5p (HR:1.58, 95%CI:1.04-2.40) and miR-17-5p (HR:1.58, 95%CI: 1.04–2.40)). The expression of miR-17-5p was upregulated in HCC tissues and miR-17-5p showed an oncogenic role in HCC cells. CONCLUSION: The clinical innovation is the use of m6A-miRNAs as biomarkers for predicting prognosis regarding immunotherapy response in HCC patients.

Publisher

IOS Press

Subject

Cancer Research,Genetics,Oncology,General Medicine

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