Cancer Management and Research (Aug 2021)

Analysis of m6A-Related lncRNAs for Prognosis Value and Response to Immune Checkpoint Inhibitors Therapy in Hepatocellular Carcinoma

  • Wang Y,
  • Li N,
  • Tian D,
  • Zhou CW,
  • Wang YH,
  • Yang C,
  • Zeng MS

Journal volume & issue
Vol. Volume 13
pp. 6451 – 6471

Abstract

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Yi Wang,1,* Na Li,1,* Di Tian,1,* Chang-Wu Zhou,1 You-Hua Wang,2 Chun Yang,1 Meng-Su Zeng1 1Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, 200032, People’s Republic of China; 2Department of Orthopaedics, Affiliated Hospital of Nantong University, Nantong, Jiangsu, 226001, People’s Republic of China*These authors contributed equally to this workCorrespondence: Meng-Su Zeng; Chun YangDepartment of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Xuhui District, Shanghai, 200032, People’s Republic of ChinaTel +86 13501922963; Tel +86 18702135336Email [email protected]; [email protected]: N6-methyladenosine (m6A) modification and long non-coding RNAs (lncRNAs) play pivotal roles in the progression of hepatocellular carcinoma (HCC). However, how their interaction is involved in the prognostic value of HCC and immune checkpoint inhibitors (ICIs) therapy remains unclear.Methods: The RNA sequencing and clinical data of HCC patients were collected from TCGA database. The prognostic m6A-related lncRNAs were screened out with Pearson correlation test, univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. Patients with HCC were classified into 2 subtypes by consensus clustering. Survival analyses were performed to assess the prognostic value of different clusters and risk models. Potential tumor correlated biological pathways correlated with different clusters were explored through gene set enrichment analysis. We also identified the relationship of the risk model and clusters with response to immune checkpoint inhibitors (ICIs) therapy and tumor microenvironment (TME). Furthermore, the prognostic value of the 9 m6A-related lncRNAs was validated in the external cohort. Finally, the role of SNHG4 was explored by silencing and overexpression of SNHG4 through conducting proliferation, migration and invasion experiments.Results: Patients from 2 clusters and different risk groups based on m6A-related lncRNAs had significantly different clinicopathological characteristics and overall survival outcomes. Tumor-correlated biological pathways were found to be correlated with Cluster 2 through GSEA. Moreover, we found that patients from different clusters and risk groups expressed higher levels of immune checkpoint genes and had distinct TME and different responses for ICIs therapy. Prognostic value of this risk model was further confirmed in the external cohort. Finally, consistent with the discovery, SNHG4 played an oncogenic role in vitro.Conclusion: Our study demonstrated that the 9 m6A-related lncRNA signature may serve as a novel predictor in the prognosis of HCC and optimize (ICIs) therapy. SNHG4 plays an oncogenic role in HCC.Keywords: N6-methyladenosine, long non-coding RNAs, prognosis, immune checkpoints inhibitors therapy, hepatocellular carcinoma

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