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ORIGINAL RESEARCH article

Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2024 | doi: 10.3389/fimmu.2024.1374465
This article is part of the Research Topic Spotlighting the Interaction Network of Hub Genes, Molecules, and Cells in the Tumor Immune Microenvironment (TIME) and their Contribution to Malignant Progression View all 8 articles

An m 6 A Regulators-Related Classifier for Prognosis and Tumor Microenvironment Characterization in Hepatocellular Carcinoma

Provisionally accepted
Song-Mei Liu Song-Mei Liu 1*Shaohua Xu Shaohua Xu 1Ying Yang Ying Yang 1Kexin Dong Kexin Dong 1Hanfei Zhang Hanfei Zhang 1Luo Chunhua Luo Chunhua 2
  • 1 Zhongnan Hospital, Wuhan University, Wuhan, Hubei Province, China
  • 2 China Three Gorges University, Yichang, Hubei Province, China

The final, formatted version of the article will be published soon.

    Background: Increasing evidence have highlighted the biological significance of mRNA N 6methyladenosine (m 6 A) modification in regulating tumorigenicity and progression. However, the potential roles of m 6 A regulators in tumor microenvironment (TME) formation and immune cell infiltration in liver hepatocellular carcinoma (LIHC or HCC) requires further clarification.Method: RNA sequencing data were obtained from TCGA-LIHC databases and ICGC-LIRI-JP databases. Consensus clustering algorithm was used to identify m 6 A regulators cluster subtypes.Weighted gene co-expression network analysis (WGCNA), LASSO regression, Random Forest (RF), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) were applied to identify candidate biomarkers, and then a m 6 Arisk score model was constructed. The correlations of m 6 Arisk score with immunological characteristics (immunomodulators, cancer immunity cycles, tumorinfiltrating immune cells (TIICs), and immune checkpoints) were systematically evaluated. The effective performance of nomogram was evaluated using concordance index (C-index), calibration plots, decision curve analysis (DCA), and receiver operating characteristic curve (ROC).: Two distinct m 6 A modification patterns were identified based on 23 m 6 A regulators, which were correlated with different clinical outcomes and biological functions. Based on the constructed m 6 Arisk score model, HCC patients can be divided into two distinct risk score subgroups. Further analysis indicated that the m 6 Arisk score showed excellent prognostic performance. Patients with a high m 6 Arisk score was significantly associated with poorer clinical outcome, lower drug sensitivity, and higher immune infiltration. Moreover, we developed a nomogram model by incorporating the m 6 Arisk score and clinicopathological features. The application of the m 6 Arisk score for the prognostic stratification of HCC has good clinical applicability and clinical net benefit. Conclusions: Our findings reveal the crucial role of m 6 A modification patterns for predicting HCC TME status and prognosis, and highlight the good clinical applicability and net benefit of m 6 Arisk score in terms of prognosis, immunophenotype, and drug therapy in HCC patients.

    Keywords: N 6 -methyladenosine, WGCNA, SVM-RFE, LASSO, Consensus clustering algorithm, TIICs, DCA

    Received: 22 Jan 2024; Accepted: 11 Jul 2024.

    Copyright: © 2024 Liu, Xu, Yang, Dong, Zhang and Chunhua. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Song-Mei Liu, Zhongnan Hospital, Wuhan University, Wuhan, 430071, Hubei Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.