Research Paper Volume 15, Issue 12 pp 5445—5481

Cross-talk of RNA modification "writers" describes tumor stemness and microenvironment and guides personalized immunotherapy for gastric cancer

Zhuoqi Li1,2, , Xuehong Zhang2, , Wenjie Weng2, , Ge Zhang2, , Qianwen Ren2, , Yuan Tian1,3, ,

  • 1 Radiotherapy Department, Shandong Second Provincial General Hospital, Shandong University, Jinan, China
  • 2 Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Division of Etiology, Peking University Cancer Hospital and Institute, Peking University, Beijing, China
  • 3 Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial ENT Hospital, Shandong University, Jinan, China

Received: March 24, 2023       Accepted: May 27, 2023       Published: June 14, 2023
How to Cite

Copyright: © 2023 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Background: RNA modifications, TME, and cancer stemness play significant roles in tumor development and immunotherapy. The study investigated cross-talk and RNA modification roles in the TME, cancer stemness, and immunotherapy of gastric cancer (GC).

Methods: We applied an unsupervised clustering method to distinguish RNA modification patterns in GC. GSVA and ssGSEA algorithms were applied. The WM_Score model was constructed for evaluating the RNA modification-related subtypes. Also, we conducted an association analysis between the WM_Score and biological and clinical features in GC and explored the WM_Score model’s predictive value in immunotherapy.

Results: We identified four RNA modification patterns with diverse survival and TME features. One pattern consistent with the immune-inflamed tumor phenotype showed a better prognosis. Patients in WM_Score high group were related to adverse clinical outcomes, immune suppression, stromal activation, and enhanced cancer stemness, while WM_Score low group showed opposite results. The WM_Score was correlated with genetic, epigenetic alterations, and post-transcriptional modifications in GC. Low WM_Score was related to enhanced efficacy of anti-PD-1/L1 immunotherapy.

Conclusions: We revealed the cross-talk of four RNA modification types and their functions in GC, providing a scoring system for GC prognosis and personalized immunotherapy predictions.


TME: Tumor microenvironment; m6A: N6-methyladenosine; m1A: N1-methyladenosine; APA: Alternative polyadenylation; A-to-I: A-to-inosine RNA editing; GC: Gastric cancer; WM: Writers of RNA modification; DEGs: Differentially expressed genes; EMT: Epithelial-mesenchymal transition; 3’UTR: 3′-untranslated region; CSC: Cancer stem cell; ICI: Immune checkpoint inhibitor; Pan-F-TBRS: Pan-fibroblast TGFb response signature; APM: Antigen processing machinery; GEO: Gene-Expression Omnibus; TCGA: The Cancer Genome Atlas; GSVA: Gene set variation analysis; ssGSEA: Single-sample gene-set enrichment analysis; PCA: Principal component analysis; STAD: Stomache adenocarcinoma; WGCNA: Weighted gene co-expression network analysis; CNV: Copy number variation; PDUI: Percentage of Distal polyA site Usage Index; ICB: Immune checkpoint blockade; HPA: The Human Protein Atlas; HR: Hazard ratios; ROC: Receiver operating characteristic; GO: Gene ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; MSI: Microsatellite instability; TMB: Tumor mutation burden.