ArticleFrontiers in immunology2022
Cross-Talk of Multiple Types of RNA Modification Regulators Uncovers the Tumor Microenvironment and Immune Infiltrates in Soft Tissue Sarcoma.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 24 citations in OpenAlex.
- Regulatory roles of N6-methyladenosine methylation factors in melanoma invasion and metastasis (Review).Oncology letters · 2026Review
- Unravelling Multilayered RNA Modification Networks in Female Reproduction and Obstetric/Gynaecologic Disorders.Biomolecules · 2026Review
- mInternational journal of molecular sciences · 2026Article
- Global Co-regulatory Cross Talk Between mMolecular neurobiology · 2025Article
- Comprehensive analysis of TMEM9 in human tumors.Discover oncology · 2025Article
- Soft tissue sarcomas at the single-cell and spatial resolution: new markers and targets.Cancer gene therapy · 2025Review
- Immunomodulatory role of RNA modifications in sex hormone-dependent cancers.Frontiers in immunology · 2025Review
- Integrated multi-omics analysis and machine learning identify G protein-coupled receptor-related signatures for diagnosis and clinical benefits in soft tissue sarcoma.Frontiers in immunology · 2025Article
- A Review on Canine and Human Soft Tissue Sarcomas: New Insights on Prognosis Factors and Treatment Measures.Veterinary sciences · 2024Review
- Multiplex Profiling of Biomarker and Drug Uptake in Single Cells Using Microfluidic Flow Cytometry and Mass Spectrometry.ACS nano · 2024Article
- M7G-related tumor immunity: novel insights of RNA modification and potential therapeutic targets.International journal of biological sciences · 2024Review
- PIK3CD correlates with prognosis, epithelial-mesenchymal transition and tumor immune infiltration in breast carcinoma.Discover oncology · 2023Article
- A novel m6A/m5C/m1A score signature to evaluate prognosis and its immunotherapy value in colon cancer patients.Journal of cancer research and clinical oncology · 2023Article
- Integration analysis of senescence-related genes to predict prognosis and immunotherapy response in soft-tissue sarcoma: evidence based on machine learning and experiments.Frontiers in pharmacology · 2023Article
- Deciphering the Divergent Gene Expression Landscapes of m6A/m5C/m1A Methylation Regulators in Hepatocellular Carcinoma Through Single-Cell and Bulk RNA Transcriptomic Analysis.Journal of hepatocellular carcinoma · 2023Article
- Deciphering the role of NETosis-related signatures in the prognosis and immunotherapy of soft-tissue sarcoma using machine learning.Frontiers in pharmacology · 2023Article
- Vital roles of mFrontiers in immunology · 2023Review
- Identification and validation of RNA methylation-related alternative splicing gene signature for low-grade glioma to predict survival and immune landscapes.Journal of cancer research and clinical oncology · 2023Article
- Modification of m5C regulators in sarcoma can guide different immune infiltrations as well as immunotherapy.Frontiers in surgery · 2022Article
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Soft-tissue sarcoma (STS) represents a rare and diverse cohort of solid tumors, and encompasses over 100 various histologic and molecular subtypes. In recent years, RNA modifications including m Methods: In this study, we comprehensively investigated transcriptional and genetic alterations of 32 RNA modification regulators in STS patients from The Cancer Genome Atlas (TCGA) cohort and validated them in the Gene Expression Omnibus (GEO) cohort. Single-cell transcriptomes were introduced to identify regulators within specific cell types, with own sequencing data and RT-qPCR conducted for biological validation. Distinct regulator clusters and regulator gene subtypes were identified by using unsupervised consensus clustering analysis. We further built the regulator score model based on the prognostic regulator-related differentially expressed genes (DEGs), which could be used to quantitatively assess the risk for individual STS patients. The clinical and biological characteristics of different regulator score groups were further examined. Results: A total of 455 patients with STS were included in this analysis. The network of 32 RNA modification regulators demonstrated significant correlations within multiple different RNA modification types. Distinct regulator clusters and regulator gene subtypes were characterized by markedly different prognoses and TME landscapes. The low regulator score group in the TCGA-SARC cohort was characterized by poor prognosis. The robustness of the scoring model was further confirmed by the external validation in GSE30929 and GSE17674. The regulator score was negatively correlated with CD4+ T cell, Th2 cell, and Treg cell recruitment and most immunotherapy-predicted pathways, and was also associated with immunotherapy efficacy. Conclusions: Overall, our study is the first to demonstrate the cross-talk of RNA modification regulators and the potential roles in TME and immune infiltrates in STS. The individualized assessment based on the regulator score model could facilitate and optimize personalized treatment.
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