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Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors
Published on: August 16, 2024
Cross-Talk of Multiple Types of RNA Modification Regulators Uncovers the Tumor Microenvironment and Immune
Lin Qi1,2, Wenchao Zhang1,2, Xiaolei Ren1,2
1Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.
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 m6A, m5C, m1A, and m7G have been demonstrated to regulate immune response and tumorigenesis. Nevertheless, the cross-talk among these RNA modification regulators and related effects upon the tumor microenvironment (TME), immune infiltrates, and immunotherapy in STS remain poorly understood.
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.
Insights
This study reveals RNA modification regulators impact soft-tissue sarcoma (STS) progression and immune infiltration. A novel regulator score model aids in assessing STS patient risk and optimizing personalized immunotherapy.
Area of Science:
- Oncology
- Molecular Biology
- Immunology
Background:
- Soft-tissue sarcoma (STS) is a rare, heterogeneous cancer with over 100 subtypes.
- RNA modifications (m6A, m5C, m1A, m7G) influence immunity and cancer, but their interplay in STS is unclear.
- The impact of RNA modification regulators on the tumor microenvironment (TME) and immunotherapy response in STS requires further investigation.
Purpose of the Study:
- To comprehensively investigate RNA modification regulators in soft-tissue sarcoma (STS).
- To explore the associations between these regulators, the tumor microenvironment (TME), immune infiltrates, and immunotherapy efficacy in STS.
- To develop a prognostic model for risk stratification and personalized treatment in STS.
Main Methods:
- Analysis of transcriptional and genetic alterations of 32 RNA modification regulators in TCGA and GEO cohorts.
- Single-cell transcriptomics to identify cell-type-specific regulators.
- Development and validation of a regulator score model based on prognostic differentially expressed genes (DEGs).
Main Results:
- Identified significant correlations among RNA modification regulators, revealing distinct clusters and subtypes with varied prognoses and TME landscapes.
- A low regulator score was associated with poor prognosis in STS.
- The regulator score negatively correlated with immune cell infiltration (CD4+ T cells, Th2, Treg) and immunotherapy pathways, indicating potential impacts on treatment efficacy.
Conclusions:
- This study is the first to elucidate the cross-talk of RNA modification regulators in STS and their roles in the TME and immune infiltrates.
- The developed regulator score model provides a quantitative tool for assessing individual STS patient risk.
- This model can facilitate optimized personalized treatment strategies for soft-tissue sarcoma.
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