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The implication of integrative multiple RNA modification-based subtypes in gastric cancer immunotherapy and prognosis.

ABSTRACT: Previous studies have focused on the impact of individual RNA modifications on tumor development. This study comprehensively investigated the effects of multiple RNA modifications, including m6A, alternative polyadenylation, pseudouridine, adenosine-to-inosine editing, and uridylation, on gastric cancer (GC). By analyzing 1,946 GC samples from eleven independent cohorts, we identified distinct clusters of RNA modification genes with varying survival rates and immunological characteristics. We assessed the chromatin activity of these RNA modification clusters through regulon enrichment analysis. A prognostic model was developed using Stepwise Regression and Random Survival Forest algorithms and validated in ten independent datasets. Notably, the low-risk group showed a more favorable prognosis and positive response to immune checkpoint blockade therapy. Single-cell RNA sequencing confirmed the abundant expression of signature genes in B cells and plasma cells. Overall, our findings shed light on the potential significance of multiple RNA modifications in GC prognosis, stemness development, and chemotherapy resistance.

SUBMITTER: Zhang X

PROVIDER: S-EPMC10839690 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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The implication of integrative multiple RNA modification-based subtypes in gastric cancer immunotherapy and prognosis.

Zhang Xiangnan X Wu Liuxing L Jia Liqing L Hu Xin X Yao Yanxin Y Liu Huahuan H Ma Junfu J Wang Wei W Li Lian L Chen Kexin K Liu Ben B

iScience 20240112 2

Previous studies have focused on the impact of individual RNA modifications on tumor development. This study comprehensively investigated the effects of multiple RNA modifications, including m6A, alternative polyadenylation, pseudouridine, adenosine-to-inosine editing, and uridylation, on gastric cancer (GC). By analyzing 1,946 GC samples from eleven independent cohorts, we identified distinct clusters of RNA modification genes with varying survival rates and immunological characteristics. We as ...[more]

PMID: 38318382

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Project description:BackgroundEnhancer RNAs (eRNAs), the transcriptional products of active enhancers, are of great significance in the initial progression of cancers. However, the biological function and bioinformatics profiles of eRNA in gastric cancer remains largely enigmatic.MethodsFirstly, STAD were clustered into three subtypes with the data of eRNA expression from TCeA. Then we explored the difference of the tumor immune microenvironment, transcription levels, and transcription regulation among the three clusters. Finally, samples collected from 12 patients diagnosed with STAD were used to conduct qRT-PCR, verifying the conclusion based on network database.ResultsThe three clusters were detected to have different tumor microenvironments: Cluster A has an immune "cold" microenvironment. While cluster B features as more infiltration of immune cells, accompanied with higher expression of immune checkpoints such as PDCD1, LAG3, and TIGIT. Besides, Cluster C shows a higher stromal feature with B lineage, neutrophils, and fibroblasts. Further analyses indicated that CpG island methylation level of Cluster B is different from the other two clusters. Meanwhile, Cluster A and B showed significant enrichment of TP53 and KRAS mutation respectively while Cluster C has higher tumor mutation burden (TMB) and microsatellite instability (MSI). With the elaboration of transcriptional regulation of epigenetic clustering, we detected that Cluster A enriched in epithelial phenotype pathways. Cluster B enriched in cell-cell adhesion. Cluster C enriched in fibroblast proliferation. The clinical cohort show that Cluster B patients have lower interstitial cell characteristics and CAF infiltration.ConclusionWe identified three unique epigenetic clusters of STAD through the differential activation of super-enhancers, and identified Cluster B with a higher immune infiltrating and a better prognosis, which provides a novel understanding of eRNAs and potential clinical applicability of eRNA-based molecular subtypes in gastric cancer.

Project description:BackgroundEpigenetic regulations of the tumor microenvironment (TME) and immunotherapy have been investigated in recent years. Nevertheless, the potential value of mitochondrial ribosomal RNA (mt-rRNA) modification in regulation of the TME and immunotherapy remains unknown.MethodsWe comprehensively investigated the mt-rRNA-modification patterns in glioma patients based on nine regulators of mt-rRNA. Subsequently, these modification patterns were correlated systematically with immunologic characteristics and immunotherapy. An "mt-rRNA predictor" was constructed and validated in multiple publicly available cohorts to provide guidance for prognosis prediction and immunotherapy of glioma patients.ResultsTwo distinct patterns of mt-rRNA modification were determined based on the evidence that nine regulators of mt-rRNA correlated significantly with most clinicopathologic characteristics, immunomodulators, TME, immune-checkpoint blockers (ICBs), and prognosis. Patients with mt-rRNA subtype II presented significantly poorer overall survival/progression-free survival (OS/PFS), but higher tumor mutational burden (TMB), more somatic mutations, and copy number variation (CNV). These two mt-rRNA subtypes had distinct TME patterns and responses to ICB therapy. An mt-rRNA predictor was constructed and validated in four glioma cohorts. The subtype with high mt-rRNA score, characterized by increased TMB, infiltration of immune cells, and activation of immunity, suggested an immune-activated phenotype, and was also linked to greater sensitivity to immunotherapy using anti-programmed cell death protein 1 (PD-1) but resistance to temozolomide.ConclusionsRegulators of mt-rRNA modification have indispensable roles in the complexity and diversity of the TME and prognosis. This novel classification based on patterns of mt-rRNA modification could provide an effective prognostic predictor and guide more appropriate immunotherapy/chemotherapy strategies for glioma patients.

Project description:BackgroundGastric cancer (GC) is a common upper gastrointestinal tumor. However, the evaluation of prognosis and treatment response in patients with gastric cancer remains a challenge. Programmed cell death (PCD) is one of the important terminal paths for the cells of metazoans, and is involved in a variety of biological events that include morphogenesis, maintenance of tissue homeostasis, and elimination of harmful cells. The objective of this project is to investigate the predictive significance of cell death pathways and create prognostic signatures associated to cell death, with the purpose of forecasting prognosis and providing guidance for the treatment of gastric cancer.MethodsGene transcription profiles and corresponding clinical data of gastric cancer patients were collected from The Cancer Genome Atlas (TCGA-STAD, n = 448) and the Gene Expression Comprehensive Database (GSE84437, n = 483). Thirteen types of cell death-related genes, including apoptosis, necroptosis, pyroptosis, ferroptosis, autophagy, cuprotosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, were analysed. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Patients were categorized into high and low-risk groups based on the median risk score for survival difference analysis. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Additionally, the response to immunotherapy in the high-risk and low-risk groups was calculated using the oncoPredict algorithm. Futhermore, the model genes were validated in the GEO validation set.ResultsA total of 324 differential programmed cell death (PCD)-related genes were identified, and 65 were selected through single-factor Cox analysis. Six PCD-related genes were ultimately identified by Lasso regression to construct a prognostic risk score model. The log-rank test revealed that patients in the high-risk group had inferior survival time compared with those in the low-risk group. The area under the ROC curve (AUC) for the training group at years 1, 3, and 5 were 0.684, 0.713, 0.743, respectively, while the AUC for the validation cohort at years 1, 3, and 5 were 0.695, 0.704, and 0.707, respectively. Unsupervised clustering identified potential subtypes included in the model, and a survival difference was also observed between the two subgroups. Multifactor Cox results, combined with clinical information, demonstrated that the prognostic risk score can serve as an independent prognostic factor, irrespective of other clinical features.ConclusionBy comprehensively analyzing multiple cell death patterns, we have established a novel model that accurately forecasts the clinical prognosis and drug sensitivity of gastric cancer. It was found that all 12 representative drugs may not be suitable for patients in high-risk groups.

Dataset Information

The implication of integrative multiple RNA modification-based subtypes in gastric cancer immunotherapy and prognosis.

Publications

The implication of integrative multiple RNA modification-based subtypes in gastric cancer immunotherapy and prognosis.

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