Dataset Information

Association of RYR2 Mutation With Tumor Mutation Burden, Prognosis, and Antitumor Immunity in Patients With Esophageal Adenocarcinoma.

ABSTRACT: Background: Esophageal adenocarcinoma (EAC) remains a leading cause of cancer-related deaths worldwide and demonstrates a predominant rising incidence in Western countries. Recently, immunotherapy has dramatically changed the landscape of treatment for many advanced cancers, with the benefit in EAC thus far been limited to a small fraction of patients. Methods: Using somatic mutation data of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium, we delineated the somatic mutation landscape of EAC patients from US and England. Based on the expression data of TCGA cohort, multiple bioinformatics algorithms were utilized to perform function annotation, immune cell infiltration analysis, and immunotherapy response assessment. Results: We found that RYR2 was a common frequently mutated gene in both cohorts, and patients with RYR2 mutation suggested higher tumor mutation burden (TMB), better prognosis, and superior expression of immune checkpoints. Moreover, RYR2 mutation upregulated the signaling pathways implicated in immune response and enhanced antitumor immunity in EAC. Multiple bioinformatics algorithms for assessing immunotherapy response demonstrated that patients with RYR2 mutation might benefit more from immunotherapy. In order to provide additional reference for antitumor therapy of different RYR2 status, we identified nine latent antitumor drugs associated with RYR2 status in EAC. Conclusion: This study reveals a novel gene whose mutation could be served as a potential biomarker for prognosis, TMB, and immunotherapy of EAC patients.

SUBMITTER: Liu Z

PROVIDER: S-EPMC8166246 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Colon adenocarcinoma (COAD) is one of the diseases with the highest morbidity and mortality in the world. At present, immunotherapy has become a valuable method for the treatment of COAD. Tumor mutational burden (TMB) is considered to be the most common biomarker for predicting immunotherapy. According to reports, the mutation rate of COAD ranks third. However, whether these gene mutations are related to TMB and immune response is still unknown. Here, COAD somatic mutation data were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Bioinformatics methods were used to study the relationships among gene mutations, COAD survival prognosis, and tumor immune response. A total of 22 of the top 40 mutations in TCGA and ICGC databases were the same. Among them, the USH2A mutation was associated with high TMB and poor clinical prognosis. According to Gene Set Enrichment Analysis (GSEA) and the CIBERSORT algorithm, we determined that the USH2A mutation upregulates signaling pathways involved in the immune system and the antitumor immune response. In cases with a USH2A mutation, the immune score and MSI score of TCGA samples increased, the expression of immune checkpoint genes decreased significantly, and the TIDE score decreased significantly. Dependent on the presence or absence of a USH2A mutation, TCGA COAD samples were analyzed for differentially expressed genes, 522 of which were identified. Using a univariate Cox analysis and LASSO COX analysis of these differential genes, a prediction model was established, which established significant differences in the infiltration of immune cells, immune checkpoint gene expression, immune score, MSI score, TMB, and TIDE in patients in high- and low-risk groups. In conclusion, mutation of USH2A is frequent in COAD and is related to an increase in TMB and the antitumor immunity. The differential genes screened by USH2A mutation allowed the construction of a risk model for predicting the survival and prognosis of cancer patients, in addition to providing new ideas for COAD immunotherapy.

Project description:PurposeTumor mutation burden (TMB) and tumor-infiltrating lymphocytes (TILs) have been well recognized as molecular determinants of immunotherapy responsiveness. In this study, we aimed to construct a TMB prognostic model and explore biomarkers that have predictive potential for prognosis and therapeutic effect in lung adenocarcinoma (LUAD).Patients and methodsThe TCGA, GEO and Immport databases were used to analyze the mutation profiles and immune infiltration of LUAD. TMB scores were calculated and differential analysis was conducted to identify TMB-related genes. Then, Cox regression model and survival analysis were applied to identify the prognostic genes and construct a TMB prognostic model. The expression and prognostic value of CD1B were further verified by immunohistochemistry (IHC) in 92 patient tissue samples. GSEA was performed to analyze the signaling pathways associated with CD1B expression.ResultsHigh-TMB samples exhibited higher infiltration of CD8+ T cells, CD4+ memory T cells, and M1 macrophages. A total of 397 TMB-related differentially expressed genes were identified, of which 47 were immune-related genes. Cox regression analyses determined 3 hub TMB-related immune genes (CD1B, SCGB3A1, and VEGFD) with prognostic effects, and a TMB prognostic model was constructed. The model demonstrated robust predictive ability in both the training (TCGA) and testing (GEO) datasets. Notably, CD1B was identified as an independent prognostic factor. IHC of clinical samples showed that low expression of CD1B was related to poor overall survival and advanced pathological stages. In addition, there was a strong positive correlation between CD1B and most immune checkpoint molecules, including PD-L1. CD1B expression was associated with immune cell infiltration and immune activation in LUAD.ConclusionOur study constructed a TMB prognostic model that effectively predicted the prognosis of LUAD patients. CD1B expression is correlated with better prognosis and promotes antitumor immunity in LUAD, which may serve as a potential prognostic biomarker and immune-related therapeutic target for LUAD.

Dataset Information

Association of RYR2 Mutation With Tumor Mutation Burden, Prognosis, and Antitumor Immunity in Patients With Esophageal Adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets