Dataset Information

Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma.

ABSTRACT:

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent malignancies worldwide, N6-methyladenosine (m6A) has been shown to play important roles in regulating gene expression and phenotypes in both health and disease. Here, our purpose is to construct a m6A-regulrator-based risk score (RS) for prediction of the prognosis of ccRCC.

Methods

We used clinical and expression data of m6A related genes from The Cancer Genome Atlas (TCGA) dataset and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis to develop an RS to predict survival of patients with ccRCC, and analyzed correlations between RS and other clinical indicators such as age, grade and stage. Validation of this RS was then engaged in another cohort, E-MTAB-1980 from the ArrayExpress dataset. Finally, we used quantitative real-time PCR to analyze the expression profile of genes consists of the RS.

Results

A three-gene RS including METTL3, METTL14 and HNRNPA2B1 which can predict overall survival (OS) of ccRCC patients from TCGA. After applying this RS into the validation cohort from Arrayexpress, we found that it successfully reproduced the result; furthermore, the results of PCR validation were in line with our analysis.

Conclusion

To sum up, our study has identified an RS composed of m6A related genes that may predict the prognosis of ccRCC patients, which might be helpful for future therapeutic strategies. Our results call for further experimental studies for validations.

SUBMITTER: Zhao Y

PROVIDER: S-EPMC7085294 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma.

Zhao Yiqiao Y Tao Zijia Z Chen Xiaonan X

PeerJ 20200318

<h4>Background</h4>Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent malignancies worldwide, N6-methyladenosine (m6A) has been shown to play important roles in regulating gene expression and phenotypes in both health and disease. Here, our purpose is to construct a m6A-regulrator-based risk score (RS) for prediction of the prognosis of ccRCC.<h4>Methods</h4>We used clinical and expression data of m6A related genes from The Cancer Genome Atlas (TCGA) dataset and the Least Absol ...[more]

PMID: 32219036

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Project description:BackgroundTumor Protein D52-Like 2 (TPD52L2) is a tumor-associated protein that participates in B-cell differentiation. However, the role of TPD52L2 in the pathological process of clear cell renal cell carcinoma (ccRCC) is unclear.MethodsMultiple omics data of ccRCC samples were obtained from public databases, and 5 pairs of ccRCC tissue samples were collected from the operating room. Wilcox, chi-square test, Kaplan-Meier method, receiver operating characteristic curve, regression analysis, meta-analysis, and correlation analysis were used to clarify the relationship of TPD52L2 with clinical features, prognosis, and immune microenvironment. Functional enrichment analysis was performed to reveal the potential pathways in which TPD52L2 participates in the progression of ccRCC. The siRNA technique was used to knockdown in the expression level of TPD52L2 in 786-O cells to verify its effect on ccRCC progression.ResultsFirst, TPD52L2 was found to be upregulated in ccRCC at both mRNA and protein levels. Second, TPD52L2 was significantly associated with poor prognosis and served as an independent prognostic factor. Moreover, TPD52L2 expression was regulated by DNA methylation, and some methylation sites were associated with ccRCC prognosis. Third, TPD52L2 overexpression may participate in the pathological process through various signaling pathways such as cytokine-cytokine receptor interactions, PI3K-Akt, IL-17, Wnt, Hippo signaling pathway, and ECM-receptor interactions. Interestingly, TPD52L2 expression level was also closely related to the abundance of various immune cells, immune checkpoint expression, and TMB. Finally, in vitro experiments confirmed that knocking down TPD52L2 can inhibit the proliferation, migration, and invasion abilities of ccRCC cells.ConclusionThis study for the first time revealed the upregulation of TPD52L2 expression in ccRCC, which is closely associated with poor prognosis of patients and is a potentially valuable therapeutic and efficacy assessment target for immunotherapy.

Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is a widespread urogenital neoplasm. However, the therapeutic efficacy of these methods is unsatisfactory. In-depth screening of biomarkers could aid early diagnosis and therapy and predict patient prognosis.MethodsThe GEO datasets were selected with specific criteria. Differentially expressed gene (DEG), weighted gene coexpression network analysis (WGCNA), protein-protein interaction, LASSO, random forest, and Cox regression analyses were applied to identify the independent prognostic biomarkers. Survival analysis, correlation with clinical features, gene set enrichment analysis (GSEA), GO enrichment, immune infiltration analysis, and correlation with cuproptosis-related genes were carried out to determine the prognostic value and possible molecular mechanisms of the TSVR. Wound healing assays, transwell assays, cell colony formation experiments, flow cytometry, and immunohistochemistry (IHC) analysis were used to validate the functional attributes of CRYL1.ResultsFour GEO datasets were included to screen for hub genes. DEG combined with WGCNA showed a key module with 300 genes having the strongest correlation with "survival state" (R2 = -0.24 and P = 7e-8); six genes were identified by LASSO, random forest, and Cytoscape. Finally, CRYL1 (hazard ratio (HR) = 2.01, P < 0.001) was selected as an independent prognostic biomarker. The higher CRYL1 expression group had better DFS and overall survival (OS). GSEA demonstrated that the CRYL1-related DEGs were enriched mainly in the metabolism of sugar, fat, and amino acids. CRYL1 is positively correlated with FDX1 and the LIAS pathway, which are important molecule involved in cuproptosis. CRYL1 affects the infiltration abundance of four immune cells and can predict a positive OS. Wound healing, transwell, cell colony formation, and flow cytometry assays demonstrated that CRYL1 silencing enhances migration and proliferation and leads to a decreased apoptotic ratio. IHC analysis suggested that CRYL1 was highly expressed in adjacent tissues.ConclusionsCRYL1 is a robust predictive marker for clinicopathological characteristics and survival status in ccRCC patients.

Dataset Information

Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma.

Background

Methods

Results

Conclusion

Publications

Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma.

Similar Datasets

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