Dataset Information

Establishment of a Risk Signature Based on m6A RNA Methylation Regulators That Predicts Poor Prognosis in Renal Cell Carcinoma.

ABSTRACT:

Purpose

N6-methyladenosine (m6A) modifications represent one of the most common methylation modifications, and they are mediated by m6A RNA methylation regulators. However, their functions in renal cell carcinoma (RCC) are not completely understood. The aim of this study was to investigate the effects of the regulators in RCC.

Materials and methods

The expression levels of the 13 main m6A RNA methylation regulators in RCC were detected and consensus clustering was performed to explore their relationships with RCC. Thereafter, a risk signature based on the regulators was established. This risk model was fully verified by conducting prognostic analyses using two datasets (The Cancer Genome Atlas [TCGA] and Gene Expression Omnibus [GEO] datasets) and a ROC curve analysis.

Results

Of the 13 main m6A regulators, six were significantly upregulated and four were significantly downregulated in 893 RCC cases compared to 128 normal controls in the TCGA database. Consensus clustering based on the regulators identified two clusters of RCC cases, which were significantly associated with a pathological characteristic (T status). Thus, these results indicated that m6A RNA methylation regulators were associated with RCC. Thereafter, a risk model involving two of the regulators (METTL14 and WTAP) was established. The alterations in the mRNA and protein expression levels of these two regulators were further confirmed based on Human Protein Atlas data and real-time PCR in RCC and normal cell lines. The results indicated that the risk model may serve as an independent prognostic marker of overall survival, and it was also associated with clinicopathological characteristics (T status, M status, pathological stage, and gender) in RCC.

Conclusion

Collectively, the results of this study indicated that the risk model (based on two m6A RNA methylation regulators) may serve as an independent prognostic indicator of RCC, which may aid further investigation into m6A RNA modification in RCC.

SUBMITTER: Wei J

PROVIDER: S-EPMC7814279 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Establishment of a Risk Signature Based on m6A RNA Methylation Regulators That Predicts Poor Prognosis in Renal Cell Carcinoma.

Wei Jingsun J Qian Yucheng Y Tang Yang Y Ge Xiaoxu X Jiang Kai K Fang Yimin Y Fu Dongliang D Kong Xiangxing X Xiao Qian Q Ding Kefeng K

OncoTargets and therapy 20210114

<h4>Purpose</h4>N6-methyladenosine (m6A) modifications represent one of the most common methylation modifications, and they are mediated by m6A RNA methylation regulators. However, their functions in renal cell carcinoma (RCC) are not completely understood. The aim of this study was to investigate the effects of the regulators in RCC.<h4>Materials and methods</h4>The expression levels of the 13 main m6A RNA methylation regulators in RCC were detected and consensus clustering was performed to exp ...[more]

PMID: 33488096

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Project description:Objectives: This study aims to explore the roles of 13 m6A RNA methylation regulators in clear cell renal cell carcinoma (ccRCC), and identify a risk signature and prognostic values of m6A RNA methylation regulators in ccRCC. Materials and Methods: RNA sequence data of ccRCC was obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed of 13 m6A RNA methylation regulators in ccRCC stratified by different clinicopathological characteristics were unveiled using "limma" package in R version 3.6.0. Cox regression and LASSO analyses were conducted to identify the powerful independent prognostic factors in ccRCC associated with overall survival (OS). Protein-protein interaction (PPI) network and correlation analyses of the 13 m6A RNA methylation regulators were performed using "STRING" and R package, respectively. Principal component analysis (PCA) was also done using R. In addition, gene ontology (GO), GSEA and Kyoto Encyclopedia of Genes and Genomes pathways were used to functionally annotate the differentially expressed genes in different subgroups. Results: Most of the 13 m6A RNA methylation regulators are differentially expressed in ccRCC tissue samples stratified by different clinicopathological characteristics in 537 patients. Next, a risk signature for predicting prognosis of ccRCC patients, was established based on two powerful independent prognostic m6A RNA methylation regulators (METTL14 and METTL3). Then, two subgroups (cluster1 and 2) were identified by consensus clustering to the two powerful independent factors and the cluster1 had a poorer prognosis than cluster2. Furthermore, the genes in cluster1 were significantly enriched in cancer-related pathways, biological process, and hallmarks, including "cell adhesion molecules (CAMs)," "leukocyte migration," "Wnt/β-catenin signaling," and so on. Conclusion: M6A RNA methylation regulators play important roles in the initiation and progression of ccRCC and provide a novel sight to understand m6A RNA modification in ccRCC.

Project description:BackgroundMETTL14, as one of N6-methyladenosine (m6A) related genes, has been found to be associated with promoting tumorigenesis in different types of cancers. This study was aimed to investigate the prognostic value of METTL14 in clear cell renal cell carcinoma (ccRCC).MethodsWe collected ccRCC patients' clinicopathological parameters information and 13 m6A related genes expression from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses were conducted to investigate whether METTL14 could serve as an independent factor correlated with overall survival (OS). Gene Set Enrichment Analysis (GSEA) was carried out to identify METTL14-related signaling pathways. Moreover, a risk score (RS) was calculated to predict the prognosis of ccRCC. Quantitative real-time PCR (qRT-PCR) was also utilized to verify the expression of METTL14 in clinical specimens.ResultsDifferently expressed m6A related genes were identified between ccRCC tissues and normal tissues. Therein, METTL14 was lowly expressed in ccRCC tissues and verified by qRT-PCR (all p < 0.01). Survival analysis indicated that high expression of METTL14 was associated with better OS (p = 1e-05). GSEA results revealed that high METTL14 expression was enriched in ERBB pathway, MAPK pathway, mTOR pathway, TGF-β pathway and Wnt pathway. Moreover, METTL14 was proved to be an independent prognostic factor by means of univariate and multivariate Cox regression analyses. Nomogram integrating both the METTL14 expression and clinicopathologic variables was also established to provide clinicians with a quantitative approach for predicting survival probabilities of ccRCC. Furthermore, a METTL14-based riskscore (RS) was developed with significant OS (p = 6.661e-16) and increased AUC of 0.856. Besides, significant correlated genes with METTL14 were also provided.ConclusionsOur results indicated that METTL14 could serve as a favorable prognostic factor for ccRCC. Moreover, this study also provided a prognostic signature to predict prognosis of ccRCC and identified METTL14-related signaling pathways.

Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets. Two conditions were compared and each sample has a biological replicate. Samples are hybridized in dye-swap, resulting in 4 hybridizations.

Project description:BackgroundRunt-related transcription factor 1 (RUNX1) was previously reported to play a dual role in promoting or suppressing tumorigenesis in various malignancies. A public dataset from The Cancer Genome Atlas (TCGA) was used to evaluate the role of RUNX1 in clear cell renal cell carcinoma (ccRCC).MethodsThe Wilcoxon signed-rank test was used to compare the expression of RUNX1 in ccRCC tissues and normal tissues. The Wilcoxon signed-rank test and logistic regression were utilized to investigate the relationship between clinicopathological factors and RUNX1 expression. Additionally, we analysed the differences in prognosis between patients with high and low expression of RUNX1 via the Kaplan-Meier method and Cox regression. Gene set enrichment analysis (GSEA) was performed to explore the mechanisms of RUNX1 in ccRCC.ResultsThe expression of RUNX1 in ccRCC tissues was significantly higher than that in normal tissues. High expression of RUNX1 was significantly associated with gender (p = 0.003), clinical stage (p < 0.001), tissue infiltration (p < 0.001), lymph node metastasis (p = 0.037) and histological grade (p < 0.001). Logistic regression analysis showed that high RUNX1 expression was significantly correlated with gender (OR = 1.71 for male vs. female, p = 0.004), histological grade (OR = 11.61 for grade IV vs. I, p < 0.001), clinical stage (OR = 1.55 for stage III/IV vs. I/II, p = 0.014) and tissue infiltration (OR = 1.54 for positive vs. negative, p = 0.018). Kaplan-Meier survival curves revealed that the prognosis of patients with ccRCC with high RUNX1 expression was worse than that of patients with ccRCC with low RUNX1 expression (p < 0.001). Univariate Cox regression analysis showed that high RUNX1 expression was strongly correlated with poor prognosis (HR = 1.60, 95% CI [1.31-1.97], p < 0.001). In addition, high expression of RUNX1 was an independent prognostic factor for poor overall survival (OS), with an HR of 1.50 (95% CI [1.20-1.87], p < 0.001) in multivariate Cox analysis. GSEA showed that the apoptosis, B cell receptor signalling pathway, calcium signalling pathway, chemokine signalling pathway, JAK/STAT signalling pathway, MAPK signalling pathway, p53 signalling pathway, pathways in cancer, T cell receptor signalling pathway, Toll-like receptor signalling pathway, VEGF signalling pathway, and Wnt signalling pathway were significantly enriched in the RUNX1 high-expression phenotype. In conclusion, RUNX1 can be used as a novel prognostic factor and therapeutic target in ccRCC.

Dataset Information

Establishment of a Risk Signature Based on m6A RNA Methylation Regulators That Predicts Poor Prognosis in Renal Cell Carcinoma.

Purpose

Materials and methods

Results

Conclusion

Publications

Establishment of a Risk Signature Based on m6A RNA Methylation Regulators That Predicts Poor Prognosis in Renal Cell Carcinoma.

Similar Datasets

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