Dataset Information

Succinylation Regulators Promote Clear Cell Renal Cell Carcinoma by Immune Regulation and RNA N6-Methyladenosine Methylation.

ABSTRACT: Succinylation is a newly discovered and multienzyme-regulated post-translational modification (PTM) that is associated with the initiation and progression of cancer. Currently, no systematic analyses on the role of succinylation regulators in tumors have been reported. In this study, we performed a comprehensive pan-cancer analysis on four well-known succinylation regulators (CPT1A, KAT2A, SIRT5, and SIRT7). We found that these regulators played specific and critical roles in the prognosis of clear cell renal cell carcinoma (ccRCC). We constructed a risk score (RS) based on two independent prognostic prediction factors, CPT1A and KAT2A, and subsequently developed a nomogram model containing the RS, which showed good accuracy in the prediction of overall survival (OS) in ccRCC patients. Furthermore, we used the similar expression pattern of four succinylation regulators according to consensus clustering analysis to divide the patients into three clusters that exhibited prominently different OS as well as clinicopathological characteristics. Differently expressed genes (DEGs) and pathway enrichment analyses of three clusters indicated that succinylation regulators might promote malignant progression of ccRCC by regulating the infiltration of immune cells and RNA N6-methyladenosine (m6A) methylation. Importantly, our data suggest that CPT1A and SIRT5 might up-regulate and down-regulate the expression of LRPPRC and EIF3B, respectively. Our study systematically analyzed the prognostic predictive values of four succinylation regulators and revealed their potential mechanisms in ccRCC aggressiveness. These data provide new insight into the understanding of succinylation modification and present clinical evidence for its role in ccRCC treatments.

SUBMITTER: Lu W

PROVIDER: S-EPMC7935513 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Succinylation Regulators Promote Clear Cell Renal Cell Carcinoma by Immune Regulation and RNA N6-Methyladenosine Methylation.

Lu Wenqing W Che Xiaofang X Qu Xiujuan X Zheng Chunlei C Yang Xianghong X Bao Bowen B Li Zhi Z Wang Duo D Jin Yue Y Wang Yizhe Y Xiao Jiawen J Qi Jianfei J Liu Yunpeng Y

Frontiers in cell and developmental biology 20210218

Succinylation is a newly discovered and multienzyme-regulated post-translational modification (PTM) that is associated with the initiation and progression of cancer. Currently, no systematic analyses on the role of succinylation regulators in tumors have been reported. In this study, we performed a comprehensive pan-cancer analysis on four well-known succinylation regulators (CPT1A, KAT2A, SIRT5, and SIRT7). We found that these regulators played specific and critical roles in the prognosis of cl ...[more]

PMID: 33681201

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Project description:N6‑methyladenosine (m6A) RNA methylation is the most prevalent type of mRNA modification; however, little is known about its function in clear cell renal cell carcinoma (ccRCC). The present study aimed to establish and validate a m6A‑related risk signature as a prognostic factor for patients with ccRCC. Consensus clustering was used to divide patients with ccRCC from The Cancer Genome Atlas (TCGA) cohort (n=489) into three clusters (cluster 1/2/3) based on 19 m6A RNA methylation regulators. In addition, a m6A‑related risk signature was constructed using TCGA data, and its accuracy was validated using data from the International Cancer Genome Consortium (n=91). The prognostic performance of the risk signature was evaluated by Kaplan‑Meier analyses, least absolute shrinkage and selection operator Cox regression, multivariate Cox regression, receiver operating characteristic curves and nomograms. The results revealed that the majority of the 19 m6A RNA methylation regulators were differentially expressed among ccRCC stratified by different clinicopathological features. The cluster 1 group exhibited a higher frequency of metastasis and poorer overall survival compared with the cluster 2/cluster 3 group. The hallmarks of RNA metabolism, transcription misregulation in cancer and regulation of autophagy, were significantly enriched in the cluster 1 group. A m6A‑related risk signature was constructed and validated with high prognostic accuracy for the prediction of 5‑year survival and recurrence (area under the curve, 0.736 and 0.728, respectively). The present study also established robust nomograms for evaluating the risk of mortality and recurrence for patients with ccRCC (c‑index, 0.783 and 0.819, respectively). The dysregulation of hub m6A RNA methylation regulator expression levels and m6A RNA methylation levels were also validated in multiple RCC cells using in vitro experiments. Taken together, the m6A RNA methylation regulators promoted the malignant progression of ccRCC and exhibited good performance in prognostic predictions. These results provided insight into the development of m6A‑targeted treatments for ccRCC.

Project description:BackgroundKidney renal clear cell carcinoma (KIRC) lacks effective prognostic biomarkers and the role and mechanism of N6-methyladenosine (m6A) modification of long noncoding RNAs (lncRNAs) in KIRC remain unclear.MethodsWe extracted standard mRNA-sequencing and clinical data from the TCGA database. The prognostic risk model was obtained by Lasso regression and Cox regression. We randomly divided the samples into training and test sets, each taking half of the cases. Based on Lasso regression and Cox regression for training set, the prognostic risk signature was constructed; risk scores were calculated with the R package "glmnet." Based on the median value of the prognostic risk score, risk scores were calculated for each patient and we divided all KIRC samples into high-risk and low-risk groups. Then, high- and low-risk subtypes were established and their prognosis, clinical features, and immune infiltration microenvironment were evaluated in test set and the entire sampled data set. The reliability of the prognostic model was confirmed by receiver operating characteristic curve analysis.ResultsWe found 28 prognostic m6A-related lncRNAs and established a m6A-related lncRNAs prognostic signature. Risk score=AC015813.1∗(0.0086)+EMX2OS∗(-0.0101)+LINC00173∗(0.0309)+PWAR5∗(-0.0146)+SNHG1∗(0.0043). The signature showed a better predictive ability than other clinical indicators, including tumor node metastasis classification (TNM), histological, and pathological stages. In the high-risk group, M0 macrophages, CD8+ T cells, and regulatory T cells had significantly higher scores. Contrarily, in the low-risk group, activated dendritic cells, M1 macrophages, mast resting cells, and monocytes had significantly higher scores. In the high-risk group, LSECtin was overexpressed. In the low-risk group, PD-L1 was overexpressed. Moreover, high-risk patients may benefit more from AZ628.ConclusionsIn conclusion, prognosis prediction of patients with KIRC and new insights for immunotherapy are provided by the m6A-related lncRNA prognostic signature.

Project description:BackgroundPatients with advanced clear cell renal cell carcinoma (ccRCC) have a poor prognosis and lack effective prognostic biomarkers. N6-methyladenosine-related lncRNAs (m6A-related long noncoding RNAs [lncRNAs]) have been confirmed to be associated with the development of multiple tumors, but its role in ccRCC is not clear.MethodsGene expression data and clinical information of ccRCC patients were extracted from The Cancer Genome Atlas Database. The prognostic m6A-related lncRNAs were obtained by Pearson's correlation analysis and univariate Cox regression analysis. Afterward, the cluster classification and its correlation with prognosis, clinical characteristics, and immunity were analyzed. LASSO regression was used to establish the prognostic risk model. The predictive performance of the prognostic model was evaluated and validated by survival analysis and receiver operating characteristic curve analysis, et al. The expression of immune checkpoints and immune cell infiltration in patients with different risks were systematically analyzed.ResultsA total of 27 prognostic m6A-related lncRNAs were identified. These m6A-related lncRNAs were differentially expressed between tumor and normal tissues. Among them, 24 high-risk m6A-related lncRNAs were overexpressed in Cluster 2 and correlated with poor prognosis, low stromal score, high expression of immune checkpoints, and immunosuppressive cells infiltration. Based upon, a prognostic risk model composed of seven m6A-related lncRNAs was constructed. After a series of analyses, it was proved that this model had good sensitivity and specificity, and could predict the prognosis of patients with different clinical stratification. The expression of PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, and TIGIT were significantly increased in the high-risk patients, and there was a correlation between the risk score and immune cell infiltration.ConclusionsThe seven m6A-related lncRNAs prognostic risk signature showed reliable prognostic predictive power for ccRCC and was associated with the expression of immune checkpoints and immune cell infiltration. This seven m6A-related lncRNAs signature will be helpful in managing ccRCC and guiding individualized immunotherapy.

Dataset Information

Succinylation Regulators Promote Clear Cell Renal Cell Carcinoma by Immune Regulation and RNA N6-Methyladenosine Methylation.

Publications

Succinylation Regulators Promote Clear Cell Renal Cell Carcinoma by Immune Regulation and RNA N6-Methyladenosine Methylation.

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