scholarly journals Identification of DNA methylation signatures associated with poor outcome in lower-risk Stage, Size, Grade and Necrosis (SSIGN) score clear cell renal cell cancer

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Louis Y. El Khoury ◽  
Shuang Fu ◽  
Ryan A. Hlady ◽  
Ryan T. Wagner ◽  
Liguo Wang ◽  
...  

Abstract Background Despite using prognostic algorithms and standard surveillance guidelines, 17% of patients initially diagnosed with low risk clear cell renal cell carcinoma (ccRCC) ultimately relapse and die of recurrent disease, indicating additional molecular parameters are needed for improved prognosis. Results To address the gap in ccRCC prognostication in the lower risk population, we performed a genome-wide analysis for methylation signatures capable of distinguishing recurrent and non-recurrent ccRCCs within the subgroup classified as ‘low risk’ by the Mayo Clinic Stage, Size, Grade, and Necrosis score (SSIGN 0–3). This approach revealed that recurrent patients have globally hypermethylated tumors and differ in methylation significantly at 5929 CpGs. Differentially methylated CpGs (DMCpGs) were enriched in regulatory regions and genes modulating cell growth and invasion. A subset of DMCpGs stratified low SSIGN groups into high and low risk of recurrence in independent data sets, indicating that DNA methylation enhances the prognostic power of the SSIGN score. Conclusions This study reports a global DNA hypermethylation in tumors of recurrent ccRCC patients. Furthermore, DMCpGs were capable of discriminating between aggressive and less aggressive tumors, in addition to SSIGN score. Therefore, DNA methylation presents itself as a potentially strong biomarker to further improve prognostic power in patients with low risk SSIGN score (0–3).

Author(s):  
Wuping Yang ◽  
Kenan Zhang ◽  
Lei Li ◽  
Yawei Xu ◽  
Kaifang Ma ◽  
...  

Abstract Background Emerging evidence confirms that lncRNAs (long non-coding RNAs) are potential biomarkers that play vital roles in tumors. ZNF582-AS1 is a novel lncRNA that serves as a potential prognostic marker of cancers. However, the specific clinical significance and molecular mechanism of ZNF582-AS1 in ccRCC (clear cell renal cell carcinoma) are unclear. Methods Expression level and clinical significance of ZNF582-AS1 were determined by TCGA-KIRC data and qRT-PCR results of 62 ccRCCs. DNA methylation status of ZNF582-AS1 promoter was examined by MSP, MassARRAY methylation and demethylation analysis. Gain-of-function experiments were conducted to investigate the biological roles of ZNF582-AS1 in the phenotype of ccRCC. The subcellular localization of ZNF582-AS1 was detected by RNA FISH. iTRAQ, RNA pull-down and RIP-qRT-PCR were used to identify the downstream targets of ZNF582-AS1. rRNA MeRIP-seq and MeRIP-qRT-PCR were utilized to examine the N(6)-methyladenosine modification status. Western blot and immunohistochemistry assays were used to determine the protein expression level. Results ZNF582-AS1 was downregulated in ccRCC, and decreased ZNF582-AS1 expression was significantly correlated with advanced tumor stage, higher pathological stage, distant metastasis and poor prognosis. Decreased ZNF582-AS1 expression was caused by DNA methylation at the CpG islands within its promoter. ZNF582-AS1 overexpression inhibited cell proliferative, migratory and invasive ability, and increased cell apoptotic rate in vitro and in vivo. Mechanistically, we found that ZNF582-AS1 overexpression suppressed the N(6)-methyladenosine modification of MT-RNR1 by reducing rRNA adenine N(6)-methyltransferase A8K0B9 protein level, resulting in the decrease of MT-RNR1 expression, followed by the inhibition of MT-CO2 protein expression. Furthermore, MT-RNR1 overexpression reversed the decreased MT-CO2 expression and phenotype inhibition of ccRCC induced by increased ZNF582-AS1 expression. Conclusions This study demonstrates for the first time that ZNF582-AS1 functions as a tumor suppressor gene in ccRCC and ZNF582-AS1 may serve as a potential biomarker and therapeutic target of ccRCC.


2019 ◽  
Vol 60 (11) ◽  
pp. 1013 ◽  
Author(s):  
Shanping Shi ◽  
Shazhou Ye ◽  
Xiaoyue Wu ◽  
Mingjun Xu ◽  
Renjie Zhuo ◽  
...  

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qianwei Xing ◽  
Tengyue Zeng ◽  
Shouyong Liu ◽  
Hong Cheng ◽  
Limin Ma ◽  
...  

Abstract Background The role of glycolysis in tumorigenesis has received increasing attention and multiple glycolysis-related genes (GRGs) have been proven to be associated with tumor metastasis. Hence, we aimed to construct a prognostic signature based on GRGs for clear cell renal cell carcinoma (ccRCC) and to explore its relationships with immune infiltration. Methods Clinical information and RNA-sequencing data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and ArrayExpress datasets. Key GRGs were finally selected through univariate COX, LASSO and multivariate COX regression analyses. External and internal verifications were further carried out to verify our established signature. Results Finally, 10 GRGs including ANKZF1, CD44, CHST6, HS6ST2, IDUA, KIF20A, NDST3, PLOD2, VCAN, FBP1 were selected out and utilized to establish a novel signature. Compared with the low-risk group, ccRCC patients in high-risk groups showed a lower overall survival (OS) rate (P = 5.548Ee-13) and its AUCs based on our established signature were all above 0.70. Univariate/multivariate Cox regression analyses further proved that this signature could serve as an independent prognostic factor (all P < 0.05). Moreover, prognostic nomograms were also created to find out the associations between the established signature, clinical factors and OS for ccRCC in both the TCGA and ArrayExpress cohorts. All results remained consistent after external and internal verification. Besides, nine out of 21 tumor-infiltrating immune cells (TIICs) were highly related to high- and low- risk ccRCC patients stratified by our established signature. Conclusions A novel signature based on 10 prognostic GRGs was successfully established and verified externally and internally for predicting OS of ccRCC, helping clinicians better and more intuitively predict patients’ survival.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11880
Author(s):  
Hui Zhao ◽  
Junjun Zhang ◽  
Xiaoliang Fu ◽  
Dongdong Mao ◽  
Xuesen Qi ◽  
...  

The members of the Nedd4-like E3 family participate in various biological processes. However, their role in clear cell renal cell carcinoma (ccRCC) is not clear. This study systematically analyzed the Nedd4-like E3 family members in ccRCC data sets from multiple publicly available databases. NEDD4L was identified as the only NEDD4 family member differentially expressed in ccRCC compared with normal samples. Bioinformatics tools were used to characterize the function of NEDD4L in ccRCC. It indicated that NEDD4L might regulate cellular energy metabolism by co-expression analysis, and subsequent gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A prognostic model developed by the LASSO Cox regression method showed a relatively good predictive value in training and testing data sets. The result revealed that NEDD4L was associated with biosynthesis and metabolism of ccRCC. Since NEDD4L is downregulated and dysregulation of metabolism is involved in tumor progression, NEDD4L might be a potential therapeutic target in ccRCC.


2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Maolin Hu ◽  
Jiangling Xie ◽  
Huiming Hou ◽  
Ming Liu ◽  
Jianye Wang

Background. Few previous studies have comprehensively explored the level of DNA methylation and gene expression in ccRCC. The purpose of this study was to identify the key clear cell renal cell carcinoma- (ccRCC-) related DNA methylation-driven genes (MDG) and to build a prognostic model based on the level of DNA methylation. Methods. RNA-seq transcriptome data and DNA methylation data were obtained from The Cancer Genome Atlas. Based on the MethylMix algorithm, we obtain ccRCC-related MDG. The univariate and multivariate Cox regression analyses were employed to investigate the correlation between patient overall survival and the methylation level of each MDG. Finally, a prognosis risk score was established based on a linear combination of the regression coefficient derived from the multivariate Cox regression model (β) multiplied with the methylation level of the gene. Results. 19 ccRCC-related MDG were identified. Three MDG (NCKAP1L, EVI2A, and BATF) were further screened and integrated into a prognostic risk score model, risk score=3.710∗methylation level of NCKAP1L+−3.892∗methylation level of EVI2A+−3.907∗methylation level of BATF. The risk model was independent from conventional clinical characteristics as a prognostic factor for ccRCC (HR=1.221, 95% confidence interval: 1.063–1.402, and P=0.005). The joint survival analysis showed that the gene expression and methylation levels of the prognostic genes EVI2A and BATF were significantly related with prognosis. Conclusion. This study provided an important bioinformatics foundation for in-depth studies of ccRCC DNA methylation.


2016 ◽  
Vol 76 (7) ◽  
pp. 1954-1964 ◽  
Author(s):  
Elinne Becket ◽  
Sameer Chopra ◽  
Christopher E. Duymich ◽  
Justin J. Lin ◽  
Jueng Soo You ◽  
...  

2016 ◽  
Vol 2 (6) ◽  
pp. 608-615 ◽  
Author(s):  
Mansi Parasramka ◽  
Daniel J. Serie ◽  
Yan W. Asmann ◽  
Jeanette E. Eckel-Passow ◽  
Erik P. Castle ◽  
...  

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