scholarly journals Effect of Aberrant Long Noncoding RNA on the Prognosis of Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Han Wu ◽  
Haixiao Wu ◽  
Peng Sun ◽  
Desheng Zhu ◽  
Min Ma ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Noncoding Rna ◽  
Risk Model ◽  
Clear Cell ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis

Clear cell renal cell carcinoma (ccRCC) is a kind of lethal cancer. Although there are mature treatment methods, there is still a lack of rigorous and scientific means for cancer diagnosis. Long noncoding RNAs (lncRNAs) are a kind of noncoding RNA (ncRNA). Recent studies find that alteration of lncRNA expression is related to the occurrence of many cancers. In order to find lncRNAs which can effectively predict the prognosis of ccRCC, RNA-seq count data and clinical information were downloaded from TCGA-KIRC, and gene expression profiles from 530 patients were included. Then, K -means was used for clustering, and the number of clusters was determined to be 5. The R-package “edgeR” was used to perform differential expression analysis. Subsequently, a risk model composed of 10 lncRNA biomarkers significantly related to prognosis was identified via Cox and LASSO regression analyses. Then, patients were divided into two groups according to the model-based risk score, and then, GSEA pathway enrichment was performed. The results showed that metabolism- and mTOR-related pathways were activated while immune-related pathways were inhibited in the high-risk patients. Combined with previous studies, it is believed that these 10 lncRNAs are potential targets for the treatment of ccRCC. In addition, Cox regression analysis was used to verify the independence of the risk model, and as results revealed, the risk model can be used to independently predict the prognosis of patients. In conclusion, our study found 10 lncRNAs related to the prognosis of ccRCC and provided new ideas for clinical diagnosis and drug development.

scholarly journals Identification of Six Potentially Long Noncoding RNAs as Biomarkers Involved Competitive Endogenous RNA in Clear Cell Renal Cell Carcinoma

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Kang Yang ◽  
Xiao-fan Lu ◽  
Peng-cheng Luo ◽  
Jie Zhang
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Expression Profiles ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Cerna Network

Background. Clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma (RCC), usually is representative of metastatic heterogeneous neoplasm that links with poor prognosis, but the pathogenesis of ccRCC remains unclear. Currently, numerous evidences prove that long noncoding RNAs (lncRNAs) are considered as competing endogenous RNA (ceRNA) to participate in cellular processes of tumors. Therefore, to investigate the underlying mechanisms of ccRCC, the expression profiles of lncRNAs, miRNAs, and mRNAs were downloaded from the Cancer Genome Atlas (TCGA) database. A total of 1526 differentially expressed lncRNAs (DElncRNAs), 54 DEmiRNAs, and 2352 DEmRNAs were identified. To determine the connection of them, all DElncRNAs were input to the miRcode database. The results indicated that 85 DElncRNAs could connect with 9 DEmiRNAs in relation to our study. Then, databases of TargetScan and miRDB were used to search for targeted genes with reference to DEmiRNAs. The results showed that 203 out of 2352 targeted genes were identified in our TCGA set. Subsequently, ceRNA network was constructed according to Cytoscape and the targeted genes were functionally analyzed to elucidate the mechanisms of DEmRNAs. The results of survival analysis and regression analysis indicated that 6 DElncRNAs named COL18A1-AS1, WT1-AS, LINC00443, TCL6, AL356356.1, and SLC25A5-AS1 were significantly correlative with the clinical traits of ccRCC patients and could be served as predictors for ccRCC. Finally, these findings were validated by quantitative RT-PCR (qRT-PCR). Based on these discoveries, we believe that this identified ceRNA network will provide a novel perspective to elucidate ccRCC pathogenesis.

scholarly journals Development and Interpretation of a Genomic Instability Derived lncRNAs Based Risk Signature as a Predictor of Prognosis for Clear Cell Renal Cell Carcinoma Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Huiying Yang ◽  
Xiaoling Xiong ◽  
Hua Li
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Genomic Instability ◽  
Renal Cell ◽  
Clear Cell ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Prognosis Prediction

BackgroundClear cell renal cell carcinoma (ccRCC) is a kind of frequently diagnosed cancer, leading to high death rate in patients. Genomic instability (GI) is regarded as playing indispensable roles in tumorigenesis and impacting the prognosis of patients. The aberrant regulation of long non-coding RNAs (lncRNAs) is a main cause of GI. We combined the somatic mutation profiles and expression profiles to identify GI derived lncRNAs (GID-lncRNAs) in ccRCC and developed a GID-lncRNAs based risk signature for prognosis prediction and medication guidance.MethodsWe decided cases with top 25% cumulative number of somatic mutations as genomically unstable (GU) group and last 25% as genomically stable (GS) group, and identified differentially expressed lncRNAs (GID-lncRNAs) between two groups. Then we developed the risk signature with all overall survival related GID-lncRNAs with least absolute shrinkage and selection operator (LASSO) Cox regression. The functions of the GID-lncRNAs were partly interpreted by enrichment analysis. We finally validated the effectiveness of the risk signature in prognosis prediction and medication guidance.ResultsWe developed a seven-lncRNAs (LINC00460, AL139351.1, AC156455.1, AL035446.1, LINC02471, AC022509.2, and LINC01606) risk signature and divided all samples into high-risk and low-risk groups. Patients in high-risk group were in more severe clinicopathologic status (higher tumor grade, pathological stage, T stage, and more metastasis) and were deemed to have less survival time and lower survival rate. The efficacy of prognosis prediction was validated by receiver operating characteristic analysis. Enrichment analysis revealed that the lncRNAs in the risk signature mainly participate in regulation of cell cycle, DNA replication, material metabolism, and other vital biological processes in the tumorigenesis of ccRCC. Moreover, the risk signature could help assess the possibility of response to precise treatments.ConclusionOur study combined the somatic mutation profiles and the expression profiles of ccRCC for the first time and developed a GID-lncRNAs based risk signature for prognosis predicting and therapeutic scheme deciding. We validated the efficacy of the risk signature and partly interpreted the roles of the seven lncRNAs composing the risk signature in ccRCC. Our study provides novel insights into the roles of genomic instability derived lncRNAs in ccRCC.

scholarly journals Long Noncoding RNA HOTTIP Serves as an Independent Predictive Biomarker for the Prognosis of Patients with Clear Cell Renal Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhanxin Liu ◽  
Zichun Wang ◽  
Xiaoxiong Wang ◽  
Meisong Lu ◽  
Guang Chen
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Noncoding Rna ◽  
Clear Cell ◽  
Clinical Stage ◽  
Predictive Biomarker ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Advanced Clinical Stage

Several studies have indicated that HOXA transcript at the distal tip (HOTTIP) play important roles in the tumorigenesis and development of various cancers. We aim to investigate the expression and prognostic value of HOTTIP in clear cell renal cell carcinoma (ccRCC). A systematic review of PubMed, Embase, Medline, and Web of Science databases was performed to select eligible literatures relevant to the correlation between HOTTIP expression and clinical outcome of different cancers. The association between the HOTTIP level and overall survival (OS), lymph node metastasis (LNM), or clinical stage was subsequently analyzed. Survival analyses were performed in a large cohort of more than 500 patients with ccRCC from The Cancer Genome Atlas (TCGA) using bioinformatic methods. Seventeen studies with a total of 1594 patients with thirteen kinds of carcinomas were included in this analysis. The result showed that high HOTTIP expression could predict worse outcome in cancer patients, with the pooled hazard ratio (HR) of 2.34 (95% confidence interval (CI) 1.96–2.79, p<0.0001). The result also showed that elevated HOTTIP expression was correlated with more LNM (OR=2.61, 95% CI 1.91-3.58, p<0.0001) and advanced clinical stage (OR=3.57, 95% CI 2.58-4.93, p<0.0001). We further validated that ccRCC patients with higher HOTTIP expression tend to have unsatisfactory outcomes both in the entire TCGA dataset and different clinical stratums, like age, grade, and stage. The tumor of those patients was associated with a larger size, easier to metastasis, advanced clinical stage, and a higher pathological grade. These findings suggested that increased HOTTIP expression might act as a novel prognostic marker for ccRCC patients.

C121 PROTEIN EXPRESSION PROFILES IN CLEAR CELL RENAL CELL CARCINOMA

2010 ◽  
Vol 9 (6) ◽  
pp. 649 ◽  
Author(s):  
L. Mesarosova ◽  
J. Svihra ◽  
J. Klimas ◽  
P. Krenek ◽  
J. Kyselovic ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Protein Expression ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Expression Profiles ◽  
Cell Renal Cell Carcinoma ◽  
Protein Expression Profiles

scholarly journals Association between visceral and subcutaneous adiposity and clinicopathological outcomes in non-metastatic clear cell renal cell carcinoma

2014 ◽  
Vol 8 (9-10) ◽  
pp. 675 ◽  
Author(s):  
Roy Mano ◽  
A Ari Hakimi ◽  
Emily C Zabor ◽  
Marta A Bury ◽  
Olivio F Donati ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Ct Scans ◽  
Study Cohort ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Pathologic Features ◽  
Subcutaneous Adiposity

Introduction: Visceral adiposity has been inconsistently associated with clinicopathologic features and outcomes of clear cell renal cell carcinoma (ccRCC); however, most studies were conducted in non-Western populations. We evaluated the associations between visceral and subcutaneous adiposity and clinicopathological characteristics of non-metastatic ccRCC patients in a Western population.Methods: The medical records of 220 surgically treated ccRCC patients with documented preoperative body mass index (BMI) and computed tomography (CT) scans were retrospectively reviewed. Nineteen patients with stage IV disease were excluded. Visceral (VFA) and subcutaneous fat area (SFA) were computed from preoperative CT scans. Correlations between obesity measures were assessed with Pearson correlation. Associations between obesity measures and pathologic features were evaluated using logistic regression models adjusted for sex. Overall survival (OS) probabilities were estimated using Cox regression analysis. The log-rank test was used for group comparisons.Results: The study cohort comprised 150 men and 51 women. Women had higher SFA (p = 0.01) but lower VFA (p < 0.001) than men. BMI was highly correlated with SFA (r = 0.804) and moderately correlated with VFA (r = 0.542). SFA and VFA were weakly correlated (r = 0.367). An increased BMI was associated with a better OS (p = 0.028). When adjusting for sex, neither SFA nor VFA was significantly associated with tumour grade, stage, or OS.Conclusions: Consistent with prior reports, our study suggests that increased BMI is associated with a better OS for patient with non-metastatic ccRCC. Despite the high correlation between SFA and BMI, neither SFA nor VFA were significantly associated with tumour stage, grade, or OS in the current study; however, further studies in larger cohorts are required to validate this finding. 

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