scholarly journals Development and Validation of a Nine-Redox-Related Long Noncoding RNA Signature in Renal Clear Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-30
Author(s):  
Xia Qi-Dong ◽  
Xun Yang ◽  
Jun-Lin Lu ◽  
Chen-Qian Liu ◽  
Jian-Xuan Sun ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Cox Regression ◽  
Clear Cell ◽  
Test Group ◽  
Training Group ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature

Background. Redox plays an essential role in the pathogeneses and progression of tumors, which could be regulated by long noncoding RNA (lncRNA). We aimed to develop and verify a novel redox-related lncRNA-based prognostic signature for clear cell renal cell carcinoma (ccRCC). Materials and Methods. A total of 530 ccRCC patients from The Cancer Genome Atlas (TCGA) were included in this study. All the samples were randomly split into training and test group at a 1 : 1 ratio. Then, we screened differentially expressed redox-related lncRNAs and constructed a novel prognostic signature from the training group using the least absolute shrinkage and selection operation (LASSO) and COX regression. Next, to verify the accuracy of the signature, we conducted risk and survival analysis, as well as the construction of ROC curve, nomogram, and calibration curves in the training group, test group, and all samples. Finally, the redox gene-redox-related lncRNA interaction network was constructed, and gene set enrichment analysis (GSEA) was performed to investigate the status of redox-related functions between high/low-risk groups. Results. A nine-redox-related lncRNA signature consisted of AC025580.3, COLCA1, AC027601.2, DLEU2, AC004918.3, AP006621.2, AL031670.1, SPINT1-AS1, and LAMA5-AS1 was significantly associated with overall survival in ccRCC patients. The signature proved efficient, and thus, a nomogram was successfully assembled. In addition, the GSEA results demonstrated that two major redox-related functions were enhanced in the high-risk group ccRCC patients. Conclusions. Our findings robustly demonstrate that the nine-redox-related lncRNA signature could serve as an efficient prognostic indicator for ccRCC.

GALNT14 expression in renal clear cell carcinoma and its effect on prognosis

2021 ◽  
Author(s):  
Yuqin Wei ◽  
Fan Wu ◽  
Shengfeng Zhang ◽  
Yanlin Tan ◽  
Qunying Wu ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Cox Regression ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Regulatory Pathways ◽  
Cox Analysis ◽  
The Relationship

Abstract Background The expression of GALNT14 in kidney renal clear cell carcinoma (KIRC) and its clinical significance remains unknown. Methods The KIRC data expressed by GALNT14 was downloaded from The Cancer Genome Atlas (TCGA) database. The expression of GALNT14 was analyzed by R software, Perl software and online analysis database. The relationship between GALNT14 expression and clinicopathological features in KIRC was analyzed by univariate, multivariate Cox regression and some databases. Gene Expression Profling Interactive Analysis (GEPIA), Starbase v3.0, UALCAN, and Kaplan-Meier were used to analyze the relationship between GALNT14 expression and overall survival (OS) in KIRC. UALCAN detects the expression of GALNT14 methylation in KIRC. Linkedomics and Genemania were used to analyze the gene co-expression of GALNT14. Gene Set Enrichment Analysis (GSEA) was performed to search for potential regulatory pathways. Results We found that GALNT14 was overexpressed in KIRC (p=1.433e-25). Patients with high GALNT14 expression in KIRC had a better prognosis than patients with low GALNT14 expression (p=0.008). In addition, high GALNT14 expression in KIRC was significantly associated with low T stage and positive OS (p<0.05). Univariate Cox analysis showed that GALNT14 was positively correlated with OS (p<0.001). Multivariate Cox analysis showed that GALNT14 was associated with OS (p<0.001), age (p=0.01) and histological grade (p=0.02). GALNT14 methylation is low expressed in KIRC (p<0.001). GSEA analysis showed that GALNT14 was enriched in histidine metabolism, peroxisome, and renin-angiotensin system pathways. Conclusion GALNT14 can be used as an independent prognostic factor for renal clear cell carcinoma and a potential target for clinical diagnosis and treatment of KIRC.

scholarly journals N6-Methyladenosine-Related Long Non-coding RNA Signature Associated With Prognosis and Immunotherapeutic Efficacy of Clear-Cell Renal Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Tianming Ma ◽  
Xiaonan Wang ◽  
Jiawen Wang ◽  
Xiaodong Liu ◽  
Shicong Lai ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differential Expression ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis

Increasing evidence suggests that N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) play important roles in cancer progression and immunotherapeutic efficacy in clear-cell renal cell carcinoma (ccRCC). In this study, we conducted a comprehensive ccRCC RNA-seq analysis using The Cancer Genome Atlas data to establish an m6A-related lncRNA prognostic signature (m6A-RLPS) for ccRCC. Forty-four prognostic m6A-related lncRNAs (m6A-RLs) were screened using Pearson correlation analysis (|R| &gt; 0.7, p &lt; 0.001) and univariable Cox regression analysis (p &lt; 0.01). Using consensus clustering, the patients were divided into two clusters with different overall survival (OS) rates and immune status according to the differential expression of the lncRNAs. Gene set enrichment analysis corroborated that the clusters were enriched in immune-related activities. Twelve prognostic m6A-RLs were selected and used to construct the m6A-RLPS through least absolute shrinkage and selection operator Cox regression. We validated the differential expression of the 12 lncRNAs between tumor and non-cancerous samples, and the expression levels of four m6A-RLs were further validated using Gene Expression Omnibus data and Lnc2Cancer 3.0 database. The m6A-RLPS was verified to be an independent and robust predictor of ccRCC prognosis using univariable and multivariable Cox regression analyses. A nomogram based on age, tumor grade, clinical stage, and m6A-RLPS was generated and showed high accuracy and reliability at predicting the OS of patients with ccRCC. The prognostic signature was found to be strongly correlated to tumor-infiltrating immune cells and immune checkpoint expression. In conclusion, we established a novel m6A-RLPS with a favorable prognostic value for patients with ccRCC. The 12 m6A-RLs included in the signature may provide new insights into the tumorigenesis and allow the prediction of the treatment response of ccRCC.

scholarly journals Prognostic Signature for Lung Adenocarcinoma Patients Based on Cell-Cycle-Related Genes

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Jiang ◽  
Jiameng Xu ◽  
Zirui Liao ◽  
Guangbin Li ◽  
Chengpeng Zhang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Training Group ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
External Test

ObjectiveTo screen lung adenocarcinoma (LUAC)-specific cell-cycle-related genes (CCRGs) and develop a prognostic signature for patients with LUAC.MethodsThe GSE68465, GSE42127, and GSE30219 data sets were downloaded from the GEO database. Single-sample gene set enrichment analysis was used to calculate the cell cycle enrichment of each sample in GSE68465 to identify CCRGs in LUAC. The differential CCRGs compared with LUAC data from The Cancer Genome Atlas were determined. The genetic data from GSE68465 were divided into an internal training group and a test group at a ratio of 1:1, and GSE42127 and GSE30219 were defined as external test groups. In addition, we combined LASSO (least absolute shrinkage and selection operator) and Cox regression analysis with the clinical information of the internal training group to construct a CCRG risk scoring model. Samples were divided into high- and low-risk groups according to the resulting risk values, and internal and external test sets were used to prove the validity of the signature. A nomogram evaluation model was used to predict prognosis. The CPTAC and HPA databases were chosen to verify the protein expression of CCRGs.ResultsWe identified 10 LUAC-specific CCRGs (PKMYT1, ETF1, ECT2, BUB1B, RECQL4, TFRC, COCH, TUBB2B, PITX1, and CDC6) and constructed a model using the internal training group. Based on this model, LUAC patients were divided into high- and low-risk groups for further validation. Time-dependent receiver operating characteristic and Cox regression analyses suggested that the signature could precisely predict the prognosis of LUAC patients. Results obtained with CPTAC, HPA, and IHC supported significant dysregulation of these CCRGs in LUAC tissues.ConclusionThis prognostic prediction signature based on CCRGs could help to evaluate the prognosis of LUAC patients. The 10 LUAC-specific CCRGs could be used as prognostic markers of LUAC.

scholarly journals A novel 10 glycolysis-related genes signature could predict overall survival for clear cell renal cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qianwei Xing ◽  
Tengyue Zeng ◽  
Shouyong Liu ◽  
Hong Cheng ◽  
Limin Ma ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Regression Analyses ◽  
Cell Renal Cell Carcinoma

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.

scholarly journals An angiogenesis-related long noncoding RNA signature correlates with prognosis in patients with hepatocellular carcinoma

2021 ◽  
Vol 41 (4) ◽  
Author(s):  
Dengliang Lei ◽  
Yue Chen ◽  
Yang Zhou ◽  
Gangli Hu ◽  
Fang Luo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Roc Curves ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Highly Correlated

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal cancers worldwide. Neovascularization is closely related to the malignancy of tumors. We constructed a signature of angiogenesis-related long noncoding RNA (lncRNA) to predict the prognosis of patients with HCC. The lncRNA expression matrix of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA). First, gene set enrichment analysis (GSEA) was used to distinguish the differentially expressed genes of the angiogenesis genes in liver cancer and adjacent tissues. Next, a signature of angiogenesis-related lncRNAs was constructed using univariate and multivariate analyses, and receiver operating characteristic (ROC) curves were used to assess the accuracy. The signature and relevant clinical information were used to construct the nomogram. A 5-lncRNA signature was highly correlated with overall survival (OS) in HCC patients and performed well in evaluations using the C-index, areas under the curve, and calibration curves. In summary, the 5-lncRNA model can serve as an accurate signature to predict the prognosis of patients with liver cancer, but its mechanism of action must be further elucidated by experiments.

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.

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