Identification of Key Genes and Pathways in Renal Cell Carcinoma Through Expression Profiling Data

Liu, Xiaoxia; Wang, Jinling; Sun, Guiling

doi:10.1159/000368504

Cited by 42 publications

(33 citation statements)

References 46 publications

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“…GNAO1 was significantly enriched in circadian entrainment, glutamatergic synapse, morphine addiction, melanogenesis, retrograde endocannabinoid signaling and cholinergic synapse pathways. A number of articles have illuminated its biological roles in cancers including hepatocellular carcinoma (HCC), gastric cancer and renal cell carcinoma [31–33]. In HCC, GNAO1 acts as tumor suppressor depending on down-regulation of GNAO1 promoting cell proliferation and suppressing the senescence of HCC cells [31].…”

Section: Discussionmentioning

confidence: 99%

Abnormal expression of mRNA, microRNA alteration and aberrant DNA methylation patterns in rectal adenocarcinoma

Yang

Liu

et al. 2017

PLoS ONE

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AimRectal adenocarcinoma (READ) is a malignancy cancer with the high morbidity and motility worldwide. Our study aimed to explore the potential pathogenesis of READ through integrated analysis of gene expression profiling and DNA methylation data.MethodsThe miRNA, mRNA expression profiling and corresponding DNA methylation data were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs/ miRNAs/methylated regions (DEmRNA/DEmiRNAs) were identified in READ. The negatively correlation of DEmiRNA-DEmRNAs and DNA methylation-DEmRNAs were obtained. DEmRNAs expression was validated through quantitative real-time polymerase chain reaction (qRT-PCR) and microarray expression profiling analyses.Results1192 dysregulated DEmRNAs, 27 dysregulated DEmiRNAs and 6403 aberrant methylation CpG sites were screened in READ compared to normal controls. 1987 negative interaction pairs among 27 DEmiRNAs and 668 DEmRNAs were predicted. 446 genes with aberrant methylation were annotated. Eventually, 50 DEmRNAs (39 down- and 11 up-regulated DEmRNAs) with hypermethylation, synchronously negatively targeted by DEmiRNAs, were identified through the correlation analysis among 446 genes with aberrant methylation and 668 DEmRNAs. 50 DEmRNAs were significantly enriched in cAMP signaling pathway, circadian entrainment and glutamatergic synapse. The validation results of expression levels of DEmRNAs through qRT-PCR and microarray analyses were compatible with our study.Conclusion7 genes of SORCS1, PDZRN4, LONRF2, CNGA3, HAND2, RSPO2 and GNAO1 with hypermethylation and negatively regulation by DEmiRNAs might contribute to the tumorigenesis of READ. Our work might provide valuable foundation for the READ in mechanism elucidation, early diagnosis and therapeutic target identification.

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Section: Discussionmentioning

confidence: 99%

Abnormal expression of mRNA, microRNA alteration and aberrant DNA methylation patterns in rectal adenocarcinoma

Yang

Liu

et al. 2017

PLoS ONE

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“…Previous studies have focused on the identification of differentially expressed genes, which may serve roles in the pathogenesis of KIRC (10,11). The present study performed a gene co-expression network analysis and a survival analysis on RNA-seq data in order to screen out prognostic genes in KIRC.…”

Section: Introductionmentioning

confidence: 99%

Identification of prognostic genes in kidney renal clear cell carcinoma by RNA-seq data analysis

et al. 2017

Molecular Medicine Reports

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The present study aimed to analyze RNA-seq data of kidney renal clear cell carcinoma (KIRC) to identify prognostic genes. RNA-seq data were downloaded from The Cancer Genome Atlas. Feature genes with a coefficient of variation (CV) >0.5 were selected using the genefilter package in R. Gene co-expression networks were constructed with the WGCNA package. Cox regression analysis was performed using the survive package. Furthermore, a functional enrichment analysis was conducted using Database for Annotation, Visualization and Integrated Discovery tools. A total of 533 KIRC samples were collected, from which 6,758 feature genes with a CV >0.5 were obtained for further analysis. The KIRC samples were divided into two sets: The training set (n=319 samples) and the validation set (n=214 samples). Subsequently, gene co-expression networks were constructed for the two sets. A total of 12 modules were identified, and the green module was significantly associated with survival time. Genes from the green module were revealed to be implicated in the cell cycle and p53 signaling pathway. In addition, a total of 11 hub genes were revealed, and 10 of them (CCNA2, CDC20, CDCA8, GTSE1, KIF23, KIF2C, KIF4A, MELK, TOP2A and TPX2) were validated as possessing prognostic value, as determined by conducting a survival analysis on another gene expression dataset. In conclusion, a total of 10 prognostic genes were identified in KIRC. These findings may help to advance the understanding of this disease, and may also provide potential biomarkers for therapeutic development.

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“…Given that the prediction softwares often suffer from high false positive rates [35-38], only target genes predicted by all three independent tools were taken in to the account.…”

Section: Resultsmentioning

confidence: 99%

“…According to previous reports, the proportion of correct predictions can be as low as 10% [35-38]. To increase the accuracy of bioinformatics’ predictions, mRNA expression profiling was done simultaneously.…”

Section: Resultsmentioning

confidence: 99%

MiRNA and mRNA Profiling in Systemic Lupus Reveals a Novel Set of Cytokine - Related miRNAs and their Target Genes in Cases With and Without Renal Involvement

Ghods

Sarikaya

Arda

et al. 2017

Kidney Blood Press Res

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Background/Aims: MiRNAs transpire as promising elements in molecular medicine for the identification of new diagnostic, prognostic and targeting therapeutic biomarkers. This study consisted of four steps: First, to investigate one or a group of specific diagnostic miRNAs for Systemic Lupus Erythematosus (SLE) disease in patients with and without renal involvement, second, to identify cytokines genes’ expression profiling, third, comparing the profiles with related amounts in the serum and finally, to study target-gene-mediated functional roles of miRNAs, which have been correlated to disease development and progression. Methods: In order to use in microarray assays total RNA and miRNAs were isolated from blood and serum samples that were obtained from 16 SLE patients (9 with renal involvement and 7 without renal involvement). Taking coexistence of factors such as hypocomplementemia, positive ANA and anti-DNA into account, obtained data were processed. For each differentially expressed miRNA, potential target genes were predicted by microRNAorg, TargetScan and PITA prediction tools. Obtained mRNA profiling data were interrogated for the target genes. MiRNA and mRNA microarray results were confirmed by QRT-PCR. Finally, the amounts of cytokines were measured by multiplex ELISA method. Results: The results of study showed that among differentially expressed miRNAs in SLE patients with renal involvement compared to those without renal involvement, hsa-miR-766-3p, may play pivotal roles in PI3K-AKT-mTOR pathway. In addition according to the obtained data it is suggested that blood-borne proinflammatory cytokines such as IL-4, IL-6 and TNF-α alongside with disease stage and severity may contribute to this differential expression of these miRNA which may be leading to insulin resistance. Finally, hsa-miR-621, which was differentially expressed in hypertensive SLE patients without renal involvement and a positive ANA test with its predicted target gene “Kallikrein-related peptidase 9” may play a role in the pathophysiology of hypertension in SLE. Conclusions: We reported some human miRNAs which were differentially expressed in SLE patients according to disease activity and renal involvement. Larger studies are necessary to confirm our findings and detect further biomarkers.

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Identification of Key Genes and Pathways in Renal Cell Carcinoma Through Expression Profiling Data

Cited by 42 publications

References 46 publications

Abnormal expression of mRNA, microRNA alteration and aberrant DNA methylation patterns in rectal adenocarcinoma

Abnormal expression of mRNA, microRNA alteration and aberrant DNA methylation patterns in rectal adenocarcinoma

Identification of prognostic genes in kidney renal clear cell carcinoma by RNA-seq data analysis

MiRNA and mRNA Profiling in Systemic Lupus Reveals a Novel Set of Cytokine - Related miRNAs and their Target Genes in Cases With and Without Renal Involvement

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