scholarly journals Identification of novel differentially expressed lncRNA and mRNA transcripts in clear cell renal cell carcinoma by expression profiling

Genomics Data ◽  
2015 ◽  
Vol 5 ◽  
pp. 173-175 ◽  
Author(s):  
Mario Deng ◽  
Jasmine J. Blondeau ◽  
Doris Schmidt ◽  
Sven Perner ◽  
Stefan C. Müller ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Expression Profiling ◽  
Renal Cell ◽  
Clear Cell ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma ◽  
Mrna Transcripts

scholarly journals Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8096 ◽  
Author(s):  
Haiping Zhang ◽  
Jian Zou ◽  
Ying Yin ◽  
Bo Zhang ◽  
Yaling Hu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Clear Cell ◽  
Clinical Stage ◽  
Stage I ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.

Proteomic analysis in clear cell renal cell carcinoma: identification of differentially expressed protein by 2-D DIGE

2012 ◽  
Vol 8 (4) ◽  
pp. 1040 ◽  
Author(s):  
Francesca Raimondo ◽  
Claudia Salemi ◽  
Clizia Chinello ◽  
Daniela Fumagalli ◽  
Lavinia Morosi ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Proteomic Analysis ◽  
Renal Cell ◽  
Clear Cell ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma ◽  
Differentially Expressed Protein

scholarly journals Transcription Factors BARX1 and DLX4 Contribute to Progression of Clear Cell Renal Cell Carcinoma via Promoting Proliferation and Epithelial–Mesenchymal Transition

2021 ◽  
Vol 8 ◽  
Author(s):  
Guoliang Sun ◽  
Yue Ge ◽  
Yangjun Zhang ◽  
Libin Yan ◽  
Xiaoliang Wu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Transcription Factors ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Epithelial Mesenchymal Transition ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma ◽  
Mesenchymal Transition

Dysregulation of transcription factors contributes to the carcinogenesis and progression of cancers. However, their roles in clear cell renal cell carcinoma remain largely unknown. This study aimed to evaluate the clinical significance of TFs and investigate their potential molecular mechanisms in ccRCC. Data were accessed from the cancer genome atlas kidney clear cell carcinoma cohort. Bioinformatics algorithm was used in copy number alterations mutations, and differentially expressed TFs’ analysis. Univariate and multivariate Cox regression analyses were performed to identify clinically significant TFs and construct a six-TF prognostic panel. TFs’ expression was validated in human tissues. Gene set enrichment analysis (GSEA) was utilized to find enriched cancer hallmark pathways. Functional experiments were conducted to verify the cancer-promoting effect of BARX homeobox 1 (BARX1) and distal-less homeobox 4 (DLX4) in ccRCC, and Western blot was performed to explore their downstream pathways. As for results, many CNAs and mutations were identified in transcription factor genes. TFs were differentially expressed in ccRCC. An applicable predictive panel of six-TF genes was constructed to predict the overall survival for ccRCC patients, and its diagnostic efficiency was evaluated by the area under the curve (AUC). BARX1 and DLX4 were associated with poor prognosis, and they could promote the proliferation and migration of ccRCC. In conclusion, the six-TF panel can be used as a prognostic biomarker for ccRCC patients. BARX1 and DLX4 play oncogenic roles in ccRCC via promoting proliferation and epithelial–mesenchymal transition. They have the potential to be novel therapeutic targets for ccRCC.

scholarly journals Genome-Wide Analysis of Differentially Expressed Genes and Splicing Isoforms in Clear Cell Renal Cell Carcinoma

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e78452 ◽  
Author(s):  
Alessio Valletti ◽  
Margherita Gigante ◽  
Orazio Palumbo ◽  
Massimo Carella ◽  
Chiara Divella ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Renal Cell ◽  
Clear Cell ◽  
Differentially Expressed ◽  
Cell Renal Cell Carcinoma ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Splicing Isoforms

scholarly journals Kinase Gene Expression Profiling of Metastatic Clear Cell Renal Cell Carcinoma Tissue Identifies Potential New Therapeutic Targets

PLoS ONE ◽  
2016 ◽  
Vol 11 (8) ◽  
pp. e0160924 ◽  
Author(s):  
Pooja Ghatalia ◽  
Eddy S. Yang ◽  
Brittany N. Lasseigne ◽  
Ryne C. Ramaker ◽  
Sara J. Cooper ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Expression Profiling ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Kinase Gene ◽  
Carcinoma Tissue ◽  
Renal Cell Carcinoma Tissue
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