Xingliang Feng^*1, Meng Zhang^*†1, Jialin Meng^*, Yongqiang Wang^†, Yi Liu^*, Chaozhao Liang^*, Song Fan^*

Oncology Research, Vol.28, No.3, pp. 285-297, 2020, DOI:10.3727/096504020X15791676105394

Abstract We aimed to investigate the potential mechanisms of progression and identify novel prognosis-related biomarkers for papillary renal cell carcinoma (PRCC) patients. The related data were derived from The Cancer Genome Atlas (TCGA) and then analyzed by weighted gene coexpression network analysis (WGCNA). The correlation between each module and the clinical traits were analyzed by Pearson’s correlation analysis. Pathway analysis was conducted to reveal potential mechanisms. Hub genes within each module were screened by intramodule analysis, and visualized by Cytoscape software. Furthermore, important hub genes were validated in an external dataset and clinical samples. A total of 5,839 differentially expressed genes… More >

Mian LIU¹, Xumeng ZHANG^{2, *}

BIOCELL, Vol.41, No.1, pp. 19-26, 2017, DOI:10.32604/biocell.2017.41.019

Abstract Bladder, kidney, prostate and testicular carcinoma are the top four genitourinary cancers in China. Here we analyzed mRNA and miRNA expression profiles of carcinomas of the bladder (TCC), kidney (ccRCC) and testis (TGCT) to uncover their specific regulatory mechanisms. The gene expression profiles of GSE31617 were downloaded from GEO database, which contained 27 samples, including 10 TCC, 7 TGCT and 10 ccRCC. Specific up- and downregulated differentially expressed genes (DEGs) and differentially expressed microRNAs (DEmiRNAs) of each cancer were selected and target genes of DEmiRNAs were predicted. Gene interaction network of the shared genes and target genes of DEmiRNAs of… More >