Identification of Core Genes and Key Pathways via Integrated Analysis of Gene Expression and DNA Methylation Profiles in Bladder Cancer

Abstract

BackgroundBladder cancer (BC) is the most common urological malignant tumor. In BC, aberrant DNA methylation is believed to be associated with carcinogenesis. Therefore, the identification of key genes and pathways could help determine the potential molecular mechanisms of BC development.Material/MethodsMicroarray data on gene expression and gene methylation were downloaded from the Gene Expression Omnibus (GEO) database. Abnormal methylated/expressed genes were analyzed by GEO2R and statistical software R. Gene Ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID database and KOBAS 3.0. STRING and Cytoscape software were used to construct protein–protein interaction (PPI) networks and analyze modules of the PPI network.ResultsA total of 71 hypomethylated/upregulated genes were significantly enriched in cell–cell adhesion and blood vessel development. KEGG pathway analysis highlighted p53 signaling and metabolic pathways. Five core genes in the PPI network were determined: CDH1, DDOST, CASP8, DHX15, and PTPRF. Additionally, 89 hypermethylated/downregulated genes were found. These genes were enriched mostly in cell adhesion and signal transduction. KEGG pathway analysis revealed enrichment in focal adhesion. The top 5 core genes in the PPI network were GNG4, ADCY9, NPY, ADRA2B, and PENK. We found most of the core genes were also significantly altered in the Cancer Genome Atlas database.ConclusionsAbnormal methylated/expressed genes and key signaling pathways involved in BC were identified through integrated bioinformatics analysis. In the future, these genes may serve as biomarkers for diagnosis and therapeutic targets in BC.

Immune and Stroma Related Genes in Breast Cancer: A Comprehensive Analysis of Tumor Microenvironment Based on the Cancer Genome Atlas (TCGA) Database

“…PENK and PNOC, precursor proteins of enkephalin and nociceptin, respectively, are highly expressed genes in the central neuron system as transmitters to opioid receptor and commonly work in pain transmission and perception. However, the promoter hypermethylation of PENK has been indicated in several malignancies including bladder cancer (54,55), colorectal cancer (56) and pancreatic cells (57,58). In researches, PENK has been reported to be required for apoptosis induction in response to activation or overexpression of p53 and p65 through NF kappa B signaling pathway (59), which is a pathway that is activated in inflammation and enriched in our functional analysis.…”

PENK inhibits osteosarcoma cell migration by activating the PI3K/Akt signaling pathway

“…The concentration and purity of total RNA was determined by measuring the absorbance at 260 and 280 nm (A260/A280). Single-strand cDNA was synthesized by reverse transcription with a Superscript II Reverse Transcriptase Kit and oligo dT (12)(13)(14)(15)(16)(17)(18) primers (Invitrogen, Carlsbad, CA, USA) and amplified by RT-PCR with iQ SYBR Green Supermix (Bio-Rad, Hercules, CA, USA). Quantitative PCR (qPCR) was performed using SYBR Green PCR Master Mix (Applied Biosystems) following the manufacturer's instructions.…”

“…Proenkephalin (PENK) was originally shown to be expressed in the mature nervous and neuroendocrine systems through the opioid pathway and to be involved in the regulation of cell death and survival [10]. PENK has been identified as a key gene in multiple types of cancers [11][12][13].…”

Bioinformatics Analysis Identifying Key Biomarkers in Bladder Cancer

“…We retrieved seven bioinformatics studies for BCa biomarkers based on public database analyses [9,[29][30][31][32][33][34], and we compared the biomarkers in the present study with the ones that were reported in the literature studies. We found that CRYAB and CASQ2 were so far unrecognized as biomarkers in previous studies.…”

“…The data collection process was undertaken and ended in November 2019. The retrieval criteria were rigorous, filtering with bioinformatics analysis and BCa, only 7 full-text papers were returned [9,[29][30][31][32][33][34]. On the basis of Oncomine database, 5 studies were relevant [35] and we gathered the information of the 14 hub genes from the 5 previous studies.…”