Dataset Information

Investigation of the molecular mechanisms underlying metastasis in prostate cancer by gene expression profiling.

ABSTRACT: The present study aimed to screen potential genes associated with metastatic prostate cancer (PCa), in order to improve the understanding of the mechanisms underlying PCa metastasis. The GSE3325 microarray dataset, which was downloaded from the Gene Expression Omnibus database, consists of seven clinically localized PCa samples, six hormone-refractory metastatic PCa samples and six benign prostate tissue samples. The Linear Models for Microarray Data package was used to identify differentially-expressed genes (DEGs) and a hierarchical cluster analysis for DEGs was performed with the pheatmap package. Furthermore, potential functions for the DEGs were predicted by a functional enrichment analysis. Subsequently, microRNAs (miRNAs) potentially involved in the regulation of PCa metastasis were identified by WebGestalt software, and the miRNA-DEG regulatory network was visualized using Cytoscape. In addition, a pathway enrichment analysis for DEGs in the regulatory network was performed. A total of 306 and 2,073 genes were differentially expressed in the clinically localized PCa and the metastatic PCa groups, respectively, as compared with the benign prostate group, of which 174 were differentially expressed in both groups. A number of the DEGs, including CAMK2D and SH3BP4, were significantly enriched in the cell cycle, and others, such as MAF, were associated with the regulation of cell proliferation. Furthermore, some DEGs (CAMK2D and PCDH17) were observed to be regulated by miR-30, whereas others (ADCY2, MAF, SH3BP4 and PCDH17) were modulated by miR-182. Additionally, ADCY2 and CAMK2D were distinctly enriched in the calcium signaling pathway. The present study identified novel DEGs, including ADCY2, CAMK2D, MAF, SH3BP4 and PCDH17, that may be involved in the metastasis of PCa.

SUBMITTER: Zhang X

PROVIDER: S-EPMC4950782 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Investigation of the molecular mechanisms underlying metastasis in prostate cancer by gene expression profiling.

Zhang Xinghua X Yao Xiaoli X Qin Cong C Luo Pengcheng P Zhang Jie J

Experimental and therapeutic medicine 20160520 2

The present study aimed to screen potential genes associated with metastatic prostate cancer (PCa), in order to improve the understanding of the mechanisms underlying PCa metastasis. The GSE3325 microarray dataset, which was downloaded from the Gene Expression Omnibus database, consists of seven clinically localized PCa samples, six hormone-refractory metastatic PCa samples and six benign prostate tissue samples. The Linear Models for Microarray Data package was used to identify differentially-e ...[more]

PMID: 27446297

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Project description:Metastasis is the main cause of breast cancer‑related mortalities. The present study aimed to uncover the relevant molecular mechanisms of breast cancer metastasis and to explore potential biomarkers that may be used for prognosis. Expression profile microarray data GSE8977, which contained 22 stroma samples (15 were from normal breast and 7 were from invasive ductal carcinoma tumor samples), were obtained from the Gene Expression Omnibus database. Following data preprocessing, differentially expressed genes (DEGs) were selected based on analyses conducted using the linear models for microarray analysis package from R and Bioconductor software. The resulting data were used in subsequent function and pathway enrichment analyses, as well as protein‑protein interaction (PPI) network and subnetwork analyses. Transcription factors (TFs) and tumor‑associated genes were also identified among the DEGs. A total of 234 DEGs were identified, which were enriched in immune response, cell differentiation and cell adhesion‑related functions and pathways. Downregulated DEGs included TFs, such as the proto‑oncogene SPI1, pre‑B‑cell leukemia homeobox 3 (PBX3) and lymphoid enhancer‑binding factor 1 (LEF1), as well as tumor suppressors (TSs), such as capping actin protein, gelsolin like (CAPG) and tumor protein p53‑inducible nuclear protein 1 (TP53INP1). Upregulated DEGs also included TFs and tumor suppressors, consisting of transcription factor 7‑like 2 (TCF7L2) and pleiomorphic adenoma gene‑like 1 (PLAGL1). DEGs that were identified at the hub nodes in the PPI network and the subnetwork were epidermal growth factor receptor (EGFR) and spleen‑associated tyrosine kinase (SYK), respectively. Several genes crucial in the metastasis of breast cancer were identified, which may serve as potential biomarkers, many of which were associated with cell adhesion, proliferation or immune response, and may influence breast cancer metastasis by regulating these function or pathways.

Dataset Information

Investigation of the molecular mechanisms underlying metastasis in prostate cancer by gene expression profiling.

Publications

Investigation of the molecular mechanisms underlying metastasis in prostate cancer by gene expression profiling.

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