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Construction of prostate cancer cell line (PC-3)-specific interactome

ABSTRACT: The purpose of our study was to construct prostate cancer cell-specific interactome by aggregating microarray samples available in public, and identify novel transcriptional regulators that control prostate cancer cell cycle progression. We collected 121 samples of PC-3 cell microarray data from 11 prior studies and our own study data, GSE45567, and performed pre-processing steps, such as quality control test, normalization, and batch effect adjusting. In quality control test, 10 low-quality samples were removed. The matrix data we deposited in GEO has normalized log2 signal intensity of 11,877 genes common in 110 samples, as the 110 samples came from different Affymetrix. The Gene IDs were identified by Entrez Gene IDs that overlapped across different Affymetrix platforms (File: GSE67157_Matrix_PC-3cell_Interactome.txt). In GSE45567 dataset, which is one of the 12 data sets, we selected microarray samples of vehicle-, cineol-, linalool-, and geraniol-treated PC-3 cells, and performed unsupervised clustering analysis to establish dependable clusters of a clear phenotypic transition. Then, the gene set specifically enriched or depleted in the geraniol cluster against vehicle cluster was used for gene set enrichment analysis (GSEA). We found cell cycle-related gene signatures were specifically down-regulated in the geraniol cluster. PC-3 cell-specific interactome was assembled from 110 microarray samples by Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe, PMID: 16723010). We used Master Regulator Analysis-Fisher’s Extact Test (MRA-FET, PMID: 20531406) to infer transcription factors which are geraniol target molecules and control cell cycle gene signatures. We discovered E2F8 is as a master regulator to modulate geraniol-specific genes toward G2/M cell cycle arrest. Our findings will provide biological insights into the role of E2F8 in prostate cancer for transcriptional regulation leading to the development of cell cycle-targeting chemotherapeutic reagent. In addition, our approach serves as an example to decide the most potent anti-cancer regime in other cancer types and identify the target molecules of cancer-preventive reagents through computational analyses.

ORGANISM(S): Homo sapiens

PROVIDER: GSE67157 | GEO | 2016/12/21

REPOSITORIES: GEO

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Project description:BACKGROUND. Human prostate cancer LNCaP and PC-3 cell lines have been extensively used as prostate cancer cell models to study prostate cancer progression and to develop therapeutic agents. Although LNCaP and PC-3 cells are generally assumed to represent early and late stages of prostate cancer development, respectively, there is limited information regarding comprehensive gene expression patterns between these two cells lines and relating these cells to prostate cancer progression based on their gene expression. METHODS. Comprehensive gene expression analysis was performed in LNCaP and PC-3 cells. Total RNA was isolated from cultured cells and hybridized to Illumina human Ref-8 version 3 BeadChips representing 24,526 transcripts. Bioinformatics approach was applied to identify genes, their functional roles and interaction networks that are unique in either LNCaP or PC-3 cells. RESULTS. We observed large differences in gene expression between LNCaP and PC-3 cells.Using robust statistical analysis and very high significance criteria to identify tractable number of genes 115 and 188 genes were identified uniquely expressed in LNCaP and PC-3 cells, respectively. Genes uniquely expressed in LNCaP cells contained UDP-glucosyltransferases as a signature for this cell line. This cell line demonstrated upregulation of various metabolic pathways on gene expression level. Talα/β, GATA-1 and c-Myc/Max were identified by in silico analysis as possible transcription factors regulating unique LNCaP genes. PC-3 cells were characterized by cytosceleton-related genes, keratins in particular. Several other well known genes (VEGFC, IL8, TGFβ2 and others) scattered throughout literature were identified and summarized in the discussion. CONCLUSIONS. This study demonstrated that LNCaP and PC-3 cells represent two distinct prostate cancer cell lineages. LNCaP cells retain many prostate cell specific properties, whereas PC-3 cells have acquired more aggressive bone-like characteristics following bone metastasis and show little resemblance to prostate cells. Microarray studies confirmed previously published results and provided more information between these two prostate cancer cell lines. Future studies need to consider their similarities and differences in gene expression between localized and metastasized prostate cancer.

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Construction of prostate cancer cell line (PC-3)-specific interactome

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