Genome-wide analysis of gene expression patterns in human prostate cancer (PCa)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE69223 | GEO | 2018/04/22
REPOSITORIES: GEO
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Project description:Prostate cancer (PCa) causes significant mortality among men worldwide. Galectin-4 plays an important roles in regulatiog cancer metastasis and high level of galectin-4 correlated with poor survival in subpopulation of PCa patients. To further understand the galectin-4-mediated signature and develop effective treatment, we froced expressed galectin-4 in 22Rv1 and LNCaP cells, and downregulated galectin-4 in 22Rv1-M4 cells. Next, cDNA microarray were applyed to study galectin-4-mediated gene expression and cancer progression.
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Project description:Copy number variations (CNVs) in the human genome have been linked to various carcinomas including prostate cancer (PCa). This study was conducted to identify CNVs in high grade PCa. We performed a pilot genome-wide CNV analysis in 36 subjects (18 high grade PCa and 18 benign prostatic hyperplasia) using array comparative genomic hybridization (aCGH) technique. Array results were validated using PCR-based copy number counting method. A total of 339 CNV regions were found to be unique to PCa subjects in this cohort (P < 0.05). Data segregation and filtering revealed six putative CNV loci associated with susceptibility to PCa. Of these, four were rare (1q21.3, 15q15, 3q27.2 and 7p12.1) and one was a novel copy number gain (12q23.1), harbouring genes such as the ARNT, THBS1, SLC5A8 and DDC which are crucial in the p53 and cancer pathways. Another CNV was a loss at 8p11.21 which contains the SFRP1 gene from the Wnt signalling pathway, known for its interaction with androgen receptors as reported for urological malignancy. Cross comparison analysis with genes already known to be associated with PCa revealed significant CNVs involved in crucial biological processes that elicit cancer pathogenesis via cytokine production, disease progression through endothelial cell proliferation and xenobiotic metabolism. In conclusion, these findings suggest that the CNV regions identified could provide an insight into the development of high grade PCa.
2018-12-18 | GSE79402 | GEO
Project description:An integrated transcriptome-wide gene expression analysis, including differential gene expression analysis and weighted gene co-expression network analysis (WGCNA), was carried out based on transcriptomics data from a series of nine matched, histologically confirmed PCa and benign samples using the Affymetrix Clariom D Human array. The analysis identified a set of potential gene markers highly associated with tumor status (malignant vs. benign). We then used these genes to establish a minimal progression-free survival (PFS)-associated gene signature (GS) (PCBP1, PABPN1, PTPRF, DANCR, and MYC) using the least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analyses from The Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD) dataset. Our signature was able to predict PFS over 1, 3, and 5 years in the TCGA-PRAD dataset, with an area under the curve (AUC) of 0.64–0.78, and our signature remained as a prognostic factor independent of age, Gleason score, and pathological T and N stages. A nomogram combining the signature and Gleason score demonstrated improved predictive capability for PFS (AUC: 0.71–0.85) and was superior to the Cambridge Prognostic Group (CPG) model alone and some conventionally used clinicopathological factors in predicting PFS. In conclusion, we have identified and validated a novel five-gene signature and established a nomogram that effectively predicted PFS in patients with PCa. These findings may improve current prognostic tools for PFS and contribute to clinical decision-making in PCa treatment.
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Project description:African American (AA) men have a significantly higher mortality rate from prostate cancer (PCa) compared to European American (EA) men. AA men are twice as likely to die from PCa compared to EA men and 8 times as likely as Asian American men to die from PCa. The biological basis for these differences in PCa mortality are unclear. We carried out Copy Number Alteration (CNA) studies on a new set of 40 highly tumor-enriched primary PCas and matched benign prostate tissues from AA men using high resolution Affymetrix 6.0 SNP arrays and expression array analysis using RNAs (GSE71016) from the same tissues using high purity tumors from AA men and matched benign tissue. We have confirmed the specific loss of 4p16.3 described previously and identified a novel tumor suppressor gene, RGS12 at this locus that shows significantly decreased expression in AA PCa but not EA EA PCa.
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2014-03-18 | E-GEOD-55945 | biostudies-arrayexpress
Project description:Prognostic biomarkers are useful to screen patients with clinically localized prostate cancer (PCa) who are at high risk of metastatic progression. The tumor transcriptome can be used to evaluate the aggressiveness of PCa and predict adverse patient outcomes. Genomewide gene expression levels were measured in primary tumor samples of 503 patients in a population‐based cohort.
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Project description:Investigation of miRNA expression profiles of prostate cancer (PCa) and normal prostatic samples
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Project description:Prostate cancer (PCa) remains a prevalent and deadly disease. The histology-based Gleason score (GS) of PCa tissue biopsy is the most accurate predictor of disease aggressiveness and an important measure to guide decision-making with respect to treatment strategies and patient management. However, inherent variability associated with PCa tumour sampling and the subjective determination of the GS are still key challenges precluding accurate diagnostication and prognostication. Thus, novel molecular signatures are urgently needed to distinguish between indolent and aggressive forms of PCa for better patient management and outcomes. Herein, we have used label-free LC-MS/MS-based proteomics to profile the proteome of 50 PCa tissues spanning five GS-based PCa grades (n = 10 per group) relative to five tissues from individuals with benign prostatic hyperplasia (BPH). Over 2,000 proteins were consistently identified albeit at different levels between and within the patient groups, revealing biological processes associated with specific grades. Excitingly, a panel of 11 prostate-derived proteins including IGKV3D-20, RNASET2, TACC2, ANXA7, LMOD1, PRCP, GYG1, NDUFV1, H1FX, APOBEC3C, CTSZ displayed the potential to accurately stratify patients displaying low and high GS. This is the first study to characterise the prostate tissue proteome signatures of the five PCa grades relative to BPH. We report a panel of proteins that accurately can distinguish low and high GS PCa tissues. These promising proteins can be further explored as candidate biomarkers for PCa aggressiveness.
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