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Identification of miRNAs specific for prostate cancer (PCa)

ABSTRACT: The purpose of this study are: - To identify new biomarkers specific for prostate cancer (PCa) that can be used as diagnostic markers in the urine of individuals with high probability of PCa (abnormal PSA and/or digital rectal examination). - To validate the utility of these new biomarkers, as well as others already known such as PCA3, fusion gene TMPRSS2-ERG, GOLPH2 and SPINK1. - To establish a prediction model for the diagnosis of PCa based on the expression of these biomarkers. - To validate this model within the framework of an opportunist programme of early diagnosis. - Within the framework of this programme, to associate a series of social-demographic, antropometric, life-style and occupational variables for establishing a risk model predictor that could be associated with the model based on the biomarkers.

ORGANISM(S): synthetic construct Homo sapiens

PROVIDER: GSE45604 | GEO | 2013/03/29

SECONDARY ACCESSION(S): PRJNA195380

REPOSITORIES: GEO

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Project description:The highly intra-tumoral heterogeneity and complex cell origination of PCa greatly limited the significance of traditional bulk RNA sequencing in finding better biomarker for disease stratification. In the context of these sequencing strategies, significant gene expression differences in specific cell population might be normalized or even shaded by genes in those less “important” but large in amount cells. Tissue specimens based single-cell RNA sequencing holds great promise for identification of novel stratification biomarkers. However, the preparation of enough viable cells for sequencing, in particular for prostate cancer (PCa), is very challenging when using this technique. In the current study, we, for the first time, employed single-cell RNA sequencing of PCa cells isolated from cancerous prostate tissues of two patients and identified fifteen cell groups including three luminal clusters with different expression profiles. One of these luminal clusters had the highest copy number variation level and marker genes mainly enriched in PCa-related metabolic process, thereafter, was considered as the malignant luminal cells in PCa. Further analysis indicates that the fifth subgroup of these cells highly expressed genes significantly correlated with PCa initiation and early development. In addition, we found this subgroup highly expressed PCa prognosis biomarkers such as AMACR and PCA3. These findings suggest that this cell subgroup might be a critical cell population for PCa diagnosis and stratification. Moreover, by further deciphering the gene expression of this subgroup, we identified another marker gene, HPN, with a 0.930 area under the curve (AUC) score distinguishing normal tissue from PCa lesion using the RNA-seq data from The Cancer Genome Atlas (TCGA). This finding was further validated by immunostaining of HPN in PCa tissue array. The expression of HPN in PCa with Gleason score > 6 is significantly higher than those in Gleason score = 6. Taken together, we provide a valuable resource for interpreting the tumor heterogeneity in PCa, and a novel candidate marker for PCa management.

Project description:Background: Breast (BCa) and prostate (PCa) cancers are hormone receptor (HR)-driven cancers. Estrogen receptor alpha (ERa) is overexpressed in 70% of diagnosed BCa patients and androgen receptor (AR) is overexpressed in 80-90% of diagnosed PCa patients. Thus, BCa and PCa patients are given therapy that reduces hormone levels or directly blocks HR activity; but most patients eventually develop treatment resistance. 15-30% of BCa patients and ≥ 30% of PCa patients that acquire treatment resistance develop tumors enriched in cancer cells with low or no HR accumulation. Furthermore, 15-20% of BCa patients and 10-20% of PCa patients are intrinsically HR-negative (HR-), and thus, have intrinsic resistance to therapy. We have previously reported that interleukin-1 (IL-1) inflammatory cytokine downregulates ERa and AR mRNA in HR-positive (HR+) BCa and PCa cell lines. Additionally, we had identified pro-survival proteins and processes upregulated by IL-1 in HR+ BCa and PCa cells, that are basally high in HR- BCa and PCa cells. Therefore, we hypothesize that IL-1 confers a conserved gene expression pattern in HR+ BCa and PCa cells that mimics conserved basal gene expression patterns in HR- BCa and PCa cells, to promote HR-independent survival and tumorigenicity. Methods: To identify changes in global gene expression we performed RNA sequencing (RNA-seq) for HR+ BCa and PCa cell lines exposed to IL-1 and for untreated HR- BCa and PCa cell lines. We confirmed expression patterns of select genes by RT-qPCR and used siRNA and/or drug inhibition to silence select genes in BCa and PCa cell lines. We also compared our gene expression data with publicly available data sets from hormone receptor-independent sublines. Finally, we performed Ingenuity Pathway Analysis (IPA) to identify signaling pathways encode by our RNA-seq data set. Results: We identified 350 genes in common between BCa and PCa cells that are induced or repressed by IL-1 in HR+ cells that are, respectively, basally high or low in HR- cells. Among these genes, we identified Sequestome-1 (SQSTM1/p62) and SRY (Sex-Determining Region Y)-Box 9 (SOX9) to be essential for survival of HR- BCa and PCa cell lines. Analysis of publicly available data indicates that p62 and SOX9 expression are elevated in hormone receptor-independent BCa and PCa sublines generated in vitro, suggesting that p62 and SOX9 have a role in acquired treatment resistance. We also assessed HR- cell line viability in response verteporfin, an FDA approved therapy for macular degeneration known to target p62, and we found that verteporfin is cytotoxic for HR- cells lines. Conclusions: Taken together, our 350 gene set can be used to identify novel therapeutic targets and/or biomarkers conserved among acquired (e.g. due to inflammation) or intrinsic hormone receptor-independent BCa and PCa.

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Identification of miRNAs specific for prostate cancer (PCa)

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