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Identification of potential therapeutic targets in prostate cancer through a cross-species approach.

ABSTRACT: Genetically engineered mouse models of cancer can be used to filter genome-wide expression datasets generated from human tumours and to identify gene expression alterations that are functionally important to cancer development and progression. In this study, we have generated RNAseq data from tumours arising in two established mouse models of prostate cancer, PB-Cre/PtenloxP/loxP and p53loxP/loxPRbloxP/loxP, and integrated this with published human prostate cancer expression data to pinpoint cancer-associated gene expression changes that are conserved between the two species. To identify potential therapeutic targets, we then filtered this information for genes that are either known or predicted to be druggable. Using this approach, we revealed a functional role for the kinase MELK as a driver and potential therapeutic target in prostate cancer. We found that MELK expression was required for cell survival, affected the expression of genes associated with prostate cancer progression and was associated with biochemical recurrence.

SUBMITTER: Jurmeister S

PROVIDER: S-EPMC5840539 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Identification of potential therapeutic targets in prostate cancer through a cross-species approach.

Jurmeister Sarah S Ramos-Montoya Antonio A Sandi Chiranjeevi C Pértega-Gomes Nelma N Wadhwa Karan K Lamb Alastair D AD Dunning Mark J MJ Attig Jan J Carroll Jason S JS Fryer Lee Gd LG Felisbino Sérgio L SL Neal David E DE

EMBO molecular medicine 20180301 3

Genetically engineered mouse models of cancer can be used to filter genome-wide expression datasets generated from human tumours and to identify gene expression alterations that are functionally important to cancer development and progression. In this study, we have generated RNAseq data from tumours arising in two established mouse models of prostate cancer, PB-Cre/PtenloxP/loxP and p53loxP/loxPRbloxP/loxP, and integrated this with published human pro ...[more]

PMID: 29437778

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Project description:Prostate cancer (PC) is the most common and the second leading cause of cancer-related death among American men. Early diagnosis is a prerequisite to improving therapeutic benefits. However, the current clinical biomarkers for PC do not reliably decipher indolent PC from other urogenital disorders. Thus, effective clinical intervention necessitates development of new biomarkers for early detection of PC. The present study aimed to identify the miRNA signature in organ-confined (Gleason Score 6) prostate tumors. MicroRNA (miRNA/miR) array analysis identified 118 upregulated and 73 downregulated miRNAs in microdissected tumors in comparison to matched neighboring normal prostate epithelium. The miRs-Plus-A1083, -92b-5p, -18a-3p, -19a-3p, -639, -3622b-3p, -3189-3p, -155-3p, -410, -1179, 548b-5p, and -4469 are predominantly expressed (7-11-fold), whereas miRs-595, 4490, -3120-5p, -1299, -21-5p, -3677-3, -let-7b-5p, -5189, 3-121-5p, -4518, -200a-5p, -3682-5p, -3689d, -3149 represent the most downregulated (12-113-fold) miRNAs in microdissected prostate tumors. The array expression profile of selected miRNA signature and their potential mRNA targets was validated by qRT-PCR analysis in PC cell lines. Integrated in silico and computational prediction analyses demonstrated that the dysregulated miRNA signature map to key regulatory factors involved in tumorigenesis, including cell cycle, apoptosis, and p53 pathways. The newly identified miRNA signature has potential clinical utility as biomarkers, prognostic indicators, and therapeutic targets for early detection of PC. Further studies are needed to assess the functional significance and clinical usefulness of the identified miRNAs. Impact Statement To our knowledge his is the first study of identifying miRNA signatures in microdissected indolent (Gleason score 6) prostate cancer in comparison to matched normal prostate epithelium. By employing in silico and computational prediction analysis, the study provides a landscape of potential miRNA targets and key cellular pathways involved in prostate tumorigenesis. Identification if miRNAs and their relevant targets and pathways pave the way for underpinning their mechanistic role of miRNAs in human prostate tumorigenesis, and possibly other human cancers. Importantly, the outcome of the study has important clinical implications for the management of prostate cancer, including the use of miRNA(s) as biomarkers for early detection of prostate cancer.

Project description:The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially-expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA-target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over-represented genes in the integrated miRNA-target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v-myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa-let-7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa-let-7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I ?2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle-related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR-129, hsa-mir-145 and hsa-let-7c, respectively. However, further validation of these data is required.

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Project description:Introduction: Neuroendocrine prostate cancer (NEPC) is an aggressive subtype of prostate cancer, exhibiting rapid progression and is unresponsive to hormone therapy. Reliable prognostic assays and more effective treatments are critically required. However, the research of NEPC has been hampered by a lack of clinically relevant in vivo models. Recently, we successfully developed a first-in-field patient tissue-derived xenograft model of complete neuroendocrine transdifferentiation from prostate adenocarcinoma. By comparing gene expression profiles of the parental adenocarcinoma line (LTL331) and the NEPC subline (LTL331R), we identified DEK, a gene not previously reported in prostate cancer, as a potential biomarker and target for NEPC. Methods: DEK protein expression in patient tissue-derived xenograft models and clinical samples was assessed by immunohistochemistry. The function of DEK was determined by siRNA-induced reduction of DEK expression in PC-3 cells, a cell line with NEPC characteristics, followed by functional assays and gene expression profiling analysis. Results: Elevated DEK protein expression was observed in all clinical NEPC cases, which is distinct from their benign counterparts (0%), hormonal naïve prostate cancer (2.45%) and castration resistant prostate cancer (29.55%). Increased DEK expression is an independent clinical risk factor and is associated with shorter disease free survival in hormonal naïve prostate cancer patients. Reduction of DEK expression in PC-3 cells led to a marked reduction in cell proliferation, cell migration and invasion. Conclusions: The results suggest that DEK may play an important role in the progression of prostate cancer, especially NEPC and provide a potential biomarker to aid risk stratification of prostate cancer and a novel therapeutic target for treating NEPC. The function of DEK was determined by siRNA-induced reduction of DEK expression in PC-3 cells, a cell line with NEPC characteristics, followed by functional assays and gene expression profiling analysis.

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Identification of potential therapeutic targets in prostate cancer through a cross-species approach.

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Identification of potential therapeutic targets in prostate cancer through a cross-species approach.

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