Project description:Currently, comprehensive and quantitative proteomic analysis of human prostate cancer tissue specimens remains scarce, hindering the identification of protein complexes and pathways deregulated in prostate cancer. In this study, we applied TMT-SPS-MS3-based quantitative proteomics to analzye 9 normal controls, 9 low-grade prostate cancer, and 9 high-grade prostate cancer. About 3,600 proteins were quantified across all the 27 prostate specimens. Statistical analysis identified 651 proteins that are differentially expressed in high-grade prostate cancer and normal prostate. Pathway enrichment analysis revealed that the LXR/RXR activation and integrin signaling pathways are substantially downregulated in high-grade prostate cancer, compared with normal prostate cancer. In addition, protein complex analysis suggested that mitochondrial ribosomes and ribosome-biogenesis complexes are significnatly overexpressed, whereas the cholesterol effluex and focal adhesion comlexes are significantly downregulated in high-grade prostate cancer, compared with normal controls. Furthermore, differential correlation analysis indicated that the spliceosome machinery might be more active in low-grade prostate cancer, compared with normal controls. The results are expected to shed light on the molecular mechnanisms underlying the development and progression of primary prostate cancer in human patients.
Project description:We identified a novel molecular target and diagnostic biomarker, SHISA2, as an overexpressed gene in high-grade prostate cancer (PC) cells. To understand the association of SHISA2 overexpression with the aggressiveness of high-grade PC, we performed gene expression analysis using a cDNA microarray.
Project description:We identified a novel molecular target and diagnostic biomarker, SHISA2, as an overexpressed gene in high-grade prostate cancer (PC) cells. To understand the association of SHISA2 overexpression with the aggressiveness of high-grade PC, we performed gene expression analysis using a cDNA microarray. Gene expression patterns of PC-3 cells transfected with the two shRNA expression vectors (siSHISA2 and siCONTROL) were compared.
Project description:The protein Glycine-N-Acyltransferase Like 1 (GLYATL1) is involved in detoxification of benzoate and other xenobiotics and is expressed in liver and kidney. Through In silico analysis of cancer gene expression profiling and transcriptome sequencing we revealed an overexpression of GLYATL1 in primary prostate cancer. Confirming these findings by immunohistochemistry we show that GLYATL1 is overexpressed in primary prostate cancer compared to metastatic prostate cancer and benign prostatic tissue. Low grade cancers had higher GLYATL1 expression compared to high grade prostate tumors. Our studies showed that GLYATL1 is upregulated upon androgen treatment in LNCaP prostate cancer cells which harbors ETV1 gene rearrangement. Furthermore, ETV1 knockdown in LNCaP cells showed downregulation of GLYATL1 suggesting potential regulation of GLYATL1 by ETS transcription factor ETV1. Transcriptome sequencing using the GLYATL1 knockdown prostate cancer cell lines LNCaP showed regulation of multiple metabolic pathways. In summary, our study characterizes the expression GLYATL1 in prostate cancer and explore its regulation mechanism. Future studies are needed to decipher the biological significance of these findings.
Project description:To identify molecules to serve as diagnostic markers for high-grade prostate cancer (PC) and targets for novel therapeutic drugs, we investigated the gene expression profiles of high-grade PCs using a cDNA microarray combined with laser microbeam microdissection. For this study, we collected 10 frozen specimens from high-grade PCs with high PSA levels and high Gleason score (GS) in clinically using prostatic needle biopsy. All needle biopsy specimens were at clinical stages T2 to T4 with or without N1 and M1 and their GS were 8-9. Moreover, all 10 patients had not received androgen ablation therapy. Simultaneously, normal prostate (NP) epithelial cells were also microdissected from five non-prostate cancer (BPH) patients. These NP cells from five males were used as a normal mixture control for our cDNA microarray analysis.
Project description:Prostate cancer is one of the most frequently diagnosed cancers in men. Prostate tumor staging and disease aggressiveness are evaluated based on the Gleason scoring system, which is further used to direct clinical intervention. The Gleason scoring system provides an estimate of tumor aggressiveness through quantitation of the serum level of prostate specific antigen (PSA) and histologic assessment of Grade Group, determined by the Gleason Grade of the tumor specimen. To improve our understanding of the proteomic characteristics differentiating low- versus high-grade prostate cancer tumors, we performed a deep proteomic characterization of laser microdissected epithelial and stromal subpopulations from surgically resected tissue specimens from patients with Gleason 6 (n=23 specimens from n=15 patients) and Gleason 9 (n=15 specimens from n=15 patients) prostate cancer via quantitative high-resolution liquid chromatography-tandem mass spectrometry analysis.
Project description:In order to identify methylation changes in prostate cancer, we performed a genome-wide analysis of DNA methylation using Agilent human CpG island arrays. We then chose specific genes to validate methylation both in the same cases as were hybridized to the array (using quantitative EpiTYPER analysis) and in an independent series of prostate cancer samples (using MethyLight quantitative methylation specific PCR). We specifically chose low grade (Gleason score 6 cases) and high grade (Gleason score 8 cases) to discover methylated genes/loci that may be involved in the progression to a higher grade of prostate cancer.
Project description:Analysis of the transcriptome of mouse models of prostate cancer to assemble a mouse prostate cancer interactome. To assemble the mouse prostate cancer interactome, we collected 13 distinct mice or genetically-engineered mouse models (GEMMs), which together represent the full spectrum of prostate cancer phenotypes including: normal epithelium (i.e., wild-type), low-grade PIN (i.e., Nkx3.1 and APT), high-grade PIN and adenocarcinoma (i.e., APT-P; APC; Myc; NP; Erg-P; and NP53), castration-resistant prostate cancer (i.e., NP-AI), and metastatic prostate cancer (i.e., NPB; NPK; and TRAMP). To further enhance the heterogeneity afforded by this diversity of mouse models, we pharmacologically perturbed each GEMM using 13 different drugs (or appropriate vehicle). The resulting mouse prostate tissue/tumor dataset encompassed 384 expression profiles Total RNA obtained from prostate tumors/tissues of 13 mouse models of prostate cancer treated with 13 different drugs for 5 consecutive days. Prostate tumors/tissues were harvested and processed for RNA isolation and transcriptome analysis.