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.
Project description:To characterize the molecular features of clinical (Hormone-Refractory Prostate Cancers) HRPCs, we generated the precise gene-expression profiles of 25 clinical HRPCs and 10 hormone-sensitive prostate cancers (HSPCs) by genome-wide cDNA microarrays combining with laser microbeam microdisection. Keywords: disease status analysis
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:Prostate cancer is the most common malignancy in men. Yet, the modest benefit of treatment highlights the unmet need for prognostic biomarkers in prostate cancer (1). Few large prostate oncogenome resources currently exist that combine the molecular and clinical outcome data necessary for prognostic discovery. To determine the extent to which genomic aberrations reflect the risk of prostate cancer-specific outcomes, we profiled more than 100 primary prostate cancers with long-term follow-up for genome-wide copy number alterations (CNA). We also updated the long-term clinical outcome (median 8 years) of an additional independent cohort of 181 primary prostate cancers that we previously profiled for CNA and expression changes (2). Together, we found that CNA burden across the genome, defined as the percent of the tumor genome affected by CNA, is prognostic for recurrence and metastasis in these two cohorts. This prognostic significance of CNA is independent of Gleason grade, a major existing histopathological prognostic variable in prostate cancer. Moreover, in intermediate-risk Gleason 7 prostate cancers that show a wide range of outcomes, CNA burden is also prognostic for biochemical recurrence, independent of prostate-specific antigen or nomogram score. CNA burden therefore has the potential to stratify patients by their risk of recurrence in an otherwise intermediate risk subpopulation. We further demonstrate that CNA burden can be established in diagnostic FFPE needle biopsies using low-input whole genome sequencing. Together, this work highlights the potential of oncogenomics to identify useful and clinically amenable prognostic factors that may inform prostate cancer outcome and treatment. Human prostate samples were profiled on Agilent 1M aCGH arrays per manufacturer's instructions. A pooled reference normal DNA was used as the reference.