Epithelial ovarian cancer is the most lethal gynecological malignancy, and disease-specific biomarkers are urgently needed to improve diagnosis, prognosis, and to predict and monitor treatment efficiency. We present an in-depth proteomic analysis of selected biochemical fractions of human ovarian cancer ascites, resulting in the stringent and confident identification of over 2500 proteins. Rigorous filter schemes were applied to objectively minimize the number of false-positive identifications, and we only report proteins with substantial peptide evidence. Integrated computational analysis of the ascites proteome combined with several recently published proteomic data sets of human plasma, urine, 59 ovarian cancer related microarray data sets, and protein-protein interactions from the Interologous Interaction Database I 2 D (http://ophid.utoronto.ca/i2d) resulted in a short-list of 80 putative biomarkers. The presented proteomics analysis provides a significant resource for ovarian cancer research, and a framework for biomarker discovery.

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Placental abnormalities are associated with two of the most common and serious complications of human pregnancy, maternal preeclampsia (PE) and fetal intrauterine growth restriction (IUGR), each disorder affecting B5% of all pregnancies. An important question for the use of the mouse as a model for studying human disease is the degree of functional conservation of genetic control pathways from human to mouse. The human and mouse placenta show structural similarities, but there have been no systematic attempts to assess their molecular similarities or differences. We collected protein and mRNA expression data through shot-gun proteomics and microarray expression analysis of the highly vascular exchange region, microdissected from the human and mouse near-term placenta. Over 7000 ortholog genes were detected with 70% co-expressed in both species. Close to 90% agreement was found between our human proteomic results and 1649 genes assayed by immunohistochemistry for expression in the human placenta in the Human Protein Atlas. Interestingly, over 80% of genes known to cause placental phenotypes in mouse are co-expressed in human. Several of these phenotype-associated proteins form a tight protein-protein interaction network involving 15 known and 34 novel candidate proteins also likely important in placental structure and/or function. The entire data are available as a web-accessible database to guide the informed development of mouse models to study human disease.

Proteomic profiling has emerged as a useful tool for identifying tissue alterations in disease states including malignant transformation. The aim of this study was to reveal expression profiles associated with the highly motile/invasive ovarian cancer cell phenotype. Six ovarian cancer cell lines were subjected to proteomic characterization using multidimensional protein identification technology (MudPIT), and evaluated for their motile/invasive behavior, so that these parameters could be compared. Within whole cell extracts of the ovarian cancer cells, MudPIT identified proteins that mapped to 2245 unique genes. Western blot analysis for selected proteins confirmed the expression profiles revealed by MudPIT, demonstrating the fidelity of this high-throughput analysis. Unsupervised cluster analysis partitioned the cell lines in a manner that reflected their motile/invasive capacity. A comparison of protein expression profiles between cell lines of high (group 1) versus low (group 2) motile/invasive capacity revealed 300 proteins that were differentially expressed, of which 196 proteins were significantly upregulated in group 1. Protein network and KEGG pathway analysis indicated a functional interplay between proteins up-regulated in group 1 cells, with increased expression of several key members of the actin cytoskeleton, extracellular matrix (ECM) and focal adhesion pathways. These proteomic expression profiles can be utilized to distinguish highly motile, aggressive ovarian cancer cells from lesser invasive ones, and could prove to be essential in the development of more effective strategies that target pivotal cell signaling pathways used by cancer cells during local invasion and distant metastasis.

Preeclampsia (PE) adversely impacts ϳ5% of pregnancies. Despite extensive research, no consistent biomarkers or cures have emerged, suggesting that different molecular mechanisms may cause clinically similar disease. To address this, we undertook a proteomics study with three main goals: (1) to identify a panel of cell surface markers that distinguish the trophoblast and endothelial cells of the placenta in the mouse; (2) to translate this marker set to human via the Human Protein Atlas database; and (3) to utilize the validated human trophoblast markers to identify subgroups of human preeclampsia. To achieve these goals, plasma membrane proteins at the blood tissue interfaces were extracted from placentas using intravascular silica-bead perfusion, and then identified using shotgun proteomics. We identified 1181 plasma membrane proteins, of which 171 were enriched at the maternal blood-trophoblast interface and 192 at the fetal endothelial interface with a 70% conservation of expression in humans. Three distinct molecular subgroups of human preeclampsia were identified in existing human microarray data by using expression patterns of trophoblast-enriched proteins. Analysis of all misexpressed genes revealed divergent dysfunctions including angiogenesis (subgroup 1), MAPK signaling (subgroup 2), and hormone biosynthesis and metabolism (subgroup 3). Subgroup 2 lacked expected changes in known preeclampsia markers (sFLT1, sENG) and uniquely overexpressed GNA12. In an independent set of 40 banked placental specimens, GNA12 was overexpressed during preeclampsia when co-incident with chronic hypertension. In the current study we used a novel translational analysis to integrate mouse and human trophoblast protein expression with human microarray data. This strategy identified distinct molecular pathologies in human preeclampsia. We conclude that clinically similar

The growth, development, and differentiation of the prostate gland is largely dependent on the action of androgens and peptide growth factors that act differentially at the level of the mesenchymal and epithelial compartments. It is our premise that to understand the emergence of metastatic and hormone refractory prostate cancer we need to investigate: (1) how androgen action at the level of the mesenchyme induces the production of peptide growth factors that in turn can facilitate the growth and development of the epithelial compartment; (2) how androgen action at the level of the epithelium induces and maintains cellular differentiation, function, and replicative senescence; and (3) how transformation of the prostate gland can corrupt androgen and growth factor signaling homeostasis. To this end, we focus our discussion on how deregulation of the growth factor signaling axis can cooperate with deregulation of the androgen signaling axis to facilitate transformation, metastasis, and the emergence of the hormone refractory and neuroendocrine phenotypes associated with progressive androgen-independent prostate cancer. Finally, we suggest a working hypothesis to explain why hormone ablation therapy works to control early disease but fails to control, and may even facilitate, advanced prostate cancer.

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The metastatic spread of cancer cells involves a complex process of detachment via antiadhesion molecules and attachment and migration through adhesion. In the prostate, androgens are generally thought to contribute to the development and progression of prostate cancer by promoting cell proliferation and survival through poorly defined mechanisms. We have reported previously that PC-3 prostate cancer cells, which are unresponsive to androgens, show androgen-dependent detachment and ultimately apoptosis when stably transfected with a full-length human androgen receptor (AR) cDNA. We now demonstrate that treatment of these cells with 5alpha-dihydrotestosterone (DHT) for 24 or 48 h increased the expression of antiadhesion mucin MUC-1 at the cell surface as detected by flow cytometry with two independent antibodies. This increase in protein was concordant with up-regulation of MUC-1 mRNA in the AR-transfected PC-3 sublines, as determined by quantitative RT-PCR. Treatment with DHT for 48 h also down-regulated the cell surface expression of alpha2beta1-integrin but having little effect on the levels of alpha3beta1- and alpha5beta1-integrins. Androgen also decreased, in a dose-dependent manner, the adhesion of AR-transfected PC-3 cells to collagen type I, which was shown to be specifically inhibited by blocking antibody to alpha2beta1-integrin. The present data demonstrate that DHT can modulate expression of adhesion and antiadhesion molecules and suggest that this effect of androgen might contribute to prostate cancer progression.