Delineation of prognostic biomarkers in prostate cancer

Prostate cancer is the most frequently diagnosed cancer in American men(1,2). Screening for prostate-specific antigen (PSA) has led to earlier detection of prostate cancer(3), but elevated serum PSA levels may be present in non-malignant conditions such as benign prostatic hyperlasia (BPH). Characterization of gene-expression profiles that molecularly distinguish prostatic neoplasms may identify genes involved in prostate carcinogenesis, elucidate clinical biomarkers, and lead to an improved classification of prostate cancer(4-6). Using microarrays of complementary DNA, we examined gene-expression profiles of more than 50 normal and neoplastic prostate specimens and three common prostate-cancer cell lines. Signature expression profiles of normal adjacent prostate (NAP), BPH, localized prostate cancer, and metastatic, hormone-refractory prostate cancer were determined. Here we establish many associations between genes and prostate cancer. We assessed two of these genes-hepsin, a transmembrane serine protease, and pim-1, a serine/threonine kinase-at the protein level using tissue microarrays consisting of over 700 clinically stratified prostate-cancer specimens. Expression of hepsin and pim-1 proteins was significantly correlated with measures of clinical outcome. Thus, the integration of cDNA microarray, high-density tissue microarray, and linked clinical and pathology data is a powerful approach to molecular profiling of human cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62849/1/412822a0.pd

Expression analysis of imbalanced genes in prostate carcinoma using tissue microarrays

To identify candidate genes relevant for prostate tumour prognosis and progression, we performed an exhaustive gene search in seven previously described genomic-profiling studies of 161 prostate tumours, and four expression profiling studies of 61 tumours. From the resulting list of candidate genes, six were selected for protein-expression analysis based on the availability of antibodies applicable to paraffinised tissue: fatty acid synthase (FASN), MYC, β-adrenergic receptor kinase 1 (BARK1, GRK2) the catalytic subunits of protein phosphatases PP1α (PPP1CA) and PP2A (PPP2CB) and metastasis suppressor NM23-H1. These candidates were analysed by immunohistochemistry (IHC) on a tissue microarray containing 651 cores of primary prostate cancer samples and benign prostatic hyperplasias (BPH) from 175 patients. In univariate analysis, expression of PP1α (P=0.001) was found to strongly correlate with Gleason score. MYC immunostaining negatively correlated with both pT-stage and Gleason score (P<0.001 each) in univariate as well as in multivariate analysis. Furthermore, a subgroup of patients with high Gleason scores was characterised by a complete loss of BARK1 protein (P=0.023). In conclusion, our study revealed novel molecular markers of potential diagnostic and therapeutic relevance for prostate carcinoma

Metabolic Regulation of Invadopodia and Invasion by Acetyl-CoA Carboxylase 1 and De novo Lipogenesis

Invadopodia are membrane protrusions that facilitate matrix degradation and cellular invasion. Although lipids have been implicated in several aspects of invadopodia formation, the contributions of de novo fatty acid synthesis and lipogenesis have not been defined. Inhibition of acetyl-CoA carboxylase 1 (ACC1), the committed step of fatty acid synthesis, reduced invadopodia formation in Src-transformed 3T3 (3T3-Src) cells, and also decreased the ability to degrade gelatin. Inhibition of fatty acid synthesis through AMP-activated kinase (AMPK) activation and ACC phosphorylation also decreased invadopodia incidence. The addition of exogenous 16∶0 and 18∶1 fatty acid, products of de novo fatty acid synthesis, restored invadopodia and gelatin degradation to cells with decreased ACC1 activity. Pharmacological inhibition of ACC also altered the phospholipid profile of 3T3-Src cells, with the majority of changes occurring in the phosphatidylcholine (PC) species. Exogenous supplementation with the most abundant PC species, 34∶1 PC, restored invadopodia incidence, the ability to degrade gelatin and the ability to invade through matrigel to cells deficient in ACC1 activity. On the other hand, 30∶0 PC did not restore invadopodia and 36∶2 PC only restored invadopodia incidence and gelatin degradation, but not cellular invasion through matrigel. Pharmacological inhibition of ACC also reduced the ability of MDA-MB-231 breast, Snb19 glioblastoma, and PC-3 prostate cancer cells to invade through matrigel. Invasion of PC-3 cells through matrigel was also restored by 34∶1 PC supplementation. Collectively, the data elucidate the novel metabolic regulation of invadopodia and the invasive process by de novo fatty acid synthesis and lipogenesis

Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer

<p>Abstract</p> <p>Background</p> <p>Molecular and epidemiological evidence demonstrate that altered gene expression and single nucleotide polymorphisms in the apoptotic pathway are linked to many cancers. Yet, few studies emphasize the interaction of variant apoptotic genes and their joint modifying effects on prostate cancer (PCA) outcomes. An exhaustive assessment of all the possible two-, three- and four-way gene-gene interactions is computationally burdensome. This statistical conundrum stems from the prohibitive amount of data needed to account for multiple hypothesis testing.</p> <p>Methods</p> <p>To address this issue, we systematically prioritized and evaluated individual effects and complex interactions among 172 apoptotic SNPs in relation to PCA risk and aggressive disease (i.e., Gleason score ≥ 7 and tumor stages III/IV). Single and joint modifying effects on PCA outcomes among European-American men were analyzed using statistical epistasis networks coupled with multi-factor dimensionality reduction (SEN-guided MDR). The case-control study design included 1,175 incident PCA cases and 1,111 controls from the prostate, lung, colo-rectal, and ovarian (PLCO) cancer screening trial. Moreover, a subset analysis of PCA cases consisted of 688 aggressive and 488 non-aggressive PCA cases. SNP profiles were obtained using the NCI Cancer Genetic Markers of Susceptibility (CGEMS) data portal. Main effects were assessed using logistic regression (LR) models. Prior to modeling interactions, SEN was used to pre-process our genetic data. SEN used network science to reduce our analysis from > 36 million to < 13,000 SNP interactions. Interactions were visualized, evaluated, and validated using entropy-based MDR. All parametric and non-parametric models were adjusted for age, family history of PCA, and multiple hypothesis testing.</p> <p>Results</p> <p>Following LR modeling, eleven and thirteen sequence variants were associated with PCA risk and aggressive disease, respectively. However, none of these markers remained significant after we adjusted for multiple comparisons. Nevertheless, we detected a modest synergistic interaction between <it>AKT3 rs2125230-PRKCQ rs571715 </it>and disease aggressiveness using SEN-guided MDR (p = 0.011).</p> <p>Conclusions</p> <p>In summary, entropy-based SEN-guided MDR facilitated the logical prioritization and evaluation of apoptotic SNPs in relation to aggressive PCA. The suggestive interaction between <it>AKT3-PRKCQ </it>and aggressive PCA requires further validation using independent observational studies.</p

Prognostic factors in prostate cancer

Prognostic factors in organ confined prostate cancer will reflect survival after surgical radical prostatectomy. Gleason score, tumour volume, surgical margins and Ki-67 index have the most significant prognosticators. Also the origins from the transitional zone, p53 status in cancer tissue, stage, and aneuploidy have shown prognostic significance. Progression-associated features include Gleason score, stage, and capsular invasion, but PSA is also highly significant. Progression can also be predicted with biological markers (E-cadherin, microvessel density, and aneuploidy) with high level of significance. Other prognostic features of clinical or PSA-associated progression include age, IGF-1, p27, and Ki-67. In patients who were treated with radiotherapy the survival was potentially predictable with age, race and p53, but available research on other markers is limited. The most significant published survival-associated prognosticators of prostate cancer with extension outside prostate are microvessel density and total blood PSA. However, survival can potentially be predicted by other markers like androgen receptor, and Ki-67-positive cell fraction. In advanced prostate cancer nuclear morphometry and Gleason score are the most highly significant progression-associated prognosticators. In conclusion, Gleason score, capsular invasion, blood PSA, stage, and aneuploidy are the best markers of progression in organ confined disease. Other biological markers are less important. In advanced disease Gleason score and nuclear morphometry can be used as predictors of progression. Compound prognostic factors based on combinations of single prognosticators, or on gene expression profiles (tested by DNA arrays) are promising, but clinically relevant data is still lacking