Computational analysis of gene expression space associated with metastatic cancer

<p>Abstract</p> <p>Background</p> <p>Prostate carcinoma is among the most common types of cancer affecting hundreds of thousands people every year. Once the metastatic form of prostate carcinoma is documented, the majority of patients die from their tumors as opposed to other causes. The key to successful treatment is in the earliest possible diagnosis, as well as understanding the molecular mechanisms of metastatic progression. A number of recent studies have identified multiple biomarkers for metastatic progression. However, most of the studies consider only direct comparison between metastatic and non-metastatic classes of samples.</p> <p>Results</p> <p>We propose an alternative concept of analysis that considers the entire multidimensional space of gene expression and identifies the partition of this space in which metastatic development is possible. To apply this concept in cancer gene expression studies we utilize a modification of high-dimension natural taxonomy algorithm FOREL. Our analysis of microarray data containing primary and metastatic cancer samples has revealed not only differentially expressed genes, but also relations between different groups of primary and metastatic cancer. Metastatic samples tend to occupy a distinct partition of gene expression space. Further pathway analysis suggests that this partition is delineated by a specific pattern of gene expression in cytoskeleton remodeling, cell adhesion and apoptosis/cell survival pathways. We compare our findings with both report of original analysis and recent studies in molecular mechanism of metastasis.</p> <p>Conclusion</p> <p>Our analysis indicates a single molecular mechanism of metastasis. The new approach does not contradict previously reported findings, but reveals important details unattainable with traditional methodology.</p

Specificity and heregulin regulation of Ebp1 (ErbB3 binding protein 1) mediated repression of androgen receptor signalling

Although ErbB receptors have been implicated in the progression of prostate cancer, little is known about proteins that may mediate their interactions with the androgen receptor (AR). Ebp1, a protein cloned via its association with the ErbB3 receptor, binds the AR and inhibits androgen-regulated transactivation of wild-type AR in COS cells. As the complement of coregulators in different cells are important for AR activity, we determined the effect of Ebp1 on AR function in prostate cancer cell lines. In addition, we examined the regulation of Ebp1 function by the ErbB3/4 ligand heregulin (HRG). In this study, we demonstrate, using several natural AR-regulated promoters, that Ebp1 repressed transcriptional activation of wild-type AR in prostate cancer cell lines. Downregulation of Ebp1 expression in LNCaP cells using siRNA resulted in activation of AR in the absence of androgen. Ebp1 associated with ErbB3 in LNCaP cells in the absence of HRG, but HRG induced the dissociation of Ebp1 from ErbB3. In contrast, HRG treatment enhanced both the association of Ebp1 with AR and also the ability of Ebp1 to repress AR transactivation. These studies suggest that Ebp1 is an AR corepressor whose biological activity can be regulated by the ErbB3 ligand, HRG

A Tissue Biomarker Panel Predicting Systemic Progression after PSA Recurrence Post-Definitive Prostate Cancer Therapy

Many men develop a rising PSA after initial therapy for prostate cancer. While some of these men will develop a local or metastatic recurrence that warrants further therapy, others will have no evidence of disease progression. We hypothesized that an expression biomarker panel can predict which men with a rising PSA would benefit from further therapy.A case-control design was used to test the association of gene expression with outcome. Systemic (SYS) progression cases were men post-prostatectomy who developed systemic progression within 5 years after PSA recurrence. PSA progression controls were matched men post-prostatectomy with PSA recurrence but no evidence of clinical progression within 5 years. Using expression arrays optimized for paraffin-embedded tissue RNA, 1021 cancer-related genes were evaluated-including 570 genes implicated in prostate cancer progression. Genes from 8 previously reported marker panels were included. A systemic progression model containing 17 genes was developed. This model generated an AUC of 0.88 (95% CI: 0.84-0.92). Similar AUCs were generated using 3 previously reported panels. In secondary analyses, the model predicted the endpoints of prostate cancer death (in SYS cases) and systemic progression beyond 5 years (in PSA controls) with hazard ratios 2.5 and 4.7, respectively (log-rank p-values of 0.0007 and 0.0005). Genes mapped to 8q24 were significantly enriched in the model.Specific gene expression patterns are significantly associated with systemic progression after PSA recurrence. The measurement of gene expression pattern may be useful for determining which men may benefit from additional therapy after PSA recurrence

The cancer-associated cell migration protein TSPAN1 is under control of androgens and its upregulation increases prostate cancer cell migration.

Cell migration drives cell invasion and metastatic progression in prostate cancer and is a major cause of mortality and morbidity. However the mechanisms driving cell migration in prostate cancer patients are not fully understood. We previously identified the cancer-associated cell migration protein Tetraspanin 1 (TSPAN1) as a clinically relevant androgen regulated target in prostate cancer. Here we find that TSPAN1 is acutely induced by androgens, and is significantly upregulated in prostate cancer relative to both normal prostate tissue and benign prostate hyperplasia (BPH). We also show for the first time, that TSPAN1 expression in prostate cancer cells controls the expression of key proteins involved in cell migration. Stable upregulation of TSPAN1 in both DU145 and PC3 cells significantly increased cell migration and induced the expression of the mesenchymal markers SLUG and ARF6. Our data suggest TSPAN1 is an androgen-driven contributor to cell survival and motility in prostate cancer.This article is freely available via Open Access. Click on the Additional Link above to access the full-text via the publisher's site

Castration‐Resistant Prostate Cancer: Targeted Therapies and Individualized Treatment

Various molecular mechanisms have been implicated in the progression from hormone-sensitive to castration-resistant prostate cancer (CRPC). Novel targeted agents to treat CRPC have been developed that inhibit either androgen receptor (AR)-mediated signaling (AR antagonists and inhibitors of androgen synthesis) or non–AR-mediated signaling (inhibitors of Src, mammalian target of rapamycin, chaperone proteins, insulin-like growth factor-1 receptor, vascular endothelial growth factor, and endothelin-A receptor) pathways. However, variable efficacy has been observed in clinical trials, most likely because of the biologic heterogeneity of CRPC. To account for potential differences in disease biology, a more individualized approach to treatment, based on genomic and/or proteomic analyses of individual tumors, is being investigated. By identifying tumors with a characteristic molecular subtype and assigning treatment accordingly, it is hoped that a higher proportion of patients will benefit from targeted therapy. Additionally, lessons learned through the application of these technologies to prostate cancer may subsequently influence therapeutic development in other solid tumors