Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process

126 Background: Identifying aberrant activity of developmental pathways in prostate cancer provides therapeutic opportunities. To this end, despite a shared embryonic origin and similarities to prostate cancer in histology and androgen dependence, seminal vesicle cancer is exceptionally rare. Genomic pathway analyses of their critical developmental differences may reveal uncharacterized oncogenic pathways. Previous attempts to do so have used whole tissue preparations. We hypothesized that careful gene profiling of pure primary epithelial cultures from normal prostate and seminal vesicles would reduce confounding noise during analysis and provide more robust pathway prioritization. Methods: Paired normal prostate and seminal vesicle epithelium cultures were created from three de-identified patients. Derived gene expression profiles were grouped into cancer biomodules using a protein-protein network algorithm to analyze their relationship to known oncogenes. Each resultant biomodule was assayed for its prognostic ability in independent Kaplan-Meier analyses of prostate cancer patients for time to recurrence and overall survival. Protein products from prioritized biomodule genes were then evaluated in vitro. Results: Gene expression profiling and protein network prioritization resulted in three cancer biomodules. Survival analysis revealed that the embryonic developmental biomodule centered on homeobox genes Meis1, Meis2 and Pbx1 to have clinical import. This homeobox biomodule detected a survival difference in a set of active surveillance patients (n=172, p=0.05) and identified men who were more likely to recur biochemically post-prostatectomy (n=78, p=0.02). We analyzed in vitro protein expression of Meis1, Meis2, Pbx1 and confirmed decreased gene expression in independent datasets of prostate cancer versus normal tissue. Conclusions: The Meis1/Meis2/Pbx1 biomodule may explain key differences in seminal vesicle and normal prostate epithelium development. In contrast to other cancers, Meis1, Meis2, and Pbx1 may play a tumor suppressor role in prostate cancer. Thus deregulation of this biomodule may be critical in prostate cancer oncogenesis.

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Evidence for a field effect in early prostate cancer (PCa): Gene expression profiles in normal-appearing prostate tissue (NT) adjacent to tumor (T) as predictors of clinical outcome.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.5029 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 5029-5029 ◽

Cited By ~ 1

Author(s):

Eric A. Klein ◽

Sara Moscovita Falzarano ◽

Nan Zhang ◽

Dejan Knezevic ◽

Tara Maddala ◽

...

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Field Effect ◽

Proportional Hazards ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Cox Proportional Hazards ◽

Clinical Recurrence ◽

Molecular Alterations ◽

Cox Proportional Hazards Models

5029 Background: We previously identified genes whose expression predicts aggressive PCa (clinical recurrence (cR), prostate cancer death (PCD), adverse pathology) when assessed in histologically heterogeneous tumor foci and in biopsies (Klein ASCO 2012). These results enabled the definition of a multi-gene Genomic Prostate Score (GPS), which has been clinically validated (Cooperberg AUA 2013). There is interest regarding a possible field effect in PCa, i.e. molecular alterations throughout the gland that may influence PCa development. We conducted exploratory analyses to evaluate gene expression, including GPS, in adjacent normal-appearing tissue (NT) for prediction of cR and PCD. Methods: Cohort sampling was used to select 127 patients with and 374 without cR from 2,641 patients treated with RP for T1/T2 PCa. Expression of 732 genes was measured by qRT-PCR separately in T and NT (defined as > 3 mm from T) specimens. GPS (0-100 units) was determined using the genes and algorithm from the validation study. Analysis used Cox proportional hazards models and Storey’s false discovery rate (FDR) control. Results: 410 evaluable patients had paired T and NT. Of the 405 genes which were predictive of outcome in T (FDR < 20%), 289 (71%) showed similar but weaker effects in NT. 47 genes were associated with cR in NT (FDR < 20%), of which 34 also concordantly predicted cR in T (FDR < 20%). GPS assessed in NT significantly predicted time to cR (HR/20 units = 1.8; 95% CI: 1.3-2.4; p< 0.001) and PCD (HR/20 units = 1.9; 95% CI: 1.2-3.0; p = 0.005) but was less predictive than GPS in T (HR/20 units = 4.8 for cR; 95% CI: 3.7-6.2; p < 0.001 and HR/20 units = 6.9 for PCD; 95% CI: 4.4-10.7; p < 0.001). The strongest components of GPS in predicting cR and PCD in NT were stromal response and androgen signaling genes (p < 0.05); proliferation and cellular organization genes did not consistently provide a significant contribution in NT. Conclusions: These data indicate that gene expression profiles, including GPS, can predict outcome in NT, albeit more weakly than in tumor. These findings suggest that there is an underlying field effect associated with the development of aggressive PCa.

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