Neuropilin-1 is upregulated in the adaptive response of prostate tumors to androgen-targeted therapies and is prognostic of metastatic progression and patient mortality.

Recent evidence has implicated the transmembrane co-receptor neuropilin-1 (NRP1) in cancer progression. Primarily known as a regulator of neuronal guidance and angiogenesis, NRP1 is also expressed in multiple human malignancies, where it promotes tumor angiogenesis. However, non-angiogenic roles of NRP1 in tumor progression remain poorly characterized. In this study, we define NRP1 as an androgen-repressed gene whose expression is elevated during the adaptation of prostate tumors to androgen-targeted therapies (ATTs), and subsequent progression to metastatic castration-resistant prostate cancer (mCRPC). Using short hairpin RNA (shRNA)-mediated suppression of NRP1, we demonstrate that NRP1 regulates the mesenchymal phenotype of mCRPC cell models and the invasive and metastatic dissemination of tumor cells in vivo. In patients, immunohistochemical staining of tissue microarrays and mRNA expression analyses revealed a positive association between NRP1 expression and increasing Gleason grade, pathological T score, positive lymph node status and primary therapy failure. Furthermore, multivariate analysis of several large clinical prostate cancer (PCa) cohorts identified NRP1 expression at radical prostatectomy as an independent prognostic biomarker of biochemical recurrence after radiation therapy, metastasis and cancer-specific mortality. This study identifies NRP1 for the first time as a novel androgen-suppressed gene upregulated during the adaptive response of prostate tumors to ATTs and a prognostic biomarker of clinical metastasis and lethal PCa.

Correlation of B7-H3 with androgen receptor, immune pathways and poor outcome in prostate cancer: an expression-based analysis.

BACKGROUND: B7-H3 (CD276), part of the B7 superfamily of immune checkpoint molecules, has been shown to have an immunomodulatory role. Its regulation, receptor and mechanism of action remain unclear. B7-H3 protein expression correlates with prostate cancer outcomes, and humanized monoclonal antibodies (that is, enoblituzumab) are currently being investigated for therapeutic use. Here we used genomic expression data to examine the relationship between B7-H3 mRNA expression and prostate cancer. METHODS: Prostatectomy tissue from 2781 patients were profiled using the Affymetrix HuEx 1.0 ST microarray. Pairwise comparisons were used to identify significant associations between B7-H3 expression and clinicopathologic variables, and survival analyses were used to evaluate the prognostic significance of B7-H3. Pearson's correlation analyses were performed to assess the relationship of B7-H3 expression with molecular subtypes and individual transcripts. Androgen receptor (AR) occupancy at the B7-H3 locus was determined using chromatin immunoprecipitation (ChIP), and androgen-dependent expression changes in B7-H3 was evaluated by quantitative reverse transcription PCR in LNCaP cell lines. Oncomine was queried to evaluate B7-H3 expression in metastatic disease. RESULTS: B7-H3 mRNA expression was positively associated with higher Gleason score (P<0.001), tumor stage (P<0.001), and castrate resistant metastatic disease (P<0.0001). High B7-H3 expression correlated with the development of metastasis and prostate cancer specific mortality, but this was not significant on multi-variable analysis. B7-H3 expression correlated with ERG-positive disease (r=0.99) and AR expression (r=0.36). ChIP revealed an AR-binding site upstream of B7-H3, and the presence of androgens decreased B7-H3 expression in LNCaP suggesting potential direct AR regulation. Gene set enrichment analysis demonstrated an association of B7-H3 with androgen signaling as well as immune regulatory pathways. CONCLUSIONS: Higher B7-H3 expression correlates with Gleason grade, prostate cancer stage and poor oncologic outcomes in prostatectomy cohorts. B7-H3 expression appears to be related to androgen signaling as well as the immune reactome.

High-throughput transcriptomic analysis nominates proteasomal genes as age-specific biomarkers and therapeutic targets in prostate cancer.

BACKGROUND: Although prostate cancer (PCa) is hypothesized to differ in nature between younger versus older patients, the underlying molecular distinctions are poorly understood. We hypothesized that high-throughput transcriptomic analysis would elucidate biological differences in PCas arising in younger versus older men, and would nominate potential age-specific biomarkers and therapeutic targets. METHODS: The high-density Affymetrix GeneChip platform, encompassing >1 million genomic loci, was utilized to assess gene expression in 1090 radical prostatectomy samples from patients with long-term follow-up. We identified genes associated with metastatic progression by 10 years post-treatment in younger (age<65) versus older (age⩾65) patients, and ranked these genes by their prognostic value. We performed Gene Set Enrichment Analysis (GSEA) to nominate biological concepts that demonstrated age-specific effects, and validated a target by treating with a clinically available drug in three PCa cell lines derived from younger men. RESULTS: Over 80% of the top 1000 prognostic genes in younger and older men were specific to that age group. GSEA nominated the proteasome pathway as the most differentially prognostic in younger versus older patients. High expression of proteasomal genes conferred worse prognosis in younger but not older men on univariate and multivariate analysis. Bortezomib, a Food and Drug Administration approved proteasome inhibitor, decreased proliferation in three PCa cell lines derived from younger patients. CONCLUSIONS: Our data show significant global differences in prognostic genes between older versus younger men. We nominate proteasomeal gene expression as an age-specific biomarker and potential therapeutic target specifically in younger men. Limitations of our study include clinical differences between cohorts, and increased comorbidities and lower survival in older patients. These intriguing findings suggest that current models of PCa biology do not adequately represent genetic heterogeneity of PCa related to age, and future clinical trials would benefit from stratification based on age.

A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy.

BACKGROUND: Due to their varied outcomes, men with biochemical recurrence (BCR) following radical prostatectomy (RP) present a management dilemma. Here, we evaluate Decipher, a genomic classifier (GC), for its ability to predict metastasis following BCR. METHODS: The study population included 85 clinically high-risk patients who developed BCR after RP. Time-dependent receiver operating characteristic (ROC) curves, weighted Cox proportional hazard models and decision curves were used to compare GC scores to Gleason score (GS), PSA doubling time (PSAdT), time to BCR (ttBCR), the Stephenson nomogram and CAPRA-S for predicting metastatic disease progression. All tests were two-sided with a type I error probability of 5%. RESULTS: GC scores stratified men with BCR into those who would or would not develop metastasis (8% of patients with low versus 40% with high scores developed metastasis, P<0.001). The area under the curve for predicting metastasis after BCR was 0.82 (95% CI, 0.76-0.86) for GC, compared to GS 0.64 (0.58-0.70), PSAdT 0.69 (0.61-0.77) and ttBCR 0.52 (0.46-0.59). Decision curve analysis showed that GC scores had a higher overall net benefit compared to models based solely on clinicopathologic features. In multivariable modeling with clinicopathologic variables, GC score was the only significant predictor of metastasis (P=0.003). CONCLUSIONS: When compared to clinicopathologic variables, GC better predicted metastatic progression among this cohort of men with BCR following RP. While confirmatory studies are needed, these results suggest that use of GC may allow for better selection of men requiring earlier initiation of treatment at the time of BCR.