Cell Plasticity-Related Phenotypes and Taxanes Resistance in Castration-Resistant Prostate Cancer.

The prostatic tumor cells plasticity is involved in resistance to hormone-therapy, allowing these cells to survive despite androgen receptor inhibition. However, its role in taxanes resistance has not been fully established. Gene expression of plasticity-related phenotypes such as epithelial-mesenchymal transition (EMT), stem cell-like and neuroendocrine (NE) phenotypes was studied in vitro, in silico, in circulating tumor cells (CTCs) (N=22) and in tumor samples (N=117) from taxanes-treated metastatic castration-resistant prostate cancer (mCRPC) patients. Docetaxel (D)-resistant cells presented a more pronounced EMT phenotype than cabazitaxel (CZ)-resistant cells. In silico analysis revealed ESRP1 down-regulation in taxane-exposed mCRPC samples. Cell plasticity-related changes occurred in CTCs after taxanes treatment. Tumor EMT phenotype was associated with lower PSA progression-free survival (PFS) to D (P<0.001), and better to CZ (P=0.002). High ESRP1 expression was independently associated with longer PSA-PFS (P<0.001) and radiologic-PFS (P=0.001) in D and shorter PSA-PFS in the CZ cohort (P=0.041). High SYP expression was independently associated with lower PSA-PFS in D (P=0.003) and overall survival (OS) in CZ (P=0.002), and high EZH2 expression was associated with adverse OS in D-treated patients (P=0.013). In conclusion, EMT profile in primary tumor is differentially associated with D or CZ benefit and NE dedifferentiation correlates with adverse taxanes clinical outcome.

Targeted proteomics in urinary extracellular vesicles identifies biomarkers for diagnosis and prognosis of prostate cancer.

Rapid and reliable diagnosis of prostate cancer (PCa) is highly desirable as current used methods lack specificity. In addition, identification of PCa biomarkers that can classify patients into high- and low-risk groups for disease progression at early stage will improve treatment decision-making. Here, we describe a set of protein-combination panels in urinary extracellular vesicles (EVs), defined by targeted proteomics and immunoblotting techniques that improve early non-invasive detection and stratification of PCa patients.We report a two-protein combination in urinary EVs that classifies benign and PCa patients (ADSV-TGM4), and a combination of five proteins able to significantly distinguish between high- and low-grade PCa patients (CD63-GLPK5-SPHM-PSA-PAPP). Proteins composing the panels were validated by immunohistochemistry assays in tissue microarrays (TMAs) confirming a strong link between the urinary EVs proteome and alterations in PCa tissues. Moreover, ADSV and TGM4 abundance yielded a high diagnostic potential in tissue and promising TGM4 prognostic power. These results suggest that the proteins identified in urinary EVs distinguishing high- and low grade PCa are a reflection of histological changes that may be a consequence of their functional involvement in PCa development. In conclusion, our study resulted in the identification of protein-combination panels present in urinary EVs that exhibit high sensitivity and specificity for PCa detection and patient stratification. Moreover, our study highlights the potential of targeted proteomic approaches-such as selected reaction monitoring (SRM)-as diagnostic assay for liquid biopsies via urinary EVs to improve diagnosis and prognosis of suspected PCa patients.

Prediction of Response to Neoadjuvant Chemotherapy Using Core Needle Biopsy Samples with the Prosigna Assay.

PURPOSE: Most hormone receptor (HR)(+)/HER2(-) breast cancer patients respond unfavorably to neoadjuvant chemotherapy (NAC); however, genomic tests may identify those patients who are likely to benefit. Using the Prosigna assay, we first evaluated the technical performance of core needle biopsy (CNB) tissues. We then determined whether Prosigna risk of relapse (ROR) score and intrinsic subtype predicted response to NAC in HR(+)/HER2(-) patients using CNB samples. EXPERIMENTAL DESIGN: Using the NanoString's nCounter Dx analysis system and a development tissue sample set, we established tissue requirements and assay output variance. We then evaluated the concordance in subtype and correlation in ROR between CNBs and corresponding surgical resection specimens (SRS) in a second independent sample set. Finally, we analyzed 180 independent CNB samples from HR(+)/HER2(-) patients who were treated with NAC and correlated ROR and intrinsic subtype with pathologic response. RESULTS: Intra- and interbiopsy variabilities were 2.2 and 6.8 ROR units, respectively. Subtype concordance within multiple CNBs was high for the 4- and 3-subtype classifications (k = 0.885 and 0.889, respectively). Correlation in Prosigna ROR score observed between paired CNBs and SRS was high (r ≥ 0.90), and subtype concordance was also high for the 4- and 3-subtype classifications (kappa = 0.81 and 0.91, respectively). Prosigna results obtained from the HR(+)/HER2(-) patient samples showed that both ROR (P = 0.047) and intrinsic subtype (OR LumA vs. non-LumA = 0.341, P = 0.037) were significant predictors of response to NAC. CONCLUSIONS: Prosigna ROR and intrinsic subtype are readily obtained from CNB samples in normal practice and reliably predict response to NAC in HR(+)/HER2(-) patients.