Secreted miR-210-3p, miR-183-5p and miR-96-5p reduce sensitivity to docetaxel in prostate cancer cells.

Docetaxel (DCT) resistance is one of the main factors responsible for treatment failure in metastatic prostate cancer (PCa). Although several mechanisms of DCT resistance have been elucidated, the issue is still far from comprehensive. In this work we show that miR-96-5p, miR-183-5p and miR-210-3p (referred to as sDCTR-miRNAs) are specifically released by DCT resistant (DCTR) PCa clones and decrease the efficacy of DCT in PCa cells when overexpressed. Through bioinformatic analysis, we identified several potential targets of sDCTR-miRNAs' activity including FOXO1, IGFBP3, and PDCD4 known to exert a role in DCT resistance. Additionally, we found that PPP2CB and INSIG1 mediated the ability of sDCTR-miRNAs to reduce the efficacy of DCT. We explored whether secreted sDCTR-miRNAs could affect the phenotype of PCa cells. We found that exposure to exosomes derived from DCTR PCa clones (in which the content of sDCTR-miRNAs was higher than in exosomes from parental cells), as well as exposure to exosome loaded with sDCTR-miRNAs, reduced the cytotoxicity of DCT in PCa cells sensitive to the drug. Finally, we validated circulating miR-183-5p and miR-21-5p as potential predictive biomarkers of DCT resistance in PCa patients. Our study suggests a horizontal transfer mechanism mediated by exosomal miRNAs that contributes to reduce docetaxel sensitivity and highlights the relevance of cell-to-cell communication in drug resistance.

The Prostate Cancer Cells Resistant to Docetaxel as in vitro Model for Discovering MicroRNAs Predictive of the Onset of Docetaxel Resistance.

On the grounds that miRNAs present in the blood of prostate cancer (PCa) patients are released in the growth medium by PCa cells, it is conceivable that PCa cells resistant to docetaxel (DCT) (DCTR) will release miRNAs that may be found in PCa patients under DCT therapy if resistant PCa cells appear. We isolated DCTR clones respectively from 22Rv1 and DU-145 PCa cell lines and performed through next-generation sequencing (NGS) the miRNAs profiles of the released miRNAs. The analysis of the NGS data identified 105 and 1 miRNAs which were differentially released in the growth medium of the 22Rv1/DCTR and DU-145/DCTR clones, respectively. Using additional filters, we selected 12 and 1 miRNA more released by all 22Rv1/DCTR and DU-145/DCTR clones, respectively. Moreover, we showed that 6 of them were more represented in the growth medium of the DCTR cells than the ones of DCT-treated cells. We speculated that they have the pre-requisite to be tested as predictive biomarkers of the DCT resistance in PCa patients under DCT therapy. We propose the utilization of clones resistant to a given drug as in vitro model to identify the differentially released miRNAs, which in perspective could be tested as predictive biomarkers of drug resistance in tumor patients under therapy.

Immunologic checkpoints blockade in renal cell, prostate, and urothelial malignancies.

Genitourinary (GU) tumors, and in particular renal cell and prostate cancer, represent one of the most dynamic areas in oncology from the scientific point of view. One of the most recent treatment approaches for GU tumors has focused on a series of molecules known as immune checkpoints and the possibility of manipulating immune responses against tumor cells by blocking these molecules with monoclonal antibodies (mAbs). Cytotoxic T lymphocyte antigen-4 (CTLA-4), and the immune checkpoint inhibitor mAbs ipilimumab and tremelimumab, represent the prototypes of this new growing class of agents called immunomodulating antibodies, while programmed death/ligand 1 (PD-1/PD-L1) also has garnered a significant interest as a new immune checkpoints to target in urothelial cancer, with the anti-PD-1/PD-L1 inhibitor mAbs nivolumab, MPDL-3280, and BMS-936559 as the first agents tested. Here we report the encouraging initial data observed in GU cancers with this new class of agents, which have reinforced the interest of investigating the therapeutic potential of the immune checkpoint modulators in large controlled trials.

Clinical implications for a treatment algorithm and differential indication to hormone therapy and chemotherapy options in metastatic castrate-resistant prostate cancer: a personal view.

Although docetaxel is still considered a mainstay of treatment in metastatic castrate-resistant prostate cancer (mCRPC), in the last few years, new agents have been developed to improve survival in this setting and reach a possible optimal personalized treatment strategy. In this paper, we provide a personal view and an algorithm for mCRPC patients, according to available evidence, personal opinion and experience. Abiratone acetate, cabazitaxel, radium-223, sipuleucel-T and enzalutamide, together with docetaxel, have demonstrated a survival benefit in these patients. The use of rechallenge with docetaxel in mCRPC patients with disease progression after a first response has been considered. These new agents complicated the scenario and posed the challenge to move from the old sequential to a new algorithm-based approach. At this stage, the algorithm is necessarily based on experts' opinion, since the efficacy of a single agent in a specific setting has not been validated by sequential trials.

GOAL: an inverse toxicity-related algorithm for daily clinical practice decision making in advanced kidney cancer.

Metastatic renal cell carcinoma (mRCC), considered almost an orphan disease only six years ago, appears today a very dynamic pathology. The recently switch to the actual overcrowded scenario defined by seven active drugs has driven physicians to an incertitude status, due to difficulties in defining the best possible treatment strategy. This situation is mainly related to the absence of predictive biomarkers for any available or new therapy. Such issue, associated with the nearly absence of published face-to-face studies, draws a complex picture frame. In order to solve this dilemma, decisional algorithms tailored on drug efficacy data and patient profile are recognized as very useful tools. These approaches try to select the best therapy suitable for every patient profile. On the contrary, the present review has the "goal" to suggest a reverse approach: basing on the pivotal studies, post-marketing surveillance reports and our experience, we defined the polarizing toxicity (the most frequent toxicity in the light of clinical experience) for every single therapy, creating a new algorithm able to identify the patient profile, mainly comorbidities, unquestionably unsuitable for each single agent presently available for either the first- or the second-line therapy. The GOAL inverse decision-making algorithm, proposed at the end of this review, allows to select the best therapy for mRCC by reducing the risk of limiting toxicities.