Extracellular vesicles miR-574-5p and miR-181a-5p as prognostic markers in NSCLC patients treated with nivolumab.

Immune checkpoint inhibitors (ICIs) have revolutionized the management of advanced non-small cell lung cancer (NSCLC), although patient survival is still unsatisfactory. Accurate predictive markers capable of personalizing the treatment of patients with NSCLC are still lacking. Circulating extracellular vesicles involved in cell-to-cell communications through miRNAs (EV-miRs) transfer are promising markers. Plasma from 245 patients with advanced NSCLC who received nivolumab as second-line therapy was collected and analyzed. EV-miRnome was profiled on 174/245 patients by microarray platform, and selected EV-miRs were validated by qPCR. A prognostic model combining EV-miR and clinical variables was built using stepwise Cox regression analysis and tested on an independent patient cohort (71/245). EV-PD-L1 gene copy number was assessed by digital PCR. For 54 patients with disease control, EV-miR changes at best response versus baseline were investigated by microarray and validated by qPCR. EV-miRNome profiling at baseline identified two EV-miRs (miR-181a-5p and miR-574-5p) that, combined with performance status, are capable of discriminating patients unlikely from those that are likely to benefit from immunotherapy (median overall survival of 4 months or higher than 9 months, respectively). EV-PD-L1 digital evaluation reported higher baseline copy number in patients at increased risk of mortality, without improving the prognostic score. Best response EV-miRNome profiling selected six deregulated EV-miRs (miR19a-3p, miR-20a-5p, miR-142-3p, miR-1260a, miR-1260b, and miR-5100) in responding patients. Their longitudinal monitoring highlighted a significant downmodulation already in the first treatment cycles, which lasted more than 6 months. Our results demonstrate that EV-miRs are promising prognostic markers for NSCLC patients treated with nivolumab.

Structure-guided optimization of 3-hydroxybenzoisoxazole derivatives as inhibitors of Aldo-keto reductase 1C3 (AKR1C3) to target prostate cancer.

AKR1C3 is an enzyme that is overexpressed in several types of radiotherapy- and chemotherapy-resistant cancers. Despite AKR1C3 is a validated target for drug development, no inhibitor has been approved for clinical use. In this manuscript, we describe our study of a new series of potent AKR1C3-targeting 3-hydroxybenzoisoxazole based inhibitors that display high selectivity over the AKR1C2 isoform and low micromolar activity in inhibiting 22Rv1 prostate cancer cell proliferation. In silico studies suggested proper substituents to increase compound potency and provided with a mechanistic explanation that could clarify their different activity, later confirmed by X-ray crystallography. Both the in-silico studies and the crystallographic data highlight the importance of 90° rotation around the single bond of the biphenyl group, in ensuring that the inhibitor can adopt the optimal binding mode within the active pocket. The p-biphenyls that bear the meta-methoxy, and the ortho- and meta-trifluoromethyl substituents (in compounds 6a, 6e and 6f respectively) proved to be the best contributors to cellular potency as they provided the best IC50 values in series (2.3, 2.0 and 2.4 µM respectively) and showed no toxicity towards human MRC-5 cells. Co-treatment with scalar dilutions of either compound 6 or 6e and the clinically used drug abiraterone led to a significant reduction in cell proliferation, and thus confirmed that treatment with both CYP171A1-and AKR1C3-targeting compounds possess the potential to intervene in key steps in the steroidogenic pathway. Taken together, the novel compounds display desirable biochemical potency and cellular target inhibition as well as good in-vitro ADME properties, which highlight their potential for further preclinical studies.

Development and validation of a clinical decision support system based on PSA, microRNAs, and MRI for the detection of prostate cancer.

OBJECTIVES: The aims of this study are to develop and validate a clinical decision support system based on demographics, prostate-specific antigen (PSA), microRNA (miRNA), and MRI for the detection of prostate cancer (PCa) and clinical significant (cs) PCa, and to assess if this system performs better compared to MRI alone. METHODS: This retrospective, multicenter, observational study included 222 patients (mean age 66, range 46-75 years) who underwent prostate MRI, miRNA (let-7a-5p and miR-103a-3p) assessment, and biopsy. Monoparametric and multiparametric models including age, PSA, miRNA, and MRI outcome were trained on 65% of the data and then validated on the remaining 35% to predict both PCa (any Gleason grade [GG]) and csPCa (GG ≥ 2 vs GG = 1/negative). Accuracy, sensitivity, specificity, positive and negative predictive value (NPV), and area under the receiver operating characteristic curve were calculated. RESULTS: MRI outcome was the best predictor in the monoparametric model for both detection of PCa, with sensitivity of 90% (95%CI 73-98%) and NPV of 93% (95%CI 82-98%), and for csPCa identification, with sensitivity of 91% (95%CI 72-99%) and NPV of 95% (95%CI 84-99%). Sensitivity and NPV of PSA + miRNA for the detection of csPCa were not statistically different from the other models including MRI alone. CONCLUSION: MRI stand-alone yielded the best prediction models for both PCa and csPCa detection in biopsy-naïve patients. The use of miRNAs let-7a-5p and miR-103a-3p did not improve classification performances compared to MRI stand-alone results. CLINICAL RELEVANCE STATEMENT: The use of miRNA (let-7a-5p and miR-103a-3p), PSA, and MRI in a clinical decision support system (CDSS) does not improve MRI stand-alone performance in the detection of PCa and csPCa. KEY POINTS: • Clinical decision support systems including MRI improve the detection of both prostate cancer and clinically significant prostate cancer with respect to PSA test and/or microRNA. • The use of miRNAs let-7a-5p and miR-103a-3p did not significantly improve MRI stand-alone performance. • Results of this study were in line with previous works on MRI and microRNA.