Elucidating the role of PRMTs in prostate cancer using open access databases and a patient cohort dataset.

Protein arginine methylation is an understudied epigenetic mechanism catalyzed by enzymes known as Protein Methyltransferases of Arginine (PRMTs), while the opposite reaction is performed by Jumonji domain- containing protein 6 (JMJD6). There is increasing evidence that PRMTs are deregulated in prostate cancer (PCa). In this study, the expression of two PRMT members, PRMT2 and PRMT7 as well as JMJD6, a demethylase, was analyzed in PCa. Initially, we retrieved data from The Cancer Genome Atlas (TCGA) project and the Gene Expression Omnibus (GEO) database to explore the differential expression of various PRMT family members in patients with PCa and then applied immunohistochemistry in a patient cohort across the spectrum of PCa, including non-neoplastic prostate tissue and lymph node metastatic foci. The results from the TCGA analysis revealed that PRMT7, PRMT6 and PRMT3 expression increased while PRMT2, PRMT9 and JMJD6 levels decreased in the tumor compared to non-neoplastic prostate. Results from the GEO datasets were similar, albeit not identical with the TCGA results, with PRMT7 and PRMT3 being upregulated and PRMT2 and JMJD6 being downregulated in the tumor compared to non-neoplastic tissue in some of them. In addition, PRMT7 levels decreased with stage and grade progression in the TCGA analysis. In the patient cohort, both PRMTs and JMJD6 were overexpressed in PCa compared to non-neoplastic tissue, and nuclear PRMT2 and JMJD6 were upregulated in lymph node metastasis, too. PRMT7 and JMJD6 expression were upregulated with the progression of stage and JMJD6 was also increased with the elevation of grade. After androgen ablation therapy, nuclear expression of PRMT7 and JMJD6 were elevated compared to untreated tumors. PRMT2, PRMT7 and JMD6 were also correlated with markers of EMT and cell cycle regulators. Finally, our findings indicate that PRMTs and JMJD6 are involved in prostate cancer progression and revealed a potential interplay of PRMTs with EMT mediators, underscoring the need for therapeutic targeting of arginine methylation in prostate cancer.

Discovering NDM-1 inhibitors using molecular substructure embeddings representations.

NDM-1 (New-Delhi-Metallo-ß-lactamase-1) is an enzyme developed by bacteria that is implicated in bacteria resistance to almost all known antibiotics. In this study, we deliver a new, curated NDM-1 bioactivities database, along with a set of unifying rules for managing different activity properties and inconsistencies. We define the activity classification problem in terms of Multiple Instance Learning, employing embeddings corresponding to molecular substructures and present an ensemble ranking and classification framework, relaying on a k-fold Cross Validation method employing a per fold hyper-parameter optimization procedure, showing promising generalization ability. The MIL paradigm displayed an improvement up to 45.7 %, in terms of Balanced Accuracy, in comparison to the classical Machine Learning paradigm. Moreover, we investigate different compact molecular representations, based on atomic or bi-atomic substructures. Finally, we scanned the Drugbank for strongly active compounds and we present the top-15 ranked compounds.

Validation of Patras Immunotherapy Score model for prediction and prognosis of patients with advanced NSCLC treated with nivolumab or pembrolizumab: results from a European multicentre study.

Background: Recently, the Patras Immunotherapy Score (PIOS) has been developed to estimate the survival benefit of patients with advanced non-small-cell lung cancer (aNSCLC) treated with nivolumab or pembrolizumab. The aim of this study was to validate the clinical value of PIOS in an external cohort of aNSCLC patients. Methods: PIOS is a baseline formula produced by the combination of performance status, body mass index, age and line of treatment. In this multicentre study, 626 patients with confirmed NSCLC pathology, who had been treated with nivolumab or pembrolizumab, as well as 444 patients with aNSCLC, who had been managed with chemotherapy alone, were retrospectively enrolled. Predictive and prognostic values of PIOS were finally evaluated. Results: Patients treated with immunotherapy and higher PIOS score had an improved progression-free survival not only in univariate [hazard ratio (HR) = 0.621, p = 0.001], but also in multivariable analysis (HR = 0.651, p = 0.003). In addition, improved overall survival with increasing PIOS score was also observed (HR = 0.608, p < 0.001) with this association remaining statistically significant after adjusting for programmed-cell death ligand 1 (PD-L1) expression (HR = 0.620, p < 0.001). In addition, patients with disease progression (PD) had lower scores compared to those with stable disease (SD), partial response (PR) or complete response (CR) in a two-tier model (p < 0.001) as well as in a four-tier model (PD, SD, PR and CR; p < 0.001). Prognostic significance of PIOS score also persisted using a binary logistic regression analysis, adjusted for disease stage and PD-L1 status (p = 0.002, odds ratio: 0.578). Contrarily, PIOS had no prognostic significance in the chemotherapy group; however, upon combined analysis of the two cohorts, PIOS was found to have a significant interaction with the type of treatment (HR = 0.066 with p < 0.001), confirming its predictive value for immunotherapy. Conclusions: This study provides further validation of PIOS in aNSCLC patients treated with anti-PD-1 monotherapy.