Potent and selective tariquidar bioisosters as potential PET radiotracers for imaging P-gp

Using Jupyter Notebooks for re-training machine learning models

Machine learning (ML) models require an extensive, user-driven selection of molecular descriptors in order to learn from chemical structures to predict actives and inactives with a high reliability. In addition, privacy concerns often restrict the access to sufficient data, leading to models with a narrow chemical space. Therefore, we propose a framework of re-trainable models that can be transferred from one local instance to another, and further allow a less extensive descriptor selection. The models are shared via a Jupyter Notebook, allowing the evaluation and implementation of a broader chemical space by keeping most of the tunable parameters pre-defined. This enables the models to be updated in a decentralized, facile, and fast manner. Herein, the method was evaluated with six transporter datasets (BCRP, BSEP, OATP1B1, OATP1B3, MRP3, P-gp), which revealed the general applicability of this approach.

ABC transporters in CSCs membranes as a novel target for treating tumor relapse

CSCs are responsible for the high rate of recurrence and chemoresistance of different types of cancer. The current antineoplastic agents able to inhibit bulk replicating cancer cells and radiation treatment are not efficacious toward CSCs since this subpopulation has several intrinsic mechanisms of resistance. Among these mechanisms, the expression of ATP-Binding Cassette (ABC) transporters family and the activation of different signaling pathways (such as Wnt/β-catenin signaling, Hedgehog, Notch, Akt/PKB) are reported. Therefore, considering ABC transporters expression on CSCs membranes, compounds able to modulate MDR could induce cytotoxicity in these cells disclosing an exciting and alternative strategy for targeting CSCs in tumor therapy. The next challenge in the cure of cancer relapse may be a multimodal strategy, an approach where specific CSCs targeting drugs exert simultaneously the ability to circumvent tumor drug resistance (ABC transporters modulation) and cytotoxic activity toward CSCs and the corresponding differentiated tumor cells. The efficacy of suggested multimodal strategy could be probed by using several scaffolds active toward MDR pumps on CSCs isolated by tumor specimens.

miRNAs for the detection of multidrug resistance: overview and perspectives

The goal of the present paper is to establish and validate the link between cancer diagnosis and therapy by microRNAs detection. The induction in vitro of some specific microRNAs after treatment with MDR ligands has been outlined. Starting from the results obtained by in vitro induction of MDCK and MDCK-MDR1 cells treated by a MDR1 ligand, a new scenario in the early diagnosis and chemotherapy could be disclosed. To corroborate this perspective a short overview on pancreatic cancer diagnosis and chemotherapeutic treatment has been reported.