Characterization of new molecular targets involved in iodide flux in the thyroid gland: the anoctamins

Iodide transport is necessary for the synthesis of thyroid hormones following accumulation in the follicular lumen out of thyroid cells, via channels unknown with the exception of pendrin. According to our hypothesis, TMEM16A could be the main molecular identity of the channel mediating iodide efflux in the thyroid gland. TMEM16A is the prior candidate for calcium-activated chloride conductance (CaCC). TMEM16A belongs to the TMEM16/anoctamin family comprising ten members (TMEM16A-K). Higher affinity of TMEM16A for iodide and predicted expression in the thyroid gland suggest its mediation of iodide efflux. The aim of this project was to identify the role of TMEM16A in iodide transport in the thyroid gland, by characterizing its molecular expression and functional properties. We demonstrated that TMEM16F, H, K transcripts are expressed in FRTL-5 thyroid cells, as well as TMEM16A, which is TSH-independent. Tumor tissue from human thyroid maintains TMEM16A expression. Functional in vivo experiments in FRTL-5, stably expressing YFP-H148Q/I152L fluorescent protein as a biosensor, showed that iodide efflux is stimulated by agonists of purinergic receptors with an order of potency of ATP>UTP>ADP (compatible with an involvement of P2Y purinergic receptors), and by agonists of adrenergic receptors (epinephrine, norepinephrine and phenylephrine). Iodide efflux was blocked by α-receptor antagonists prazosin and phentolamine, consistent with a role of α1 adrenergic receptors. Iodide efflux was specifically dependent on calcium mobilized from intracellular compartments and induced by the calcium ionophore ionomycin. CaCC blockers suppressed ionomycin-/ATP-/epinephrine-stimulated iodide efflux. Heterologous expression of TMEM16A in CHO K1 cells induced calcium-activated iodide fluxes. All these results support the hypothesis of the involvement of TMEM16A in calcium-dependent iodide efflux induced by receptor agonists in thyroid cells. TMEM16A may represent a new pharmacological target for thyroid cancer therapy, since its blockade may enhance the retention of radioiodide by tumour cells enhancing the efficacy of radioablative therapy.

Design and synthesis of multipotent drugs: application to Alzheimer's disease and benign prostatic hyperplasia

The aim of this thesis was to synthesize multipotent drugs for the treatment of Alzheimer’s disease (AD) and for benign prostatic hyperplasia (BPH), two diseases that affect the elderly. AD is a neurodegenerative disorder that is characterized, among other factors, by loss of cholinergic neurons. Selective activation of M1 receptors through an allosteric site could restore the cholinergic hypofunction, improving the cognition in AD patients. We describe here the discovery and SAR of a novel series of quinone derivatives. Among them, 1 was the most interesting, being a high M1 selective positive allosteric modulator. At 100 nM, 1 triplicated the production of cAMP induced by oxotremorine. Moreover, it inhibited AChE and it displayed antioxidant properties. Site-directed mutagenesis experiments indicated that 1 acts at an allosteric site involving residue F77. Thus, 1 is a promising drug because the M1 activation may offer disease-modifying properties that could address and reduce most of AD hallmarks. BPH is an enlargement of the prostate caused by increased cellular growth. Blockade of α1-ARs is the predominant form of medical therapy for the treatment of the symptoms associated with BPH. α1-ARs are classified into three subtypes. The α1A- and α1D-AR subtypes are predominant in the prostate, while α1B-ARs regulate the blood pressure. Herein, we report the synthesis of quinazoline-derivatives obtained replacing the piperazine ring of doxazosin and prazosin with (S)- or (R)-3-aminopiperidine. The presence of a chiral center in the 3-C position of the piperidine ring allowed us to exploit the importance of stereochemistry in the binding at α1-ARs. It turned out that the S configuration at the 3-C position of the piperidine increases the affinity of the compounds at all three α1-AR subtypes, whereas the configuration at the benzodioxole ring of doxazosin derivatives is not critical for the interaction with α1-ARs.

Identificazione e classificazione delle lesioni endocavitarie uterine dalle immagini isteroscopiche con il deep learning

Anche se l'isteroscopia con la biopsia endometriale è il gold standard nella diagnosi della patologia intracavitaria uterina, l'esperienza dell’isteroscopista è fondamentale per una diagnosi corretta. Il Deep Learning (DL) come metodica di intelligenza artificiale potrebbe essere un aiuto per superare questo limite. Sono disponibili pochi studi con risultati preliminari e mancano ricerche che valutano le prestazioni dei modelli di DL nell'identificazione delle lesioni intrauterine e il possibile aiuto derivato dai fattori clinici. Obiettivo: Sviluppare un modello di DL per identificare e classificare le patologie endocavitarie uterine dalle immagini isteroscopiche. Metodi: È stato eseguito uno studio di coorte retrospettivo osservazionale monocentrico su una serie consecutiva di casi isteroscopici di pazienti con patologia intracavitaria uterina confermata all’esame istologico eseguiti al Policlinico S. Orsola. Le immagini isteroscopiche sono state usate per costruire un modello di DL per la classificazione e l'identificazione delle lesioni intracavitarie con e senza l'aiuto di fattori clinici (età, menopausa, AUB, terapia ormonale e tamoxifene). Come risultati dello studio abbiamo calcolato le metriche diagnostiche del modello di DL nella classificazione e identificazione delle lesioni uterine intracavitarie con e senza l'aiuto dei fattori clinici. Risultati: Abbiamo esaminato 1.500 immagini provenienti da 266 casi: 186 pazienti avevano lesioni focali benigne, 25 lesioni diffuse benigne e 55 lesioni preneoplastiche/neoplastiche. Sia per quanto riguarda la classificazione che l’identificazione, le migliori prestazioni sono state raggiunte con l'aiuto dei fattori clinici, complessivamente con precision dell'80,11%, recall dell'80,11%, specificità del 90,06%, F1 score dell’80,11% e accuratezza dell’86,74% per la classificazione. Per l’identificazione abbiamo ottenuto un rilevamento complessivo dell’85,82%, precision 93,12%, recall del 91,63% ed F1 score del 92,37%. Conclusioni: Il modello DL ha ottenuto una bassa performance nell’identificazione e classificazione delle lesioni intracavitarie uterine dalle immagini isteroscopiche. Anche se la migliore performance diagnostica è stata ottenuta con l’aiuto di fattori clinici specifici, questo miglioramento è stato scarso.