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Little is known about the biological functions which are exerted by hormone receptors in physiological conditions. Here, we made use of the Mouse INtraDuctal (MIND) model, an innovative patient-derived xenograft (PDX) model, to characterize global gene expression changes, which are triggered by stimulation of dihydrotestosterone (DHT) and progesterone (P4) in vivo. Fast and clever mathematical tools are needed to analyze increasing numbers of complex datasets. We generated hormone receptor-specific list of genes which were then used to test the classification performance obtained by different machine-learning algorithms in the frame of our labelled PDXs RNAseq dataset. Next to other standard techniques, we consider the variably scaled kernel (VSK) setting in the framework of support vector machines. Our results show that mixed schemes obtained via VSKs can outperform standard classification methods in the considered task.

In the context of hormonal contraception and hormone replacement therapy (HRT), many women are exposed to exogenous hormones. Current use of hormonal contraception with combined ethinyl estradiol and different progestins bestows a breast cancer relative risk (RR) of 1.2-while combined HRT has a RR of 2. Although these exposures present an important public health issue, little is known about the effects of individual progestins on the breast and other tissues. Increasing availability of large scale biobanks, high throughput analyses and data management tools enable ever expanding, sophisticated population studies. In order to address the impact of distinct progestins on various health indicators, it is desirable to accurately quantify progestins in clinical samples. Here we have developed and validated a high resolution liquid chromatography mass spectrometry (LC-MS) targeted method for the simultaneous quantification of 11 synthetic progestins widely used in oral contraceptives, gestodene, levonorgestrel, etonogestrel, chlormadinone acetate, cyproterone acetate, drospirenone, desacetyl norgestimate, medroxyprogesterone acetate, norethindrone, dienogest, nomegestrol acetate, and 4 endogenous steroid hormones, progesterone, testosterone, androstenedione, and cortisol in blood samples. This highly specific quantitative analysis with high resolution Orbitrap technology detects and quantifies 15 compounds using their internal standard counterparts in a single 12 min LC-MS run. Sensitivity is attained by the use of the instrument in targeted selected ion monitoring mode. Lower limit of quantitation ranges from 2.4 pg/ml for drospirenone to 78.1 pg/ml for chlormadinone acetate. The method provides comprehensive progestin panel measurements with as little as 50 pi of murine or human plasma. (C) 2019 The Authors. Published by Elsevier B.V.

// Assunta Adamo 1 , Danilo Fiore 1 , Fabio De Martino 1 , Giuseppina Roscigno 1, 2 , Alessandra Affinito 1 , Elvira Donnarumma 3 , Ilaria Puoti 1 , Lucia Ricci Vitiani 4 , Roberto Pallini 5 , Cristina Quintavalle 1 , Gerolama Condorelli 1, 2 1 Department of Molecular Medicine and Medical Biotechnology, “Federico II” University of Naples, Naples, Italy 2 IEOS, CNR, Naples, Italy 3 IRCCS-SDN, Naples, Italy 4 Department of Hematology, Oncology and Molecular Medicine, Istituto Superiore di Sanita, Rome, Italy 5 Institute of Neurosurgery, Universita Cattolica del Sacro Cuore, Rome, Italy Correspondence to: Gerolama Condorelli, email: gecondor@unina.it Keywords: glioblastoma, stem cells, ryk, β-catenin Received: September 06, 2016 Accepted: December 27, 2016 Published: January 09, 2017 ABSTRACT Glioblastoma multiforme (GBM) is characterized by a strong self-renewal potential and a poor differentiation state. Since receptor-like tyrosine kinase (RYK) activates the WNT/β-catenin pathway essential for cancer stem cell maintenance, we evaluated its contribution in conferring stemness to GBM cells. Here, we report that Ryk (related-to-receptor tyrosine kinase), an atypical tyrosine kinase receptor, is upregulated in samples from GBM patients as well as in GSCs. Ryk overexpression confers stemness properties to GBM cells through the modulation of the canonical Wnt signaling and by promoting the activation of pluripotency-related transcription factor circuitry and neurosphere formation ability. In contrast, siRNA-mediated knockdown of Ryk expression suppresses this stem-like phenotype. Rescue experiments reveal that stemness-promoting activity of Ryk is attributable, at least in part, to β-catenin stabilization. Furthermore, Ryk overexpression improves cell motility and anchorage independent cell growth. Taken together, our findings demonstrate that Ryk promotes stem cell-like and tumorigenic features to glioma cells its essential for the maintenance of GSCs and could be a target of novel therapies.

Glioblastoma is the most common primary brain tumor in adults; with a survival rate of 12 months from diagnosis. However, a small subgroup of patients, termed long-term survivors (LTS), has a survival rate longer then 12–14 months. There is thus increasing interest in the identification of molecular signatures predicting glioblastoma prognosis and in how to improve the therapeutic approach. Here, we report miR-340 as prognostic tumor-suppressor microRNA for glioblastoma. We analyzed microRNA expression in > 500 glioblastoma patients and found that although miR-340 is strongly down-regulated in glioblastoma overall, it is up-regulated in LTS patients compared to short-term survivors (STS). Indeed, miR-340 expression predicted better prognosis in glioblastoma patients. Coherently, overexpression of miR-340 in glioblastoma cells was found to produce a tumor-suppressive activity. We identified NRAS mRNA as a critical, direct target of miR-340: in fact, miR-340 negatively influenced multiple aspects of glioblastoma tumorigenesis by down-regulating NRAS and downstream AKT and ERK pathways. Thus, we demonstrate that expression of miR-340 in glioblastoma is responsible for a strong tumor-suppressive effect in LTS patients by down-regulating NRAS. miR-340 may thus represent a novel marker for glioblastoma diagnosis and prognosis, and may be developed into a tool to improve treatment of glioblastoma.

Serum thyroid hormone concentrations increase after radioiodine (RAI) therapy for Graves’ disease. This phenomenon has been ascribed to either antithyroid drug withdrawal before RAI therapy or release of preformed thyroid hormones into the bloodstream from the RAI-damaged thyroid. Lithium blocks the release of iodine and thyroid hormones from the thyroid, thus enhancing the effectiveness of RAI therapy. Changes in serum-free thyroxine (FT4) and triiodothyronine (FT3) levels after methimazole (MMI) discontinuation and RAI therapy were evaluated in a prospective, randomized, control study of 36 patients with Graves’ disease. After a 3- to 4-month course of MMI, patients were assigned to one of three groups: G1 (RAI alone); G2 (RAI plus lithium for 6 d starting on the day of RAI therapy); or G3 (RAI plus lithium for 19 d starting on the day of MMI withdrawal). G1-G2 patients had an increase in serum FT4 and FT3 levels from 13.5 6.5 to 19.8 9.2 pmol/liter and 5.0 2.0 to 8.0 4.8 pmol/liter, respectively (P < 0.0001), 2–5 d after MMI withdrawal, but G3 patients showed no changes. In the 30 d after RAI therapy, mean serum FT4 values increased in G1 patients (P 0.02), peaking at 3–7 d( P < 0.05) but not in G2 and G3 patients. Serum FT3 levels decreased in G1, G2, and G3 (P 0.03, P 0.001, P 0.02, respectively). Hyperthyroidism was cured in 8 of 12 G1 patients, 11 of 12 G2 patients, and 11 of 12 G3 patients (P 0.31). Control of hyperthyroidism was prompter in G2 (P 0.08) and G3 (P < 0.05) than in G1 patients. Patients in the three groups received a similar dose of RAI, but the committed radiation to the thyroid was higher in G3 (563 174 Gray) and G2 (588 347 Gray) than in G1 (429 204 Gray) (P < 0.03). In conclusion, the results of the present study demonstrate that: 1) MMI withdrawal is associated with a slight rise in serum thyroid hormone levels; 2) a further increase occurs after RAI therapy; 3) changes in serum thyroid hormone concentrations are prevented by lithium; and 4) the increased effectiveness of RAI therapy in lithium-treated patients is related to the increased RAI retention in the thyroid gland. Accordingly, a short course of lithium therapy can be considered a useful adjunct to RAI therapy to obtain a prompter control of thyrotoxicosis and avoid its transient exacerbation because of MMI withdrawal and RAI administration. (J Clin Endocrinol Metab 87: 4490 – 4495, 2002)

Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis generated with such models is often confounded by the presence of host cells and can give rise to data misinterpretation. For instance, it is important to discriminate between xenografted and host cells in histological sections prior to performing immunostainings. We developed Single Cell Classifier (SCC), a data-driven deep learning-based computational tool that provides an innovative approach for automated cell species discrimination based on a multi-step process entailing nuclei segmentation and single cell classification. We show that human and murine cell contextual features, more than cell-intrinsic ones, can be exploited to discriminate between cell species in both normal and malignant tissues, yielding up to 96% classification accuracy. SCC will facilitate the interpretation of H&E- and DAPI-stained histological sections of xenografted human-in-mouse tissues and it is open to new in-house built models for further applications. SCC is released as an open-source plugin in ImageJ/Fiji available at the following link: https://github.com/Biomedical-Imaging-Group/SingleCellClassifier.