Aromatase is an enzyme member of the cytochrome P450 superfamily coded by the CYP19A1 gene. Its main action is the conversion of androgens into estrogens, transforming androstenedione into estrone ...and testosterone into estradiol. This enzyme is present in several tissues and it has a key role in the maintenance of the balance of androgens and estrogens, and therefore in the regulation of the endocrine system. With regard to chemical safety and human health, azoles, which are used as agrochemicals and pharmaceuticals, are potential endocrine disruptors due to their agonist or antagonist interactions with the human aromatase enzyme. This theoretical study investigated the active agonist and antagonist properties of "chemical classes of azoles" to determine the relationships of azole interaction with CYP19A1, using stereochemical and electronic properties of the molecules through classification and multilinear regression (MLR) modeling. The antagonist activities for the same substituent on diazoles and triazoles vary with its chemical composition and its position and both heterocyclic systems require aromatic substituents. The triazoles require the spherical shape and diazoles have to be in proper proportion of the branching index and the number of ring systems for the inhibition. Considering the electronic aspects, triazole antagonist activity depends on the electrophilicity index that originates from interelectronic exchange interaction (
) and the LUMO energy ( E LUMO PM 7 ), and the diazole antagonist activity originates from the penultimate orbital ( E HOMONL PM 7 ) of diazoles. The regression models for agonist activity show that it is opposed by the static charges but favored by the delocalized charges on the diazoles and thiazoles. This study proposes that the electron penetration of azoles toward heme group decides the binding behavior and stereochemistry requirement for antagonist activity against CYP19A1 enzyme.
•Lung cancer is a potential risk factor that may increase Covid-19 related complications.•Elderly lung cancer patients are more likely to have Covid-19 related complications.•Our efforts should be ...made to reduce visits to the hospital during the pandemic.
Currently there are no reported series determining the Covid-19 infected lung cancer patient´s characteristics and outcome that allow us to clarify strategies to protect our patients.
In our study we determine whether exists differences in cumulative incidence and severity of Covid-19 infection between lung cancer patients visiting our Medical Oncology department and the reference population of our center (320,000 people), in the current epicenter of the pandemic in Europe (Madrid, Spain). We also describe clinical and demographic factors associated with poor prognosis and Covid-19 treatment outcomes.
We retrospectively reviewed 1878 medical records of all Covid-19 patients who were admitted at Hospital Universitario Infanta Leonor of Madrid between March 5, 2020 and April 7, 2020, in order to detect cumulative incidence of Covid-19 in lung cancer patients.
We also described Covid-19 treatment outcome, mortality and associated risk factors using univariate and multivariate logistic regression analysis.
17/1878 total diagnosis in our center had lung cancer (0.9 %) versus 1878/320,000 of the total reference population (p = 0.09). 9/17 lung cancer patients with Covid-19 diagnosis died (52.3 %) versus 192/1878 Covid-19 patients in our center (p < 0.0001). Dead lung cancer patients were elderly compared to survivors: 72 versus 64.5 years old (p = 0.12). Combined treatment with hydroxychloroquine and azithromycin improves the outcome of Covid-19 in lung cancer patients, detecting only 1/6 deaths between patients under this treatment versus others treatment, with statistical significance in the univariate and multivariate logistic regression (OR 0.04, p = 0.018).
Lung cancer patients have a higher mortality rate than general population. Combined hydroxychloroquine and azithromycin treatment seems like a good treatment option. It is important to try to minimize visits to hospitals (without removing their active treatments) in order to decrease nosocomial transmission.
We conducted a phase I clinical trial of H3B-8800, an oral small molecule that binds Splicing Factor 3B1 (SF3B1), in patients with MDS, CMML, or AML. Among 84 enrolled patients (42 MDS, 4 CMML and 38 ...AML), 62 were red blood cell (RBC) transfusion dependent at study entry. Dose escalation cohorts examined two once-daily dosing regimens: schedule I (5 days on/9 days off, range of doses studied 1-40 mg, n = 65) and schedule II (21 days on/7 days off, 7-20 mg, n = 19); 27 patients received treatment for ≥180 days. The most common treatment-related, treatment-emergent adverse events included diarrhea, nausea, fatigue, and vomiting. No complete or partial responses meeting IWG criteria were observed; however, RBC transfusion free intervals >56 days were observed in nine patients who were transfusion dependent at study entry (15%). Of 15 MDS patients with missense SF3B1 mutations, five experienced RBC transfusion independence (TI). Elevated pre-treatment expression of aberrant transcripts of Transmembrane Protein 14C (TMEM14C), an SF3B1 splicing target encoding a mitochondrial porphyrin transporter, was observed in MDS patients experiencing RBC TI. In summary, H3B-8800 treatment was associated with mostly low-grade TAEs and induced RBC TI in a biomarker-defined subset of MDS.
Human aromatase, also called CYP19A1, plays a major role in the conversion of androgens into estrogens. Inhibition of aromatase is an important target for estrogen receptor (ER)-responsive breast ...cancer therapy. Use of azole compounds as aromatase inhibitors is widespread despite their low selectivity. A toxicological evaluation of commonly used azole-based drugs and agrochemicals with respect to CYP19A1 is currently requested by the European Union- Registration, Evaluation, Authorization and Restriction of Chemicals (EU-REACH) regulations due to their potential as endocrine disruptors. In this connection, identification of structural alerts (SAs) is an effective strategy for the toxicological assessment and safe drug design. The present study describes the identification of SAs of azole-based chemicals as guiding experts to predict the aromatase activity. Total 21 SAs associated with aromatase activity were extracted from dataset of 326 azole-based drugs/chemicals obtained from Tox21 library. A cross-validated classification model having high accuracy (error rate 5%) was proposed which can precisely classify azole chemicals into active/inactive toward aromatase. In addition, mechanistic details and toxicological properties (agonism/antagonism) of azoles with respect to aromatase were explored by comparing active and inactive chemicals using structure-activity relationships (SAR). Lastly, few structural alerts were applied to form chemical categories for read-across applications.
Display omitted
•Structural alerts of azoles have been identified for Human CYP19A1 activity.•SAR analysis distinguished between agonist and antagonist activities of azoles.•2-Amino-benzothiazoles/-1,3 thiazoles associated with the agonist/toxic effects.•Imidazolium ionic liquids were CYP19A1 enzyme inhibitors/antagonists.•Xanthine and β-lactum based drugs, mostly, do not interfere with Human aromatase.
The reduction and replacement of in vivo tests have become crucial in terms of resources and animal benefits. The read-across approach reduces the number of substances to be tested, exploiting ...existing experimental data to predict the properties of untested substances. Currently, several tools have been developed to perform read-across, but other approaches, such as computational workflows, can offer a more flexible and less prescriptive approach. In this paper, we are introducing a workflow to support analogue identification for read-across. The implementation of the workflow was performed using a database of azole chemicals with in vitro toxicity data for human aromatase enzymes. The workflow identified analogues based on three similarities: structural similarity (StrS), metabolic similarity (MtS), and mechanistic similarity (McS). Our results showed how multiple similarity metrics can be combined within a read-across assessment. The use of the similarity based on metabolism and toxicological mechanism improved the predictions in particular for sensitivity. Beyond the results predicting a large population of substances, practical examples illustrate the advantages of the proposed approach.
According to the Consensus Molecular Subtype classification (CMS) in CC, the mesenchymal or CMS4 group is characterized by stromal invasion, extracellular matrix remodeling and TGF-β signaling ...activation. ...our group defined a gene expression profile associated with CAFs with high pro-migratory effects on colon tumor cells, which was associated with patients’ poor prognosis. The combination of the two signatures (50 + 50 genes) did not greatly improve the separation of the survival curves of low- and high-“signature gene score” patients (Fig. 2g), indicating that there was no overlapping gene between the two gene signatures. ...they include features that are closely related or measure similar characteristics in the colon tumors, though from two perspectives: CAF gene deregulation and fibroblasts/other cells’ crosstalk. Since these patients are usually those with worse outcomes, new therapies targeting microenvironment components would improve their clinical management.
Background: Approximately 15% of patients infected by SARS-CoV-2 develop a distress syndrome secondary to a host hyperinflammatory response induced by a cytokine storm. Myelosuppression is associated ...with a higher risk of infections and mortality. There are data to support methods of management for neutropenia and COVID-19. We present a multicenter experience during the first COVID-19 outbreak in neutropenic cancer patients infected by SARS-CoV-2. Methods: Clinical retrospective data were collected from neutropenic cancer patients with COVID-19. Comorbidities, tumor type, stage, treatment, neutropenia severity, G-CSF, COVID-19 parameters, and mortality were analyzed. A bivariate analysis of the impact on mortality was carried out. Additionally, we performed a multivariable logistic regression to predict respiratory failure and death. Results: Among the 943 cancer patients screened, 83 patients (11.3%) simultaneously had neutropenia and an infection with COVID-19. The lungs (26%) and breasts (22%) were the primary locations affected, and most patients had advanced disease (67%). In the logistic model, as adjusted covariates, sex, age, treatment (palliative vs. curative), tumor type, and the lowest level of neutrophils were used. A significant effect was obtained for the number of days of G-CSF treatment (OR = 1.4, 95% CI 1,1,03,92, p-value = 0.01). Conclusions: Our findings suggest that a prolonged G-CSF treatment could be disadvantageous for these cancer patients with infections by COVID-19, with a higher probability of worse outcome.
•Quantitative skin sensitization LLNA EC3 data of organic molecules was collected.•Two-Dimensional descriptors were computed to model the experimental LLNA EC3 data.•Multilinear regression models ...were developed for reactivity domain based categories.•Chemicals with unknown and multiple reactivity alerts were identified and modelled.•A total of eight QSAR models were proposed, for a full dataset of 366 chemicals.
Allergic contact dermatitis is increasingly of interest for the hazard characterization of chemicals. in vivo animal testing is usually adopted but in silico approaches are becoming the new frontier due to their swiftness and economic efficiency. Indeed, in silico models can rationalise the experimental outcomes besides having predictive ability. The aim of the present work was to explore the electrophilic chemical behaviour responsible for allergic contact dermatitis using quantitative QSAR regression models. Eight models were proposed, using an experimental LLNA dataset of 366 chemicals. Each model is unique to encode a type of electrophilic reactivity domain. The models were obtained using autocorrelation, electro-topological and atom centered fragment based on two-dimensional descriptors, which incorporated the electronic and stereochemical features of substances interacting with skin proteins to induce skin cell proliferation. Finally, simple steps were proposed to integrate the eight models for the application on the test chemicals.
The ABCB1 transporter also known as P-glycoprotein (P-gp) is a transmembrane protein belonging to the ATP binding cassette super-family of transporters; it is a xenobiotic efflux pump that limits ...intracellular drug accumulation by pumping the compounds out of cells. P-gp contributes to a decrease of toxicity and possesses broad substrate specificity. It is involved in the failure of numerous anticancer and antiviral chemotherapies due to the multidrug resistance (MDR) phenomenon, where it removes the chemotherapeutics out of the targeted cells. Understanding the details of the ligand-P-gp interaction is therefore crucial for the development of drugs that might overcome the MRD phenomenon and for obtaining a more effective prediction of the toxicity of certain compounds. In this work, an in silico modeling was performed using homology modeling and molecular docking methods with the aim of better understanding the ligand-P-gp interactions. Based on different mouse P-gp structural templates from the PDB repository, a 3D model of the human P-gp (
P-gp) was constructed by means of protein homology modeling. The homology model was then used to perform molecular docking calculations on a set of thirteen compounds, including some well-known compounds that interact with P-gp as substrates, inhibitors, or both. The sum of ranking differences (SRD) was employed for the comparison of the different scoring functions used in the docking calculations. A consensus-ranking scheme was employed for the selection of the top-ranked pose for each docked ligand. The docking results showed that a high number of π interactions, mainly π-sigma, π-alkyl, and π-π type of interactions, together with the simultaneous presence of hydrogen bond interactions contribute to the stability of the ligand-protein complex in the binding site. It was also observed that some interacting residues in
P-gp are the same when compared to those observed in a co-crystallized ligand (PBDE-100) with mouse P-gp (PDB ID: 4XWK). Our in silico approach is consistent with available experimental results regarding P-gp efflux transport assay; therefore it could be useful in the prediction of the role of new compounds in systemic toxicity.
PDF
