A new pharmacogenetic algorithm to predict the most appropriate dosage of acenocoumarol for stable anticoagulation in a mixed Spanish population

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.There is a strong association between genetic polymorphisms and the acenocoumarol dosage requirements. Genotyping the polymorphisms involved in the pharmacokinetics and pharmacodynamics of acenocoumarol before starting anticoagulant therapy would result in a better quality of life and a more efficient use of healthcare resources. The objective of this study is to develop a new algorithm that includes clinical and genetic variables to predict the most appropriate acenocoumarol dosage for stable anticoagulation in a wide range of patients. We recruited 685 patients from 2 Spanish hospitals and 1 primary healthcare center. We randomly chose 80% of the patients (n = 556), considering an equitable distribution of genotypes to form the generation cohort. The remaining 20% (n = 129) formed the validation cohort. Multiple linear regression was used to generate the algorithm using the acenocoumarol stable dosage as the dependent variable and the clinical and genotypic variables as the independent variables. The variables included in the algorithm were age, weight, amiodarone use, enzyme inducer status, international normalized ratio target range and the presence of CYP2C9∗2 (rs1799853), CYP2C9∗3 (rs1057910), VKORC1 (rs9923231) and CYP4F2 (rs2108622). The coefficient of determination (R2) explained by the algorithm was 52.8% in the generation cohort and 64% in the validation cohort. The following R2 values were evaluated by pathology: atrial fibrillation, 57.4%; valve replacement, 56.3%; and venous thromboembolic disease, 51.5%. When the patients were classified into 3 dosage groups according to the stable dosage (<11 mg/week, 11-21 mg/week, >21 mg/week), the percentage of correctly classified patients was higher in the intermediate group, whereas differences between pharmacogenetic and clinical algorithms increased in the extreme dosage groups. Our algorithm could improve acenocoumarol dosage selection for patients who will begin treatment with this drug, especially in extreme-dosage patients. The predictability of the pharmacogenetic algorithm did not vary significantly between diseases.This study was funded by a grant from the Spanish Ministry of Health and Social Policy (Instituto de Salud Carlos III, PI07/0710) and the Andalusian Regional Ministry of Health (Progress and Health Foundation, PI-0717-2013

Stratification of radiosensitive brain metastases based on an actionable S100A9/RAGE resistance mechanism

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Whole-brain radiotherapy (WBRT) is the treatment backbone for many patients with brain metastasis; however, its efficacy in preventing disease progression and the associated toxicity have questioned the clinical impact of this approach and emphasized the need for alternative treatments. Given the limited therapeutic options available for these patients and the poor understanding of the molecular mechanisms underlying the resistance of metastatic lesions to WBRT, we sought to uncover actionable targets and biomarkers that could help to refine patient selection. Through an unbiased analysis of experimental in vivo models of brain metastasis resistant to WBRT, we identified activation of the S100A9-RAGE-NF-κB-JunB pathway in brain metastases as a potential mediator of resistance in this organ. Targeting this pathway genetically or pharmacologically was sufficient to revert the WBRT resistance and increase therapeutic benefits in vivo at lower doses of radiation. In patients with primary melanoma, lung or breast adenocarcinoma developing brain metastasis, endogenous S100A9 levels in brain lesions correlated with clinical response to WBRT and underscored the potential of S100A9 levels in the blood as a noninvasive biomarker. Collectively, we provide a molecular framework to personalize WBRT and improve its efficacy through combination with a radiosensitizer that balances therapeutic benefit and toxicity.info:eu-repo/semantics/publishedVersio

Patients correctly classified (predicted dose within ± 20% of actual dosage) and MAE from the entire cohort (n = 682) by genetic and clinical algorithms according to dosage groups.

<p>Patients correctly classified (predicted dose within ± 20% of actual dosage) and MAE from the entire cohort (n = 682) by genetic and clinical algorithms according to dosage groups.</p

Patients characteristics in the generation (n = 556) and validation (n = 129) cohorts.

<p>Patients characteristics in the generation (n = 556) and validation (n = 129) cohorts.</p

Patients correctly classified (predicted dose within ± 20% of the actual dosage) by genetic and clinical algorithms in the generation, validation and entire cohorts (n = 682).

<p>Patients correctly classified (predicted dose within ± 20% of the actual dosage) by genetic and clinical algorithms in the generation, validation and entire cohorts (n = 682).</p

Predictive performance of the pharmacogenetic algorithm by disease in the entire cohort (n = 682).

<p>Predictive performance of the pharmacogenetic algorithm by disease in the entire cohort (n = 682).</p

Pharmacogenetic and clinical algorithms.

<p>Pharmacogenetic and clinical algorithms.</p

Predictive performance of the pharmacogenetic and clinical algorithms in the generation, validation and entire cohorts.

<p>Predictive performance of the pharmacogenetic and clinical algorithms in the generation, validation and entire cohorts.</p

Usefulness of the identification of antibodies in peripheral neuropathies, neuronopathies and ganglionopathies: review

Introducción: En los últimos anos ˜ la identificación de anticuerpos y gammapatías monoclonales ha permitido comprender la fisiopatología y favorecer el diagnóstico y tratamiento de una multiplicidad de neuropatías inmunomediadas. Objetivo: Describir los anticuerpos de mayor relevancia clínica en las neuropatías, ganglionopatías y neuronopatías inmunomediadas caracterizando en cada caso su valor fisiopatológico o diagnóstico, así como la sensibilidad y especificidad de los métodos utilizados para su determinación. Desarrollo: Se analizarán los anticuerpos identificados en 1) síndrome de Guillain-Barré; 2) polineuropatía inflamatoria desmielinizante crónica (PDIC), 3) neuropatía motora con bloqueo multifocal (NMM); 4) CANOMAD (neuropatía atáxica crónica, oftalmoplejía, proteína IgM monoclonal, aglutininas frías y anticuerpos disialosil); 5) ganglionopatías y neuronopatías y la utilidad de identificar las gammapatías monoclonales. Conclusiones: Los anticuerpos y las gammapatías monoclonales son herramientas que han permitido mejorar el diagnóstico y la comprensión fisiopatológica de las neuropatías inmunomediadas y algunas criptogénicas, así como orientar el tratamiento más adecuado.Introduction: Over the last several years the identification of both antineural antibodies and monoclonal gammopathies allowed a better understanding of pathophysiology and improvement in the diagnosis and treatment of many different immune mediated neuropathies. Objective: To describe the antineural antibodies of greater clinical utility in the diagnosis of immune mediated neuropathies and neuronopathies. In each case we underline their value in either the pathophysiology or diagnosis of these disorders as well as the sensitivity and specificity of the diagnostic techniques currently in use. Development: We will review the antibodies identified in 1) Guillain-Barré syndrome; 2) Chronic inflammatory demyelinating polyneuropathy (CIDP); 3) Multifocal motor neuropathy (MMN); 4) Chronic Ataxic Neuropathy Ophthalmoplegia M-protein Agglutination Disialosyl antibodies syndrome (CANOMAD); 5) Ganglionopathies and Neuropathies and the value of identifying monoclonal gammopathies. Conclusions: The antibodies and monoclonal gammopathies are useful tools in both the diagnosis and understanding of the mechanisms involved in immune mediated and cryptogenic neuropathies and orienting treatment.Fil: Reisin, Ricardo C.. Hospital Británico de Buenos Aires; ArgentinaFil: Salutto, Valeria Luján. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Aguirre, Florencia. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Alvarez, Valeria. Hospital Italiano. Departamento de Medicina. Servicio de Neurologia.; ArgentinaFil: Barroso, Fabio. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Bendersky, Mariana. Hospital Italiano. Departamento de Medicina. Servicio de Neurologia.; ArgentinaFil: Berardo, Andrés. Columbia University; Estados UnidosFil: Bettini, Mariela. Hospital Italiano; ArgentinaFil: Borrelli, Mariano M.. Ministerio de Defensa. Ejército Argentino. Hospital Militar Central Cirujano Mayor "Dr. Cosme Argerich"; ArgentinaFil: Chaves, Marcelo. Hospital San Martín de Paraná; ArgentinaFil: Cisneros, Elisa M.. Complejo Medico Policial Bartolome Churruca Andres Visca; ArgentinaFil: Conti, Eugenia. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; ArgentinaFil: Crespo, José M.. Hospital Británico de Buenos Aires; ArgentinaFil: di Egidio, Mariana. Hospital Enrique Tornú; ArgentinaFil: Figueredo, María Alejandra. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal de Agudos San Roque de Gonnet; ArgentinaFil: Gargiulo Monachelli, Gisella Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. CEMIC-CONICET. Centro de Educaciones Médicas e Investigaciones Clínicas "Norberto Quirno". CEMIC-CONICET; ArgentinaFil: Jáuregui, Agustín. Universidad Favaloro; ArgentinaFil: Landriscina, Paula. Instituto de Neurociencias Buenos Aires S. A.; ArgentinaFil: León Cejas, Luciana. Hospital Británico de Buenos Aires; ArgentinaFil: Martínez Perea, María del Carmen. Hospital Rivadavia; ArgentinaFil: Pirra, Laura. Universidad Favaloro; ArgentinaFil: Pivetta, Paola. Complejo Medico Policial Bartolome Churruca Andres Visca; ArgentinaFil: Quarracino, Cecilia. Complejo Medico Policial Bartolome Churruca Andres Visca; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rattagan, María Lucía. Hospital Italiano; ArgentinaFil: Rey, Roberto. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal General de Agudos Presidente Peron; ArgentinaFil: Rodriguez, Alejandro. Instituto de Neurociencias Buenos Aires S. A.; ArgentinaFil: Rodriguez, Gabriel E.. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; ArgentinaFil: Rugiero, Marcelo. Hospital Italiano; ArgentinaFil: Tillard, Belen. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Zuberhbuler, Paz. Hospital Alvarez; Argentin