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© The Author(s) 2020., PAX5 is one of the most frequently mutated genes in B-cell acute lymphoblastic leukemia (B-ALL), and children with inherited preleukemic PAX5 mutations are at a higher risk of developing the disease. Abnormal profiles of inflammatory markers have been detected in neonatal blood spot samples of children who later developed B-ALL. However, how inflammatory signals contribute to B-ALL development is unclear. Here, we demonstrate that Pax5 heterozygosis, in the presence of infections, results in the enhanced production of the inflammatory cytokine interleukin-6 (IL-6), which appears to act in an autocrine fashion to promote leukemia growth. Furthermore, in vivo genetic downregulation of IL-6 in these Pax5 heterozygous mice retards B-cell leukemogenesis, and in vivo pharmacologic inhibition of IL-6 with a neutralizing antibody in Pax5 mutant mice with B-ALL clears leukemic cells. Additionally, this novel IL–6 signaling paradigm identified in mice was also substantiated in humans. Altogether, our studies establish aberrant IL6 expression caused by Pax5 loss as a hallmark of Pax5-dependent B-ALL and the IL6 as a therapeutic vulnerability for B-ALL characterized by PAX5 loss., We would also like to thank all members of our groups for useful suggestions and for their critical reading of the manuscript. Research at G.C.’s laboratory was supported by Italian Association for Cancer Research (grant IG-17593 to GC) and Fondazione Cariplo (grant 2018-0339 to CP). Research at CC’s laboratory was partially supported by FEDER, EU, MINECO (SAF2017-83061-R), the “Fundación Ramón Areces,” a Research Contract with the “Fundación Síndrome de Wolf-Hirschhorn o 4p-”, and institutional grants from the “Fundación Ramón Areces” and “Banco de Santander” to the CBMSO. Research in the CVD group is partially supported by FEDER, “Miguel Servet” Grant (CPII19/00024—AES 2017-2020) from the Instituto de Salud Carlos III (Ministerio de Economía y Competitividad), “Fondo de Investigaciones Sanitarias/Instituto de Salud Carlos III” (PI17/00167). Research in the ISG group is partially supported by FEDER and by SAF2015-64420-R MINECO/FEDER, UE, RTI2018-093314-B-I00 MCIU/AEI/FEDER, UE, by Junta de Castilla y León (UIC-017, CSI001U16, and CSI234P18), and by the German Jose Carreras Foundation (DJCLS R13/26; DJCLS 07R/2019). CVD, and ISG have been supported by the German Federal Office for Radiation Protection (BfS)-Germany (FKZ: 3618S32274). M.R.O., and ISG have been supported by the Fundacion Unoentrecienmil (CUNINA project). Research in the A.O. group is partially supported by "Fondo de Investigaciones Sanitarias/Instituto de Salud Carlos III" - FEDER-Ministerio de Economía y Competitividad (PI19/01183). AC-G and M.I.-H. are supported by FSE-Conserjería de Educación de la Junta de Castilla y León 2019 and 2020 (ESF- European Social Fund) fellowship, respectively. J.R.-G. is supported by a scholarship from University of Salamanca co-financed by Banco Santander and ESF.

Like physics in the 19th century, biology and molecular biology in particular, has been fertilized and enhanced like few other scientific fields, by the incorporation of mathematical methods. In the last decades, a whole new scientific field, bioinformatics, has developed with an output of over 30,000 papers a year (Pubmed search using the keyword “bioinformatics”). Huge databases of mass throughput data have been established, with ArrayExpress alone containing more than 2.7 million assays (October 2019). Computational methods have become indispensable tools in molecular biology, particularly in one of the most challenging areas of cancer research, multidrug resistance (MDR). However, confronted with a plethora of different algorithms, approaches, and methods, the average researcher faces key questions: Which methods do exist? Which methods can be used to tackle the aims of a given study? Or, more generally, how do I use computational biology/bioinformatics to bolster my research? The current review is aimed at providing guidance to existing methods with relevance to MDR research. In particular, we provide an overview on: a) the identification of potential biomarkers using expression data; b) the prediction of treatment response by machine learning methods; c) the employment of network approaches to identify gene/protein regulatory networks and potential key players; d) the identification of drug-target interactions; e) the use of bipartite networks to identify multidrug targets; f) the identification of cellular subpopulations with the MDR phenotype; and, finally, g) the use of molecular modeling methods to guide and enhance drug discovery. This review shall serve as a guide through some of the basic concepts useful in MDR research. It shall give the reader some ideas about the possibilities in MDR research by using computational tools, and, finally, it shall provide a short overview of relevant literature. © 2019

Contains fulltext : 155330.pdf (Publisher’s version ) (Open Access) In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.

Las metástasis óseas representan un problema clínico devastador en las neoplasias más frecuentes, especialmente en el mieloma múltiple, mama, próstata, y pulmón. Las consecuencias incluyen dolores refractarios a analgésicos convencionales, osteolisis que conlleva en ocasiones compresión medular, fracturas patológicas, y trastornos metabólicos. Recientes avances en el diagnóstico mediante técnicas de imagen, así como diversas técnicas bioquímicas, han favorecido un certero diagnóstico y seguimiento. El aumento de la supervivencia se ha mejorado mediante una aproximación multimodal en los tratamientos con la combinación de la inhibición de la osteolisis, la cirugía ortopédica profiláctica y la radioterapia. Recientes progresos en la investigación básica han determinado la huella molecular de metástasis de un tumor capaz de predecir su proclividad metastásica. La investigación básica favorecerá un conocimiento de los mecanismos básicos y llevará a elucidar dianas moleculares que favorecerán el desarrollo de fármacos capaces de prevenir, amortiguar o bloquear el proceso metastático. Bone metastases represent a devastating clinical problem in the most frequent neoplasies, especially in multiple myeloma, tumours breast, prostate and lung. The consequences include pain which is refractory to conventional analgesics, osteolysis often leading to bone-marrow compression and pathological fractures, and metabolic disorders. Recent advances in diagnosis using imaging techniques as well as different biochemical techniques have helped accurate diagnosis and follow-up. The increase in survival has improved through a multimodal approach combining, inhibition of osteolysis, with prophylactic orthopaedic surgery and radiation therapy. Recent advances in basic research have determined the molecular metastatic that can predict its proclivity to metastasize. Basic research will improve understanding of the basic mechanisms and lead to the clarification of molecular targets that will help in the development of medicines capable of preventing, decreasing or blocking the metastatic process.