Factors associated with the development of industrial internships in university institutions

The research proposes to reveal factors associated to Industrial Internships in Experimental Universities, approaching from a descriptive level with documentary and field modality. The students who completed the Internship in 2017, the tutors and the companies where they took place were taken as a sample; applying as instruments two questionnaires aimed at students and tutors. Students stand out in factors: time spent by tutors, company collaboration and evaluation system used. For teachers: logistic mechanisms for visits, lack of effective and timely communication to improve processes and lack of inter-institutional relations between actors involvedLa investigación plantea develar factores asociados a las Pasantías Industriales en Instituciones Universitarias, abordándose desde un nivel descriptivo con modalidad documental y de campo. Se tomó como muestra los estudiantes que realizaron la Pasantía en el año 2017, los tutores y las empresas donde se realizaron; aplicándose como instrumentos dos cuestionarios dirigidos a estudiantes y a tutores. Destacan en los estudiantes factores: tiempo dedicado por tutores, colaboración de la empresa y sistema de evaluación empleado. Para los docentes: mecanismos logísticos para las visitas, falta de comunicación efectiva y oportuna para mejorar procesos y falta de relaciones interinstitucionales entre actores involucrados

ISOTOPE : ISOform-guided prediction of epiTOPEs in cancer

Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE

Genetic associations on major depression: curation and functional analysis

Major depression (MD) is the leading cause of impairment worldwide. The lack of understanding of its biological underpinnings hampers the development of better diagnostic tools and treatments. Thanks to the advances in genetic association studies, multiple genetic variants significantly associated with MD have been identified. In this thesis, we aim to leverage this knowledge to advance in the understanding of MD and unravel its molecular mechanisms. For that, we developed curation guidelines to evaluate available genetic association data on MD of diverse nature, and created an expert-curated database of genetic variants associated with MD. Then, we leveraged these data and functional genomic tools to unravel the role of these variants in disease pathogenesis and propose mechanistic hypotheses. In light of the plethora of tools available to perform such analyses, we conducted a benchmarking analysis to evaluate their performance and compare their outcomes; highlighting the need for guidelines for method selection and evaluation. Overall, this thesis contributes to filling the gap regarding the quality assessment of genetic studies on MD, and to advance in discovering the functional role of MD-associated variants by using in silico approaches.La depressió major (DM) és la principal causa d'incapacitat en tot el món. La falta de comprensió dels seus fonaments biològics dificulta el desenvolupament de millors diagnòstics i tractaments. Gràcies als avanços en estudis d'associació genètica, s'han identificat múltiples variants genètiques significativament associades a la DM. En aquesta tesi, volem aprofitar aquests coneixements per avançar en la comprensió de la DM i descobrir els seus mecanismes moleculars. Per a això, hem desenvolupat unes directrius de curació per avaluar l'ampli ventall de dades d'associació genètica disponibles sobre la DM i hem creat una base de dades de variants genètiques associades a la DM que ha estat curada per experts. Un cop finalitzada, vam aprofitar aquestes dades i diverses eines de genòmica funcional per entendre el paper d'aquestes variants en la patogènesi de la malaltia i proposar hipòtesis mecanístiques. Davant de la plètora d'eines disponibles, vam dur a terme una anàlisi de referència per avaluar el seu funcionament i comparar els seus resultats, on destaquem la necessitat de directrius per seleccionar I avaluar els mètodes. Globalment, aquesta tesi contribueix a omplir el buit que existeix pel que fa a l'avaluació de la qualitat dels estudis genètics sobre la DM, I avançar en el descobriment del paper functional de les variants associades a la DM mitjçant l’ús de mètodes in silico

Benchmarking post-GWAS analysis tools in major depression: Challenges and implications

Our knowledge of complex disorders has increased in the last years thanks to the identification of genetic variants (GVs) significantly associated with disease phenotypes by genome-wide association studies (GWAS). However, we do not understand yet how these GVs functionally impact disease pathogenesis or their underlying biological mechanisms. Among the multiple post-GWAS methods available, fine-mapping and colocalization approaches are commonly used to identify causal GVs, meaning those with a biological effect on the trait, and their functional effects. Despite the variety of post-GWAS tools available, there is no guideline for method eligibility or validity, even though these methods work under different assumptions when accounting for linkage disequilibrium and integrating molecular annotation data. Moreover, there is no benchmarking of the available tools. In this context, we have applied two different fine-mapping and colocalization methods to the same GWAS on major depression (MD) and expression quantitative trait loci (eQTL) datasets. Our goal is to perform a systematic comparison of the results obtained by the different tools. To that end, we have evaluated their results at different levels: fine-mapped and colocalizing GVs, their target genes and tissue specificity according to gene expression information, as well as the biological processes in which they are involved. Our findings highlight the importance of fine-mapping as a key step for subsequent analysis. Notably, the colocalizing variants, altered genes and targeted tissues differed between methods, even regarding their biological implications. This contribution illustrates an important issue in post-GWAS analysis with relevant consequences on the use of GWAS results for elucidation of disease pathobiology, drug target prioritization and biomarker discovery.IMI2-JU resources which are composed of financial contributions from the European Union’s Horizon 2020 Research and Innovation Programme and EFPIA (GA: 116030 TransQST and GA: 777365 eTRANSAFE), and the EU H2020 Programme 2014–2020 (GA: 676559 Elixir-Excelerate); Project 001-P-001647—Valorisation of EGA for Industry and Society funded by the European Regional Development Fund (ERDF) and Generalitat de Catalunya; Agència de Gestió d’Ajuts Universitaris i de Recerca Generalitat de Catalunya (2017SGR00519), and the Institute of Health Carlos III (project IMPaCT-Data, exp. IMP/00019), co-funded by the European Union, European Regional Development Fund (ERDF, “A way to make Europe”). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), funded by ISCIII and ERDF (PRB2-ISCIII (PT13/0001/0023, of the PE I + D + i 2013–2016)). The MELIS is a ‘Unidad de Excelencia María de Maeztu’, funded by the MINECO (MDM-2014-0370). JP-G was supported by Instituto de Salud Carlos III-Fondo Social Europeo (FI18/00034). This statement is a requirement from our funding agencies and therefore has to be included in the Funding section

ResMarkerDB: a database of biomarkers of response to antibody therapy in breast and colorectal cancer

The clinical efficacy of therapeutic monoclonal antibodies for breast and colorectal cancer has greatly contributed to the improvement of patients' outcomes by individualizing their treatments according to their genomic background. However, primary or acquired resistance to treatment reduces its efficacy. In this context, the identification of biomarkers predictive of drug response would support research and development of new alternative treatments. Biomarkers play a major role in the genomic revolution, supporting disease diagnosis and treatment decision-making. Currently, several molecular biomarkers of treatment response for breast and colorectal cancer have been described. However, information on these biomarkers is scattered across several resources, and needs to be identified, collected and properly integrated to be fully exploited to inform monitoring of drug response in patients. Therefore, there is a need of resources that offer biomarker data in a harmonized manner to the user to support the identification of actionable biomarkers of response to treatment in cancer. ResMarkerDB was developed as a comprehensive resource of biomarkers of drug response in colorectal and breast cancer. It integrates data of biomarkers of drug response from existing repositories, and new data extracted and curated from the literature (referred as ResCur). ResMarkerDB currently features 266 biomarkers of diverse nature. Twenty-five percent of these biomarkers are exclusive of ResMarkerDB. Furthermore, ResMarkerDB is one of the few resources offering non-coding DNA data in response to drug treatment. The database contains more than 500 biomarker-drug-tumour associations, covering more than 100 genes. ResMarkerDB provides a web interface to facilitate the exploration of the current knowledge of biomarkers of response in breast and colorectal cancer. It aims to enhance translational research efforts in identifying actionable biomarkers of drug response in cancer.Instituto de Salud Carlos III-Fondo Europeo de Desarrollo Regional [grant numbers: PIE15/00008, CP10/00524, CPII16/00026]; Instituto de Salud Carlos III-Fondo Social Europeo [FI18/00034]; and the European Commission Horizon 2020 Programme 2014–2020 under grant agreements MedBioinformatics [grant number: 634143] and Elixir-Excelerate [grant number: 676559]. The Research Programme on Biomedical Informatics is a member of the Spanish National Bioinformatics Institute, Plataforma de Recursos Biomoleculares y Bioinformáticos-Instituto de Salud Carlos III [grant number: PT13/0001/0023], of the PE I + D + i 2013–2016, funded by Instituto de Salud Carlos III and Fondo Europeo de Desarrollo Regional. The Departamento de Ciencias Experimentales y de la Salud is a Unidad de Excelencia María de Maeztu, funded by the Ministerio de Economía y Competitividad (reference number: MDM-2014-0370)

ResMarkerDB: a database of biomarkers of response to antibody therapy in breast and colorectal cancer

The clinical efficacy of therapeutic monoclonal antibodies for breast and colorectal cancer has greatly contributed to the improvement of patients' outcomes by individualizing their treatments according to their genomic background. However, primary or acquired resistance to treatment reduces its efficacy. In this context, the identification of biomarkers predictive of drug response would support research and development of new alternative treatments. Biomarkers play a major role in the genomic revolution, supporting disease diagnosis and treatment decision-making. Currently, several molecular biomarkers of treatment response for breast and colorectal cancer have been described. However, information on these biomarkers is scattered across several resources, and needs to be identified, collected and properly integrated to be fully exploited to inform monitoring of drug response in patients. Therefore, there is a need of resources that offer biomarker data in a harmonized manner to the user to support the identification of actionable biomarkers of response to treatment in cancer. ResMarkerDB was developed as a comprehensive resource of biomarkers of drug response in colorectal and breast cancer. It integrates data of biomarkers of drug response from existing repositories, and new data extracted and curated from the literature (referred as ResCur). ResMarkerDB currently features 266 biomarkers of diverse nature. Twenty-five percent of these biomarkers are exclusive of ResMarkerDB. Furthermore, ResMarkerDB is one of the few resources offering non-coding DNA data in response to drug treatment. The database contains more than 500 biomarker-drug-tumour associations, covering more than 100 genes. ResMarkerDB provides a web interface to facilitate the exploration of the current knowledge of biomarkers of response in breast and colorectal cancer. It aims to enhance translational research efforts in identifying actionable biomarkers of drug response in cancer.Instituto de Salud Carlos III-Fondo Europeo de Desarrollo Regional [grant numbers: PIE15/00008, CP10/00524, CPII16/00026]; Instituto de Salud Carlos III-Fondo Social Europeo [FI18/00034]; and the European Commission Horizon 2020 Programme 2014–2020 under grant agreements MedBioinformatics [grant number: 634143] and Elixir-Excelerate [grant number: 676559]. The Research Programme on Biomedical Informatics is a member of the Spanish National Bioinformatics Institute, Plataforma de Recursos Biomoleculares y Bioinformáticos-Instituto de Salud Carlos III [grant number: PT13/0001/0023], of the PE I + D + i 2013–2016, funded by Instituto de Salud Carlos III and Fondo Europeo de Desarrollo Regional. The Departamento de Ciencias Experimentales y de la Salud is a Unidad de Excelencia María de Maeztu, funded by the Ministerio de Economía y Competitividad (reference number: MDM-2014-0370)

Functional genomics analysis to disentangle the role of genetic variants in major depression

Understanding the molecular basis of major depression is critical for identifying new potential biomarkers and drug targets to alleviate its burden on society. Leveraging available GWAS data and functional genomic tools to assess regulatory variation could help explain the role of major depression-associated genetic variants in disease pathogenesis. We have conducted a fine-mapping analysis of genetic variants associated with major depression and applied a pipeline focused on gene expression regulation by using two complementary approaches: cis-eQTL colocalization analysis and alteration of transcription factor binding sites. The fine-mapping process uncovered putative causally associated variants whose proximal genes were linked with major depression pathophysiology. Four colocalizing genetic variants altered the expression of five genes, highlighting the role of SLC12A5 in neuronal chlorine homeostasis and MYRF in nervous system myelination and oligodendrocyte differentiation. The transcription factor binding analysis revealed the potential role of rs62259947 in modulating P4HTM expression by altering the YY1 binding site, altogether regulating hypoxia response. Overall, our pipeline could prioritize putative causal genetic variants in major depression. More importantly, it can be applied when only index genetic variants are available. Finally, the presented approach enabled the proposal of mechanistic hypotheses of these genetic variants and their role in disease pathogenesis.IMI2-JU resources which are composed of financial contributions from the European Union’s Horizon 2020 Research and Innovation Programme and EFPIA [GA: 116030 TransQST and GA: 777365 eTRANSAFE], and the EU H2020 Programme 2014–2020 [GA: 676559 Elixir-Excelerate]; Project 001-P-001647—Valorisation of EGA for Industry and Society funded by the European Regional Development Fund (ERDF) and Generalitat de Catalunya; Agència de Gestió d’Ajuts Universitaris i de Recerca Generalitat de Catalunya [2017SGR00519], and the Institute of Health Carlos III (project IMPaCT-Data, exp. IMP/00019), co-funded by the European Union, European Regional Development Fund (ERDF, “A way to make Europe”). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), funded by ISCIII and ERDF (PRB2-ISCIII [PT13/0001/0023, of the PE I + D + i 2013–2016]). The MELIS is a ‘Unidad de Excelencia María de Maeztu’, funded by the MINECO [MDM-2014-0370]. AMR was supported by CONACYT-FORDECYT-PRONACES grant no. [11311], and Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica–Universidad Nacional Autónoma de México (PAPIIT-UNAM) grant nos. IA203021. JPG was supported by Instituto de Salud Carlos III-Fondo Social Europeo [FI18/00034]; Instituto de Salud Carlos III [MV20]. This work reflects only the author’s view and that the IMI2-JU is not responsible for any use that may be made of the information it contains

ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer

Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE.Funding: This work was supported by the Spanish Government and European Regional Development Fund (FEDER) with grant BIO2017-85364-R (F.S., E.E.), by the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya) with grants SGR2017-1020 (E.E) and 2017 SGR 00519 (F.S), by the Instituto de Salud Carlos III (ISCIII and FEDER) with grants FI18/00034 (J.P-G) and PT17/0009/0014 (F.S), and by the AEI with CEX2018-000782-M (F.S). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB) supported by ISCIII and FEDER (PT17/0009/0014). The DCEXS is a ‘Unidad de Excelencia María de Maeztu’ supported by the AEI (CEX2018-000782-M

Initial presenting manifestations in 16,486 patients with inborn errors of immunity include infections and noninfectious manifestations

Background: Inborn errors of immunity (IEI) are rare diseases, which makes diagnosis a challenge. A better description of the initial presenting manifestations should improve awareness and avoid diagnostic delay. Although increased infection susceptibility is a well-known initial IEI manifestation, less is known about the frequency of other presenting manifestations. Objective: We sought to analyze age-related initial presenting manifestations of IEI including different IEI disease cohorts. Methods: We analyzed data on 16,486 patients of the European Society for Immunodeficiencies Registry. Patients with autoinflammatory diseases were excluded because of the limited number registered. Results: Overall, 68% of patients initially presented with infections only, 9% with immune dysregulation only, and 9% with a combination of both. Syndromic features were the presenting feature in 12%, 4% had laboratory abnormalities only, 1.5% were diagnosed because of family history only, and 0.8% presented with malignancy. Two-third of patients with IEI presented before the age of 6 years, but a quarter of patients developed initial symptoms only as adults. Immune dysregulation was most frequently recognized as an initial IEI manifestation between age 6 and 25 years, with male predominance until age 10 years, shifting to female predominance after age 40 years. Infections were most prevalent as a first manifestation in patients presenting after age 30 years. Conclusions: An exclusive focus on infection-centered warning signs would have missed around 25% of patients with IEI who initially present with other manifestations. (J Allergy Clin Immunol 2021;148:1332-41.