35 research outputs found

    Cell free circulating tumor DNA in cerebrospinal fluid detects and monitors central nervous system involvement of B-cell lymphomas

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    Limfoma no Hodgkin agressiu; Limfoma del SNCLinfoma no Hodgkin agresivo; Linfoma del SNCAggressive Non-Hodgkin's Lymphoma; CNS lymphomaThe levels of cell free circulating tumor DNA (ctDNA) in plasma correlated with treatment response and outcome in systemic lymphomas. Notably, in brain tumors, the levels of ctDNA in the cerebrospinal fluid (CSF) are higher than in plasma. Nevertheless, their role in central nervous system (CNS) lymphomas remains elusive. We evaluated the CSF and plasma from 19 patients: 6 restricted CNS lymphomas, 1 systemic and CNS lymphoma, and 12 systemic lymphomas. We performed whole exome sequencing or targeted sequencing to identify somatic mutations of the primary tumor, then variant-specific droplet digital PCR was designed for each mutation. At time of enrolment, we found ctDNA in the CSF of all patients with restricted CNS lymphoma but not in patients with systemic lymphoma without CNS involvement. Conversely, plasma ctDNA was detected in only 2/6 patients with restricted CNS lymphoma with lower variant allele frequencies than CSF ctDNA. Moreover, we detected CSF ctDNA in 1 patient with CNS lymphoma in complete remission and in 1 patient with systemic lymphoma, 3 and 8 months before CNS relapse was confirmed; indicating CSF ctDNA might detect CNS relapse earlier than conventional methods. Finally, in 2 cases with CNS lymphoma, CSF ctDNA was still detected after treatment even though a complete decrease in CSF tumor cells was observed by flow cytometry (FC), indicating CSF ctDNA better detected residual disease than FC. In conclusion, CSF ctDNA can better detect CNS lesions than plasma ctDNA and FC. In addition, CSF ctDNA predicted CNS relapse in CNS and systemic lymphomas.This work was supported by research funding from Fundación Asociación Española contra el Cáncer (AECC) (to JS, MC and PA); FERO (to JS), laCaixa (to JS), BBVA (CAIMI) (to JS), the Instituto de Salud Carlos III, Fondo de Investigaciones Sanitarias (PI16/01278 to JS; PI17/00950 to MC; PI17/00943 to FB) cofinanced by the European Regional Development Fund (ERDF) and Gilead Fellowships (GLD16/00144, GLD18/00047, to FB). MC holds a contract from Ministerio de Ciencia, Innovación y Universidades (RYC-2012-12018). SB received funding from Fundación Alfonso Martin Escudero. LE received funding from the Juan de la Cierva fellowship. We thank CERCA Programme / Generalitat de Catalunya for institutional support

    Inappropriate antibiotic use in the COVID-19 era: Factors associated with inappropriate prescribing and secondary complications. Analysis of the registry SEMI-COVID

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    Background: Most patients with COVID-19 receive antibiotics despite the fact that bacterial co-infections are rare. This can lead to increased complications, including antibacterial resistance. We aim to analyze risk factors for inappropriate antibiotic prescription in these patients and describe possible complications arising from their use. Methods: The SEMI-COVID-19 Registry is a multicenter, retrospective patient cohort. Patients with antibiotic were divided into two groups according to appropriate or inappropriate prescription, depending on whether the patient fulfill any criteria for its use. Comparison was made by means of multilevel logistic regression analysis. Possible complications of antibiotic use were also identified. Results: Out of 13,932 patients, 3047 (21.6%) were prescribed no antibiotics, 6116 (43.9%) were appropriately prescribed antibiotics, and 4769 (34.2%) were inappropriately prescribed antibiotics. The following were independent factors of inappropriate prescription: February-March 2020 admission (OR 1.54, 95%CI 1.18-2.00), age (OR 0.98, 95%CI 0.97-0.99), absence of comorbidity (OR 1.43, 95%CI 1.05-1.94), dry cough (OR 2.51, 95%CI 1.94-3.26), fever (OR 1.33, 95%CI 1.13-1.56), dyspnea (OR 1.31, 95%CI 1.04-1.69), flu-like symptoms (OR 2.70, 95%CI 1.75-4.17), and elevated C-reactive protein levels (OR 1.01 for each mg/L increase, 95% CI 1.00-1.01). Adverse drug reactions were more frequent in patients who received ANTIBIOTIC (4.9% vs 2.7%, p < .001). Conclusion: The inappropriate use of antibiotics was very frequent in COVID-19 patients and entailed an increased risk of adverse reactions. It is crucial to define criteria for their use in these patients. Knowledge of the factors associated with inappropriate prescribing can be helpful

    Autoimmune Diseases and COVID-19 as Risk Factors for Poor Outcomes: Data on 13,940 Hospitalized Patients from the Spanish Nationwide SEMI-COVID-19 Registry

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    (1) Objectives: To describe the clinical characteristics and clinical course of hospitalized patients with COVID-19 and autoimmune diseases (ADs) compared to the general population. (2) Methods: We used information available in the nationwide Spanish SEMI-COVID-19 Registry, which retrospectively compiles data from the first admission of adult patients with COVID-19. We selected all patients with ADs included in the registry and compared them to the remaining patients. The primary outcome was all-cause mortality during admission, readmission, and subsequent admissions, and secondary outcomes were a composite outcome including the need for intensive care unit (ICU) admission, invasive and non-invasive mechanical ventilation (MV), or death, as well as in-hospital complications. (3) Results: A total of 13,940 patients diagnosed with COVID-19 were included, of which 362 (2.6%) had an AD. Patients with ADs were older, more likely to be female, and had greater comorbidity. On the multivariate logistic regression analysis, which involved the inverse propensity score weighting method, AD as a whole was not associated with an increased risk of any of the outcome variables. Habitual treatment with corticosteroids (CSs), age, Barthel Index score, and comorbidity were associated with poor outcomes. Biological disease-modifying anti-rheumatic drugs (bDMARDs) were associated with a decrease in mortality in patients with AD. (4) Conclusions: The analysis of the SEMI-COVID-19 Registry shows that ADs do not lead to a different prognosis, measured by mortality, complications, or the composite outcome. Considered individually, it seems that some diseases entail a different prognosis than that of the general population. Immunosuppressive/immunoregulatory treatments (IST) prior to admission had variable effects

    Integrative pathway enrichment analysis of multivariate omics data.

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    Funder: BioTalent Canada Student InternshipFunder: Canadian Institutes of Health Research (CIHR) Canadian Graduate ScholarshipFunder: Ontario Institute for Cancer Research (OICR) Investigator Awards provided by the Government of Ontario; Terry Fox Research Institute (TFRI) and Canadian Institutes of Health Research (CIHR) New Investigator Awards.Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations

    Natural History of MYH7-Related Dilated Cardiomyopathy

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    BACKGROUND Variants in myosin heavy chain 7 (MYH7) are responsible for disease in 1% to 5% of patients with dilated cardiomyopathy (DCM); however, the clinical characteristics and natural history of MYH7-related DCM are poorly described. OBJECTIVES We sought to determine the phenotype and prognosis of MYH7-related DCM. We also evaluated the influence of variant location on phenotypic expression. METHODS We studied clinical data from 147 individuals with DCM-causing MYH7 variants (47.6% female; 35.6 +/- 19.2 years) recruited from 29 international centers. RESULTS At initial evaluation, 106 (72.1%) patients had DCM (left ventricular ejection fraction: 34.5% +/- 11.7%). Median follow-up was 4.5 years (IQR: 1.7-8.0 years), and 23.7% of carriers who were initially phenotype-negative developed DCM. Phenotypic expression by 40 and 60 years was 46% and 88%, respectively, with 18 patients (16%) first diagnosed at <18 years of age. Thirty-six percent of patients with DCM met imaging criteria for LV noncompaction. During follow-up, 28% showed left ventricular reverse remodeling. Incidence of adverse cardiac events among patients with DCM at 5 years was 11.6%, with 5 (4.6%) deaths caused by end-stage heart failure (ESHF) and 5 patients (4.6%) requiring heart transplantation. The major ventricular arrhythmia rate was low (1.0% and 2.1% at 5 years in patients with DCM and in those with LVEF of <= 35%, respectively). ESHF and major ventricular arrhythmia were significantly lower compared with LMNA-related DCM and similar to DCM caused by TTN truncating variants. CONCLUSIONS MYH7-related DCM is characterized by early age of onset, high phenotypic expression, low left ventricular reverse remodeling, and frequent progression to ESHF. Heart failure complications predominate over ventricular arrhythmias, which are rare. (C) 2022 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation

    Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

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    Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

    Understanding the genomic makeup of tumors to guide personalized medicine

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    Cancer is a disease of the genome. The study of tumor genomic alterations is used to guide several precision medicine strategies, some approved and a large number under clinical development. On the other hand, the study of tumor immunity is recently becoming the key for the success of other personalized strategies, named immunotherapies. Along this thesis I have made several contributions towards the advance of cancer precision medicine, based on the study of tumor “omics” data. First, I evinced the landscape of genomic-guided anti-cancer therapies. Second, I developed OncoPaD, a tool for the rational design of cost-effective cancer gene panels. Third, I contributed to the development of Cancer Genome Interpreter, a tool for the biological and therapeutic interpretation of variants found in newly sequenced tumors. Forth, I identified tumor intrinsic molecular mechanisms involved in tumor immune evasion.El càncer és una malaltia del genoma. L'estudi de les alteracions genòmiques dels tumors s’utilitza com a guia en varies estratègies de medicina de precisió, algunes d'elles aprovades i d'altres en assajos clínics. D'altra banda, l’estudi de la immunitat tumoral està esdevenint una peça clau per l’èxit d’altres estratègies terapèutiques, anomenades immunoteràpies. Al llarg d'aquesta tesi, mitjançant l'estudi de les dades “òmiques” tumorals, he contribuït de varies maneres cap a l'avenç de la medicina de precisió pel càncer. Primer, he identificat el panorama de les teràpies anticanceroses guiades per alteracions genòmiques. Segon, he desenvolupat OncoPaD, una eina pel disseny cost-efectiu i racional de panells de seqüenciació per càncer. A més, he contribuït al desenvolupament del Cancer Genome Interpreter, una eina que ajuda a la interpretació biològica i terapèutica de les variants presents a tumors novament seqüenciats. Per últim, he identificat diversos mecanismes mitjançant els quals els tumors són capaços d'evadir l’atac del sistema immunològic

    OncodriveROLE classifies cancer driver genes in loss of function and activating mode of action

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    MOTIVATION: Several computational methods have been developed to identify cancer drivers genes-genes responsible for cancer development upon specific alterations. These alterations can cause the loss of function (LoF) of the gene product, for instance, in tumor suppressors, or increase or change its activity or function, if it is an oncogene. Distinguishing between these two classes is important to understand tumorigenesis in patients and has implications for therapy decision making. Here, we assess the capacity of multiple gene features related to the pattern of genomic alterations across tumors to distinguish between activating and LoF cancer genes, and we present an automated approach to aid the classification of novel cancer drivers according to their role. RESULT: /nOncodriveROLE is a machine learning-based approach that classifies driver genes according to their role, using several properties related to the pattern of alterations across tumors. The method shows an accuracy of 0.93 and Matthew's correlation coefficient of 0.84 classifying genes in the Cancer Gene Census. The OncodriveROLE classifier, its results when applied to two lists of predicted cancer drivers and TCGA-derived mutation and copy number features used by the classifier are available at http://bg.upf.edu/oncodrive-role. AVAILABILITY AND IMPLEMENTATION: The R implementation of the OncodriveROLE classifier is available at http://bg.upf.edu/oncodrive-role. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.This work was supported by the Spanish Ministry of Economy and Competitivity (grant number SAF2012-36199) and the Spanish National Institute of Bioinformatics (INB). M.P.S. and C.R.-P. are supported by FPI fellowship
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