73 research outputs found

    Sirt1 protects from K-Ras-driven lung carcinogenesis.

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    The NAD+-dependent deacetylase SIRT1 can be oncogenic or tumor suppressive depending on the tissue. Little is known about the role of SIRT1 in non-small cell lung carcinoma (NSCLC), one of the deadliest cancers, that is frequently associated with mutated K-RAS Therefore, we investigated the effect of SIRT1 on K-RAS-driven lung carcinogenesis. We report that SIRT1 protein levels are downregulated by oncogenic K-RAS in a MEK and PI3K-dependent manner in mouse embryo fibroblasts (MEFs), and in human lung adenocarcinoma cell lines. Furthermore, Sirt1 overexpression in mice delays the appearance of K-RasG12V-driven lung adenocarcinomas, reducing the number and size of carcinomas at the time of death and extending survival. Consistently, lower levels of SIRT1 are associated with worse prognosis in human NSCLCs. Mechanistically, analysis of mouse Sirt1-Tg pneumocytes, isolated shortly after K-RasG12V activation, reveals that Sirt1 overexpression alters pathways involved in tumor development: proliferation, apoptosis, or extracellular matrix organization. Our work demonstrates a tumor suppressive role of SIRT1 in the development of K-RAS-driven lung adenocarcinomas in mice and humans, suggesting that the SIRT1-K-RAS axis could be a therapeutic target for NSCLCs.We thank Jesus Herranz for his biostatistical advice; and Alba de Martino, Patricia Gonzalez, Maria Gomez, and Zaira Vega, from the Histopathology Unit at the CNIO, for their work in mouse histopathology. Work in the laboratory of P.J.F.-M. was funded by the IMDEA Food, the Spanish Association against Cancer (aecc) and the Ramon Areces (CIVP18A3891) Foundation. Work in the laboratory of M.S. was funded by the CNIO and by grants from the Spanish Ministry of Economy co-funded by the European Regional Development Fund (SAF project), the European Research Council (ERC Advanced Grant), the European Union (RISK-IR project), and the Botin Foundation and Banco Santander (Santander Universities Global Division). Work in the laboratory of DH was funded by Rutgers Cancer Institute of New Jersey, the Alex's Lemonade Stand Foundation Shark Tank Award and by the National Institutes of Health Grant K99/R00 CA197869. Work in the laboratory of M.S.C. was supported by a grant (SAF2012-40026) from the Spanish Ministry of Science and Innovation. L.F.C-M. was supported by a PhD Fellowship from the Portuguese Foundation for Science and Technology (FCT-MCTES, SFRH/BD/124022/2016).S

    Bladder Cancer Tissue-Based Biomarkers

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    This review aims to provide a practical update regarding the current role of tissue-based biomarkers in bladder cancer. Their prognostic and predictive role both in non-muscle-invasive (NMIBC) and in muscle-invasive disease (MIBC) has been reviewed with particular focus to their use in clinical practice. In summary, the literature on the prediction of disease recurrence in NMIBC is inconclusive, and there is little information on prediction of response to intravesical bacillus Calmette-Guerin (BCG). Concerning disease progression, external prospective validation studies suggest that FGFR3 mutation status and gene signatures may improve models that are based only on clinicopathologic information. In MIBC, tissue-based biomarkers are increasingly important, since they may predict the response to systemic chemotherapy and immunotherapy. In particular, the advent of molecular characterization promises to revolutionize the paradigm of decision-making in the treatment of MIBC. Molecular subtyping has been shown to improve the prediction of pathological stage at RC and to predict the response to systemic chemotherapy and immunotherapy. However, external and prospective validations are warranted to confirm these preliminary findings. Several different tissue-based biomarkers such as PD-1/PD-L1 expression, tumor mutational burden, and the analysis of tumor microenvironment, may in future play a role in selecting patients for systemic immunotherapy. However, to date, no pretreatment recommendations can be definitively made on the basis of any molecular predictors. In conclusion, despite the potential of tissue-based biomarkers, their use in bladder cancer should be limited to experimental settings

    Role of Pirh2 in Mediating the Regulation of p53 and c-Myc

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    Ubiquitylation is fundamental for the regulation of the stability and function of p53 and c-Myc. The E3 ligase Pirh2 has been reported to polyubiquitylate p53 and to mediate its proteasomal degradation. Here, using Pirh2 deficient mice, we report that Pirh2 is important for the in vivo regulation of p53 stability in response to DNA damage. We also demonstrate that c-Myc is a novel interacting protein for Pirh2 and that Pirh2 mediates its polyubiquitylation and proteolysis. Pirh2 mutant mice display elevated levels of c-Myc and are predisposed for plasma cell hyperplasia and tumorigenesis. Consistent with the role p53 plays in suppressing c-Myc-induced oncogenesis, its deficiency exacerbates tumorigenesis of Pirh2−/− mice. We also report that low expression of human PIRH2 in lung, ovarian, and breast cancers correlates with decreased patients' survival. Collectively, our data reveal the in vivo roles of Pirh2 in the regulation of p53 and c-Myc stability and support its role as a tumor suppressor

    Quality indicators for patients with traumatic brain injury in European intensive care units

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    Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

    Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

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    Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

    Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

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    Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

    Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

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    INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches
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