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1.
Am J Pathol ; 182(3): 646-67, 2013 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-23321323

RESUMO

Patients with neurofibromatosis type 1 (NF1) develop benign plexiform neurofibromas that frequently progress to become malignant peripheral nerve sheath tumors (MPNSTs). A genetically engineered mouse model that accurately models plexiform neurofibroma-MPNST progression in humans would facilitate identification of somatic mutations driving this process. We previously reported that transgenic mice overexpressing the growth factor neuregulin-1 in Schwann cells (P(0)-GGFß3 mice) develop MPNSTs. To determine whether P(0)-GGFß3 mice accurately model human neurofibroma-MPNST progression, cohorts of these animals were monitored through death and were necropsied; 94% developed multiple neurofibromas, with 70% carrying smaller numbers of MPNSTs. Nascent MPNSTs were identified within neurofibromas, suggesting that these sarcomas arise from neurofibromas. Although neurofibromin expression was maintained, P(0)-GGFß3 MPNSTs exhibited Ras hyperactivation, as in human NF1-associated MPNSTs. P(0)-GGFß3 MPNSTs also exhibited abnormalities in the p16(INK4A)-cyclin D/CDK4-Rb and p19(ARF)-Mdm-p53 pathways, analogous to their human counterparts. Array comparative genomic hybridization (CGH) demonstrated reproducible chromosomal alterations in P(0)-GGFß3 MPNST cells (including universal chromosome 11 gains) and focal gains and losses affecting 39 neoplasia-associated genes (including Pten, Tpd52, Myc, Gli1, Xiap, and Bbc3/PUMA). Array comparative genomic hybridization also identified recurrent focal copy number variations affecting genes not previously linked to neurofibroma or MPNST pathogenesis. We conclude that P(0)-GGFß3 mice represent a robust model of neurofibroma-MPNST progression useful for identifying novel genes driving neurofibroma and MPNST pathogenesis.


Assuntos
Transformação Celular Neoplásica/genética , Cromossomos de Mamíferos/genética , Variações do Número de Cópias de DNA/genética , Progressão da Doença , Neoplasias de Bainha Neural/patologia , Neuregulina-1/metabolismo , Neurofibroma/patologia , Animais , Pareamento de Bases/genética , Biomarcadores Tumorais/metabolismo , Ciclo Celular , Transformação Celular Neoplásica/patologia , Hibridização Genômica Comparativa , Modelos Animais de Doenças , Humanos , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Transgênicos , Neoplasias de Bainha Neural/genética , Neurofibroma/genética , Neurofibromina 1/metabolismo , Sistema Nervoso Periférico/metabolismo , Sistema Nervoso Periférico/patologia , Transdução de Sinais/genética , Proteínas ras/metabolismo
2.
Cureus ; 12(8): e9575, 2020 Aug 05.
Artigo em Inglês | MEDLINE | ID: mdl-32913691

RESUMO

Background and objectives Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are rapidly spreading, posing a serious threat to the health of people worldwide, resulting in the World Health Organization officially declaring it a pandemic. There are several biochemical markers linked with predicting the severity of coronavirus disease. This study aims to identify the most effective predictive biomarker such as C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), procalcitonin (PCT), and D-dimer, among others, in predicting the clinical outcome of the disease. Materials and methods This study was conducted as a retrospective, observational, multi-centric study, including all admitted COVID-19 positive patients only. The disease outcome was followed along with the hospital course of every patient at the time of analysis. Baseline laboratory investigations of all patients were monitored both at admission and discharge. A comparative analysis was done between the survivors (n=263) and non-survivors (n=101). Statistical analysis was conducted using IBM SPSS Statistics for Windows Version 25 (Armonk, NY: IBM Corp.). Results Of 364 patients, 65.7% were in the isolation ward, and 34.3% were in the intensive care unit; 72.3% of patients survived, while 27.7% of patients died. The mean age of the study population was 52.6 ± 15.8 years with female patients significantly younger than male patients (p=0.001) and 50 to 75 years being the most common age group (p=0.121). Among the survivors versus non-survivors of COVID-19, there were significant differences in total leukocyte count (p<0.001), neutrophil count, (p<0.001), lymphocyte count (p<0.001), urea (p<0.001), serum bicarbonate (p=0.001), CRP levels (p<0.001), LDH (p=0.013), and D-dimer (p<0.001) at admission. At discharge, the laboratory values of non-surviving patients showed significant leukocytosis (p<0.001), neutrophilia (p<0.001), lymphocytopenia (p<0.001), decreased monocytes (p<0.001), elevated urea and creatinine (p<0.001), hypernatremia (p<0.001), decreased serum bicarbonate levels (p<0.001), elevated CRP level (p=0.040), LDH (p<0.001), ferritin (p=0.001), and D-dimer (p<0.001). Among the recovered patients, the laboratory investigations at admission were significantly different from those at discharge like increased platelets (p=0.007), lower neutrophil count (p=0.001), higher lymphocyte count (p=0.005), an improved creatinine (p=0.020), higher sodium (p=0.008), increased bicarbonate levels (p<0.001), decreased CRP levels (p<0.001), and a lower LDH (p=0.039). However, the laboratory values of non-surviving patients had shown a lower hemoglobin (p=0.016), increased mean cell volume (p<0.001), significantly increased total leukocyte count (p<0.001), increased urea and creatinine (p<0.001), hypernatremia (p<0.001), increased bicarbonate (p=0.025), elevated D-dimer levels (p=0.043), and elevated PCT (p=0.021) on discharge. Receiver operating characteristic analysis concluded LDH (area under the curve [AUC]: 0.875), D-dimer (AUC: 0.803), and PCT (AUC: 0.769) were superior biomarkers to ferritin (AUC: 0.714) and CRP (AUC: 0.711) in predicting the fatality of COVID-19. Conclusion Inflammatory markers are a useful guide for predicting mortality, and the study results concluded that LDH, PCT, D-dimer, CRP, and ferritin were effective biomarkers.

3.
Cureus ; 12(8): e10054, 2020 Aug 26.
Artigo em Inglês | MEDLINE | ID: mdl-32999777

RESUMO

Background and objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) pandemic. The disease mainly affects the respiratory system of the patient, in particular, the lungs, which leads to patients presenting with acute respiratory distress syndrome and acute respiratory failure, with 5-15% of patients requiring observation in the intensive care unit (ICU) with respiratory support in the form of ventilation. This study was aimed at identifying the role of biochemical markers in the risk stratification of invasive and non-invasive ventilation of hospitalized COVID-19 patients. Materials and methods The study was conducted as a prospective, observational study of all admitted COVID-19 patients. A comparative analysis was performed of the survivors who were on invasive versus (vs) non-invasive ventilation and the non-survivors similarly. After computing the descriptive statistics, a multinomial logistic regression model was applied to obtain an unadjusted odds ratio (OR) at 95% confidence interval (CI), with Hosmer-Lemeshow (HL) goodness-of-fit test used to predict the fitness of the data. Kaplan-Meier survival curves were obtained for each of the laboratory investigations predicting survival along with the intensive care stay and invasive ventilation. A log-rank test was carried out to compare the survival distributions. Results A total of 373 included patients in the study had a mean age of 52.78 ± 15.76 years with females younger than males, and indifference amongst invasive vs non-invasively ventilated (p=0.821). Females were slightly more prone to invasive ventilation (p=0.097). Overall, 39% of the subjects did not need respiratory support, while 13% were on a ventilator, 16% on bilevel positive airway pressure/continuous positive airway pressure (BiPAP/CPAP), and 31% on supplemental oxygen therapy. Among the laboratory markers, mean hemoglobin was evidently lower in the invasive group, leukocytosis and thrombocytopenia were present in both invasively ventilated and non-surviving patients, while neutrophilia and lymphocytopenia were statistically indifferent among the mode of ventilation. Elevated urea, creatinine, and sodium were also significantly deranged laboratory markers amongst the invasively ventilated group. C-reactive protein (CRP) and lactate dehydrogenase (LDH) were elevated significantly in the invasive group, while serum ferritin was more frequently raised in the non-invasively ventilated group. Procalcitonin (PCT) was significantly associated with invasive ventilation as opposed to the non-invasive group. D-dimer was equally raised in both the groups at admission but significantly elevated in the invasive group at discharge. A multinomial regression model signified D-dimer (OR: 16.301), hypernatremia (OR: 12.738), creatinine (OR: 12.589), urea (OR: 12.576), and LDH (OR: 12.245) most significantly associated with death, while those for invasive ventilation were D-dimer (OR: 8.744), hypernatremia (OR: 4.532), PCT (OR: 3.829), neutrophilia (OR: 3.804), leukocytosis (OR: 3.330), and serum urea (OR: 3.312). Kaplan-Meier curves conclude total leucocyte count (TLC), neutrophils, lymphocytes, urea, creatinine, sodium, CRP, LDH, PCT, and D-dimer all significantly contributing to an early death. Conclusion The most significant marker for mortality was D-dimer, followed by serum sodium, urea/creatinine, LDH, ICU stay, and invasive ventilation.

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