RESUMO

Although ependymoma (EPN) molecular subgroups have been well established by integrated high-throughput platforms, low- and middle-income countries still need low-cost techniques to promptly classify these molecular subtypes. Here, we applied low-cost methods to classify EPNs from a Brazilian cohort with 60 pediatric EPN patients. Fusion transcripts (C11orf95-RELA, YAP1-MAMLD1, and YAP1-FAM118B) were investigated in supratentorial EPN (ST-EPNs) samples through RT-PCR/Sanger sequencing and immunohistochemistry (IHC) for p65/L1CAM. qRT-PCR and IHC were used to evaluate expression profiling of CXorf67, LAMA2, NELL2, and H3K27me3 in posterior fossa EPN (PF-EPNs) samples. In silico analysis was performed using public microarray data to validate the molecular assignment PF-EPNs with LAMA2/NELL2 markers. RELA cases and YAP1-MAMLD1 fusions were identified in nine and four ST-EPNs, respectively. An additional RELA case was identified by IHC. Of note, LAMA2 and NELL2 gene expression and immunoprofiling were less accurate for classifying PF-EPNs, which were confirmed by in silico analysis. Yet, H3K27me3 staining was sufficient to classify PF-EPN subgroups. Our results emphasize the feasibility of a simplified strategy to molecularly classify EPNs in the vast majority of cases (49/60; 81.7%). A coordinated combination of simple methods can be effective to screen pediatric EPN with the available laboratory resources at most low-/mid-income countries, giving support for clinical practice in pediatric EPN. KEY MESSAGES: Low- and middle-income countries need effective low-cost approaches to promptly distinguish between EPN molecular subgroups. RT-PCR plus Sanger sequencing is able to recognize the most common types of RELA and YAP1 fusion transcripts in ST-EPNs. Genetic and protein expressions of LAMA2 and NELL2 are of limited value to accurately stratify PF-EPNs. Immunohistochemical staining for H3K27me3 may be used as a robust method to accurately diagnose PF-EPNs subgroups. A coordinated flow diagram based on these validated low-cost methods is proposed to help clinical-decision making and to reduce costs with NGS assessment outside research protocols.

Assuntos

Ependimoma/diagnóstico , Técnicas de Diagnóstico Molecular/métodos , Algoritmos , Biomarcadores Tumorais/genética , Brasil , Criança , Biologia Computacional/métodos , Gerenciamento Clínico , Suscetibilidade a Doenças , Ependimoma/etiologia , Feminino , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Humanos , Imuno-Histoquímica , Masculino , Técnicas de Diagnóstico Molecular/economia , Técnicas de Diagnóstico Molecular/normas , Gradação de Tumores , Estadiamento de Neoplasias , Proteínas de Fusão Oncogênica/genética , Curva ROC , Reprodutibilidade dos Testes , Análise de Sequência de DNA

RESUMO

Air pollution is a public health concern. Polycyclic aromatic hydrocarbons (PAH) are ubiquitous atmospheric pollutants contained in the atmospheric aerosol. PAH in particulate matter with diameters ≤2.5 µm (PM2.5) represent a human health risk due to their toxic properties. In this study, PAH in PM2.5 at a receptor site of Mexico City during the dry cold season were determined. The most abundant PAH (median, 10-90th percentile, pg m-3) were benzo[ghi]perylene (467, 291-697), followed by pyrene (427, 218-642). A decrease around 40% in the carcinogenic PAH onto PM2.5 was calculated with respect to the same PAH measured a decade ago, at the same receptor site, despite of increase in vehicle fleet. The PAH decrease trend agrees with the decrease trend of CO, NO and NO2, released into the air by similar emission sources than PAH. Control emissions strategies implemented by local and federal authorities are discussed. PAH analyses were carried out by non-real-time and real-time methods. The PAH non-real-time method involved PM2.5 sampling, sample treatment and gas chromatography-mass spectrometry analysis. The PAH real-time method involved the use of a photoelectric aerosol sensor (PAS). The PAH determination by non-real time method was selective and efficient, with recoveries between 75 ±â€¯14% and 98 ±â€¯26%. By combining non-real-time and real-time methodologies, multivariate regression models were obtained based on PAS response, NO2 and wind speed to estimate PAH in PM2.5 at low-cost (r2 = 0.59 to r2 = 0.89). Fossil fuel combustion from vehicles was the major source around the sampling site. Diagnostic ratios (DR) based on retene, chrysene, and triphenylene, suggested biomass burning emission sources. Photo-oxidation in sunny months was observed based on benzo[a]pyrene, benzo[ghi]perylene, benz[a]anthracene, indeno[1,2,3-cd]pyrene and black carbon. The correlation analyses suggested transport of PM2.5, O3, BC and SO2 to the sampling site, and local emissions of PAH, NO and CO.