RESUMO
This study was targeted on a metabolomic approach to compare the blood serum free amino acid profiles and concentration of confirmed breast cancer (stages I-III) patients to healthy controls in order to establish reliable biomarkers of early detection and prediction of breast cancer. The ultra-high-performance liquid chromatography coupled with mass spectrometry using positive ionization electrospray was applied for the picoline-derivatized serum free amino acids using the EZ:faastTM kit. Multivariate statistical analysis principal component analysis, partial least squares discrimination analysis and univariate analysis were applied in order to discriminate between patient groups and putative amino acid biomarkers for breast cancer. A significant decrease of amino acid concentrations between the breast cancer group and the control group was positively correlated with breast cancer progression. Arginine, Alanine, Isoleucine, Tyrosine and Tryptophan were identified as being good potential discriminants (AUROC ≥0.85) and suitable candidates to diagnose and predict the breast cancer progression.
Assuntos
Aminoácidos/sangue , Biomarcadores Tumorais/sangue , Neoplasias da Mama/diagnóstico , Detecção Precoce de Câncer/métodos , Metaboloma , Adulto , Idoso , Neoplasias da Mama/sangue , Neoplasias da Mama/patologia , Estudos de Casos e Controles , Cromatografia Líquida de Alta Pressão/métodos , Progressão da Doença , Feminino , Humanos , Metabolômica/métodos , Pessoa de Meia-Idade , Análise Multivariada , Estadiamento de Neoplasias , Picolinas/química , Análise de Componente Principal , Espectrometria de Massas por Ionização por ElectrosprayRESUMO
AIM: To assess the predictive value of metabolomic analysis for the presence of prostate cancer (PCa) at first systematic biopsy. PATIENTS & METHODS: Ninety serum samples from patients with suspicion for PCa were included. Targeted and nontargeted metabolomic analysis was performed. RESULTS: Six metabolites were combined into a predictive score. A cutoff value of 0.528 for the metabolomic score showed a good accuracy for the prediction of PCa at biopsy (Area under the curve (AUC): 0.779; p < 0.001). These results were validated in a subgroup of patients, showing similar accuracy (p = 0.1). For patients with prostate specific antigen (PSA) less than 10 ng/ml, the score showed a Se 80.95%, Sp 64.52% for the detection of PCa at biopsy. CONCLUSION: Metabolomic analysis can predict the outcome of the first systematic biopsy.
