RESUMO
Cell-free DNA (cfDNA) testing is the core of most liquid biopsy assays. In particular, cfDNA fragmentation features could facilitate non-invasive cancer detection due to their interconnection with tumor-specific epigenetic alterations. However, the final cfDNA fragmentation profile in a purified sample is the result of a complex interplay between informative biological and artificial technical factors. In this work, we use ddPCR to study cfDNA lengths in colorectal cancer patients and observe shorter and more variable cfDNA fragments in accessible chromatin loci compared to the densely packed pericentromeric region. We also report a convenient qPCR system suitable for screening cfDNA samples for artificial high molecular weight DNA contamination.
Assuntos
Biomarcadores Tumorais , Ácidos Nucleicos Livres , DNA Tumoral Circulante , Biópsia Líquida/métodos , Neoplasias/diagnóstico , Neoplasias/genética , Estudos de Casos e Controles , Gerenciamento Clínico , Suscetibilidade a Doenças , Detecção Precoce de Câncer , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Biópsia Líquida/normas , Espécies Reativas de Oxigênio/metabolismoRESUMO
Early diagnostics significantly improves the survival of patients with renal cell carcinoma (RCC), which is the prevailing type of adult kidney cancer. However, the absence of clinically obvious symptoms and effective screening strategies at the early stages result to disease progression and survival rate reducing. The study was focused on revealing of potential low molecular biomarkers for early-stage RCC. The untargeted direct injection mass spectrometry-based metabolite profiling of blood plasma samples from 51 non-cancer volunteers (control) and 78 patients with different RCC subtypes and stages (early stages of clear cell RCC (ccRCC), papillary RCC (pRCC), chromophobe RCC (chrRCC) and advanced stages of ccRCC) was performed. Comparative analysis of the blood plasma metabolites between the control and cancer groups provided the detection of metabolites associated with different tumor stages. The designed model based on the revealed metabolites demonstrated high diagnostic power and accuracy. Overall, using the metabolomics approach the study revealed the metabolites demonstrating a high value for design of plasma-based test to improve early ccRCC diagnosis.