Article
Plasma exosome-derived microRNAs as potential diagnostic and prognostic biomarkers in brazilian pancreatic cancer patients
Registro en:
MARIN, Anelis Maria et al. Plasma exosome-derived microRNAs as potential diagnostic and prognostic biomarkers in brazilian pancreatic cancer patients. Biomolecules, v. 12, n. 769, p. 1–33, 2022.
2218-273X
10.3390/biom12060769
Autor
Marin, Anelis Maria
Mattar, Sibelle Botogosque
Amatuzzi, Rafaela Ferreira
Chammas, Roger
Uno, Miyuki
Zanette, Dalila Luciola
Aoki, Mateus Nóbrega
Resumen
Pancreatic cancer represents one of the leading causes of oncological death worldwide. A combination of pancreatic cancer aggressiveness and late diagnosis are key factors leading to a low survival rate and treatment inefficiency, and early diagnosis is pursued as a critical factor for pancreatic cancer. In this context, plasma microRNAs are emerging as promising players due to their non-invasive and practical usage in oncological diagnosis and prognosis. Recent studies have showed some miRNAs associated with pancreatic cancer subtypes, or with stages of the disease. Here we demonstrate plasma exosome-derived microRNA expression in pancreatic cancer patients and healthy individuals from Brazilian patients. Using plasma of 65 pancreatic cancer patients and 78 healthy controls, plasma exosomes were isolated and miRNAs miR-27b, miR-125b-3p, miR-122-5p, miR-21-5p, miR-221-3p, miR-19b, and miR-205-5p were quantified by RT-qPCR. We found that miR125b-3p, miR-122-5p, and miR-205-5p were statistically overexpressed in the plasma exosomes of pancreatic cancer patients compared to healthy controls. Moreover, miR-205-5p was significantly overexpressed in European descendants, in patients with tumor progression and in those who died from the disease, and diagnostic ability by ROC curve was 0.86. Therefore, we demonstrate that these three microRNAs are potential plasma exosome-derived non-invasive biomarkers for the diagnosis and prognosis of Brazilian pancreatic cancer, demonstrating the importance of different populations and epidemiological bias.