Expressão Diferencial dos Transcritos dos Genes HPN, GSTM3 e NETO2 para Diagnóstico de Pacientes com Câncer de Próstata

Abstract

Prostate Cancer (PCa) is the most common cancer among the male population worldwide, making it a public health problem. Indolent in its early stages, it requires more accurate diagnostic methods, as serum levels of Prostate-Specific Antigen (PSA) are not exclusive to malignancy cases. Panels of molecular markers have shown promise, aiding in the clinical management of patients. Presently, we aim to characterize a new set of biomarkers at the transcriptional level, aiming to establish a tool for the early diagnosis of the disease. For this, data available in the The Cancer Genome Atlas (TCGA) for the transcripts of KLK3, AR, HPN, GSTM3, NETO2, PRUNE2, FOLH1, and PCA3 in PCa tissues (n = 461) and adjacent non tumoral tissues (n = 51) were initially accessed. Only AR transcripts did not differentiate the samples, and through Receiver Operating Characteristic (ROC) curve analyses, the genes GSTM3, HPN, and NETO2 stood out, with AUC ≥ 90 (p < 0.05). Thus, these genes were quantified by qPCR in RNA samples extracted from the blood of ten patients diagnosed with PCa and twelve healthy individuals. Again, the three markers differed between the study groups, with Area Under de Courve (AUC) > 90 (p < 0.05). Therefore, by different methodologies, the genes HPN, GSTM3, and NETO2 showed relevant diagnostic potential, suggesting their combined analysis, which could be included in optimized diagnostic strategies for the disease, promoting quality of life, in line with the UN Sustainable Development Goals (SDGs) 3.