Prospective Breast Cancer Biomarkers Identified Using miR-526b-Driven Metabolic Alterations.

Breast cancer is a heterogeneous disease driven by dysregulated cellular processes, including altered metabolic pathways. The oncogenic microRNA miR-526b influences several cancer hallmark phenotypes and holds promise as a plasma biomarker. Given miR-526b's role in metabolic regulation, we have decided LDHA, PDHA1, ATP5A1, and TIGAR that may help to identify additional biomarkers for breast cancer detection. We analyzed mRNA expression of these 4 metabolic markers in breast cancer tissue biopsies and plasma samples from patients and disease-free controls, using publicly available datasets and RT-qPCR validation. Diagnostic performance was evaluated using univariate and multivariate logistic regression and LASSO regression modeling. The potential of combining ATP5A1 with pri-miR-526b expression to improve plasma biomarker accuracy was also assessed. Individually, none of the metabolic markers demonstrated sufficient sensitivity or specificity as plasma biomarkers. However, combining markers via logistic and LASSO regression improved classification performance. ATP5A1 showed strong biomarker potential in biopsy tissue samples but limited utility in blood plasma. The combination of ATP5A1 with pri-miR-526b significantly enhanced plasma-based diagnostic accuracy, highlighting the value of integrated biomarker panels. Our study validates the potential of miR-526b-regulated metabolic genes as complementary breast cancer biomarkers. While ATP5A1 shows promise in tissue, plasma-based screening benefits from combining multiple markers, including pri-miR-526b. Further research is needed to refine plasma biomarker panels for effective early detection of breast cancer.