ENO1 as a Biomarker of Breast Cancer Progression and Metastasis: A Bioinformatic Approach Using Available Databases

Abstract

Background: Metabolic reprogramming is one of the hallmarks of cancer, and in breast cancer (BC), several metabolic enzymes are overexpressed and overactivated. One of these, Enolase 1 (ENO1), catalyses glycolysis and is involved in the regulation of multiple signalling pathways. Objectives: This study aimed to evaluate in silico the prognostic and predictive effects of ENO1 expression in BC. Design: This is a bioinformatic in silico analysis. Methods: Using available online platforms (Kaplan–Meier [KM] plotter, receiver operating characteristic curve [ROC] plotter, cBioPortal, Genotype-2-Outcome [G-2-O], MethSurv, and Tumour–Immune System Interaction Database [TISIDB]), we performed a bioinformatic in silico analysis to establish the prognostic and predictive effects related to ENO1 expression in BC. A network analysis was performed using the Oncomine platform, and signalling, epigenetic, and immune regulation pathways were explored. Results: ENO1 was overexpressed in all the analysed Oncomine, epigenetic, and immune pathways in triple-negative, but not in hormone receptor–positive BCs. In human epidermal growth factor receptor 2 (HER2)-positive BCs, ENO1 expression showed a mixed profile. Analysis on disease progression and histological types showed ENO1 overexpression in ductal in situ and invasive carcinoma, in high-grade tumours followed by advanced or metastasis and was linked to worse survival. High ENO1 expression was also associated with relapse-free, distant metastasis-free and overall survival, irrespectively of treatment and was mainly related to basal subtype. Conclusion: ENO1 overexpression recruits a range of signalling pathways during disease progression conferring a worse prognosis and can be potentially used as a biomarker of disease progression and therapeutic target, particularly in triple-negative and in ductal invasive carcinoma.