Giannoudis Athina, Heath Alistair, Sharma Vijay
School of Dentistry, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK.
Department of Cellular Pathology, Liverpool Clinical Laboratories, Royal Liverpool Hospital, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UKK.
Breast Cancer (Auckl). 2024 Oct 19;18:11782234241285648. doi: 10.1177/11782234241285648. eCollection 2024.
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.
This study aimed to evaluate in silico the prognostic and predictive effects of ENO1 expression in BC.
This is a bioinformatic in silico analysis.
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.
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.
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.
代谢重编程是癌症的标志之一，在乳腺癌（BC）中，几种代谢酶过度表达且过度激活。其中之一，烯醇化酶1（ENO1），催化糖酵解并参与多种信号通路的调节。
本研究旨在通过计算机模拟评估ENO1表达在乳腺癌中的预后和预测作用。
这是一项计算机模拟的生物信息学分析。
利用现有的在线平台（Kaplan-Meier [KM]绘图仪、受试者工作特征曲线[ROC]绘图仪、cBioPortal、基因型-2-结果[G-2-O]、MethSurv和肿瘤-免疫系统相互作用数据库[TISIDB]），我们进行了一项计算机模拟的生物信息学分析，以确定与乳腺癌中ENO1表达相关的预后和预测作用。使用Oncomine平台进行网络分析，并探索信号、表观遗传和免疫调节通路。
在三阴性乳腺癌的所有分析的Oncomine、表观遗传和免疫通路中，ENO1均过度表达，但在激素受体阳性乳腺癌中则不然。在人表皮生长因子受体2（HER2）阳性乳腺癌中，ENO1表达呈现混合特征。对疾病进展和组织学类型的分析显示，ENO1在导管原位癌和浸润性癌、高级别肿瘤中过度表达，其次是晚期或转移性肿瘤，并且与较差的生存率相关。高ENO1表达也与无复发生存、无远处转移生存和总生存相关，与治疗无关，主要与基底亚型相关。
ENO1过度表达在疾病进展过程中募集一系列信号通路，导致预后较差，并且有可能用作疾病进展的生物标志物和治疗靶点，特别是在三阴性和导管浸润性癌中。
