A Preliminary Evaluation of Advanced Oxidation Protein Products (AOPPs) as a Potential Approach to Evaluating Prognosis in Early-Stage Breast Cancer Patients and Its Implication in Tumour Angiogenesis: A 7-Year Single-Centre Study

Abstract

Breast cancer (BrC) is a highly prevalent tumour among women. The high incidence and mortality rate of BrC prompts researchers to search for new markers that will provide information on the possible impact of the therapy on the risk of cancer-related events. This study aimed to investigate whether the level of advanced oxidation protein products (AOPPs) may have a potential impact on disease-free (DFS) and overall survival (OS) in BrC patients with early-stage cancer. Additionally, we tried to assess the relationship between AOPPs and angiogenic parameters. In this study, the pre- and post-treatment AOPP levels were examined in the serum of 70 newly diagnosed BrC women. The receiver operating characteristic curve identified pre- and post-treatment AOPPs to be above 9.37 μM and 10.39 μM, respectively, as the best cut-off values to predict the risk of cancer relapse. Additionally, Kaplan-Meier survival analysis indicated that pre- and post-treatment AOPPs above 9.37 μM and 10.39 μM were associated with significantly poorer OS. The uni- and multivariate Cox regression analysis highlighted that lower levels of pre- and post-treatment AOPPs were associated with a longer duration without relapse or cancer-related death. A positive correlation between concentrations of pre-treatment AOPPs and vascular endothelial growth factor A, and negative correlations with levels of soluble forms of vascular endothelial growth factor receptor type 1 and 2, were found. In conclusion, AOPPs appear to have an important role in predicting cancer-related events and may potentially serve as a simple prognostic marker in clinical practice.

Keywords: AOPP; adjuvant treatment; disease-free survival; early-stage breast cancer; overall survival.

Figure 1

Flowchart describing enrolment of breast cancer participants.

Figure 2

A graph showing nine ROC curves for the Ki-67 expression, pre- and post-treatment concentrations of AOPPs, VEGF-A, sVEGFR1 and sVEGFR2 with different values of area under the curve (AUC) and p-values for predicting disease-free survival.

Figure 3

Kaplan–Meier curves for the overall survival (OS) and disease-free survival (DFS) analysis regarding (A,B) pre-treatment AOPP concentrations according to median; (C,D) pre-treatment AOPP concentrations according to ROC cut-off; (E,F) post-treatment AOPP concentrations according to median; (G,H) post-treatment AOPP concentrations according to ROC cut-off. Significant differences are marked by bold p-values.

Figure 4

A graph showing nine ROC curves for Ki-67 expression, and pre- and post-treatment concentrations of AOPP, VEGF-A, sVEGFR1, and sVEGFR2 with different values of area under the curve (AUC) and p-values for predicting overall survival.