Abstract

Blood-based early detection of breast cancer has recently gained novel momentum, as liquid biopsy diagnostics is a fast emerging field. In this study, we aimed to identify secreted proteins which are up-regulated both in tumour tissue and serum samples of breast cancer patients compared to normal tissue and sera. Based on two independent tissue cohorts (n = 75 and n = 229) and one serum cohort (n = 80) of human breast cancer and healthy serum samples, we characterised AGR3 as a novel potential biomarker both for breast cancer prognosis and early breast cancer detection from blood. AGR3 expression in breast tumours is significantly associated with oestrogen receptor α (P<0.001) and lower tumour grade (P<0.01). Interestingly, AGR3 protein expression correlates with unfavourable outcome in low (G1) and intermediate (G2) grade breast tumours (multivariate hazard ratio: 2.186, 95% CI: 1.008-4.740, P<0.05) indicating an independent prognostic impact. In sera analysed by ELISA technique, AGR3 protein concentration was significantly (P<0.001) elevated in samples from breast cancer patients (n = 40, mainly low stage tumours) compared to healthy controls (n = 40). To develop a suitable biomarker panel for early breast cancer detection, we measured AGR2 protein in human serum samples in parallel. The combined AGR3/AGR2 biomarker panel achieved a sensitivity of 64.5% and a specificity of 89.5% as shown by receiver operating characteristic (ROC) curve statistics. Thus our data clearly show the potential usability of AGR3 and AGR2 as biomarkers for blood-based early detection of human breast cancer.

Highlights

  • Breast cancer remains the most frequently diagnosed and leading cause of cancer deaths in women worldwide [1]

  • AGR3 mRNA expression is increased in G1/G2 grade and luminal breast tumours compared to normal tissue controls

  • The current study is the first to analyse in depth the AGR3 expression, as well as its potential clinical relevance in breast cancer

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Summary

Introduction

Breast cancer remains the most frequently diagnosed and leading cause of cancer deaths in women worldwide [1]. Therewith, early detection remains a major challenge in the management of breast cancer. Mammography has become the standard of care for breast cancer screening [3] several limitations are known concerning this procedure, such as a poor accuracy in women with dense breast parenchyma resulting in reduced clinical sensitivity and specificity [3,4]. For women at high risk to develop breast cancer, supplemental magnetic resonance imaging (MRI), an expensive technique that offers excellent imaging even around dense breast tissue, is applied [3]. The high sensitivity of MRI (85% to 100%) is compromised by a high rate of false positives (37% to 100%) resulting in unnecessary follow-up examinations (including invasive biopsies) causing further stress for the patient and costs [5]

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