Proteomic identification of predictive biomarkers of resistance to neoadjuvant chemotherapy in luminal breast cancer: A possible role for 14-3-3 theta/tau and tBID?

Abstract

Introduction

Chemotherapy resistance is a major obstacle in effective neoadjuvant treatment for estrogen receptor-positive breast cancer. The ability to predict tumour response would allow chemotherapy administration to be directed towards only those patients who would benefit, thus maximising treatment efficiency. We aimed to identify putative protein biomarkers associated with chemotherapy resistance, using fresh tumour samples with antibody microarray analysis and then to perform pilot clinical validation experiments.

Materials and methods

Chemotherapy resistant and chemotherapy sensitive tumour samples were collected from breast cancer patients who had received anthracycline based neoadjuvant therapy consisting of epirubicin with cyclophosphamide followed by docetaxel. A total of 5 comparative proteomics experiments were performed using invasive ductal carcinomas which demonstrated estrogen receptor positivity (luminal subtype). Protein expression was compared between chemotherapy resistant and chemotherapy sensitive tumour samples using the Panorama XPRESS Profiler725 antibody microarray containing 725 antibodies from a wide variety of cell signalling and apoptosis pathways. A pilot series of archival samples was used for clinical validation of putative predictive biomarkers.

Results

AbMA analysis revealed 38 differentially expressed proteins which demonstrated at least 1.8 fold difference in expression in chemotherapy resistant tumours and 7 of these proteins (Zyxin, 14-3-3 theta/tau, tBID, Pinin, Bcl-xL, RIP and MyD88) were found in at least 2 experiments. Clinical validation in a pilot series of archival samples revealed 14-3-3 theta/tau and tBID to be significantly associated with chemotherapy resistance.

Conclusions

For the first time, antibody microarrays have been used to identify proteins associated with chemotherapy resistance using fresh breast cancer tissue. We propose a potential role for 14-3-3 theta/tau and tBID as predictive biomarkers of neoadjuvant chemotherapy resistance in breast cancer. Further validation in a larger sample series is now required.

Introduction

Molecular diversity within breast tumours can be characterised according to estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2) status. Luminal (ER positive), HER2 positive and triple negative (ER negative, PR negative, HER2 negative) tumours are biologically different and exhibit distinct clinical behaviour [1], [2], [3], [4], [5]. For locally advanced breast cancer, neoadjuvant chemotherapy can be administered with the aim to decrease the tumour size and enable breast conserving surgery to be offered. Molecular subtype is significantly associated with response to neoadjuvant chemotherapy and ER positive subtypes demonstrate a very poor rate of pathological complete response [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15]. A number of studies have investigated the use of gene signatures for the prediction of response to neoadjuvant chemotherapy [16], [17], [18] whilst proteomic studies have, to date, largely explored cell line models of chemotherapy resistance to identify putative predictive biomarkers [19]. Several potential protein biomarkers of anthracycline or taxane resistance in breast cancer have been identified during such research, including 14-3-3 family proteins, cyclins, heat shock protein 27 and peroxiredoxins [19], [20], [21], [22]. There is however a paucity of clinical proteomics research for the investigation of fresh breast tumour samples in order to identify putative protein biomarkers which may be associated with resistance to neoadjuvant chemotherapy [19]. We aimed to examine ER positive breast cancer samples from patients treated with neoadjuvant chemotherapy in order to identify proteins which may be associated with resistance. In order to do this we employed antibody microarray (AbMA) technology [19], [22], [23], [24], [25] to assess the differential expression of 725 protein targets simultaneously per experiment.