Breast cancer classification by proteomic technologies: Current state of knowledge

Abstract

Breast cancer is traditionally considered as a heterogeneous disease. Molecular profiling of breast cancer by gene expression studies has provided us an important tool to discriminate a number of subtypes. These breast cancer subtypes have been shown to be associated with clinical outcome and treatment response. In order to elucidate the functional consequences of altered gene expressions related to each breast cancer subtype, proteomic technologies can provide further insight by identifying quantitative differences at the protein level. In recent years, proteomic technologies have matured to an extent that they can provide proteome-wide expressions in different clinical materials. This technology can be applied for the identification of proteins or protein profiles to further refine breast cancer subtypes or for discovery of novel protein biomarkers pointing towards metastatic potential or therapy resistance in a specific subtype. In this review, we summarize the current state of knowledge of proteomic research on molecular breast cancer classification and discuss important aspects of the potential usefulness of proteomics for discovery of breast cancer-associated protein biomarkers in the clinic.

Introduction

Breast cancer affects more than 1.3 million women worldwide each year and accounts for about 14% of cancer-related deaths [1]. The incidence of breast cancer has increased over the past decades and is expected to rise substantially in the coming years [2]. Hence, breast cancer will remain a considerable health burden.

Work on breast cancer has revealed substantial tumor heterogeneity consisting of different molecular subtypes, each with distinct biological and clinical characteristics [3], [4]. In the pivotal study by Perou et al. [5], it has been shown that differential gene expression patterns account for heterogeneity among breast carcinomas. Based on the so-called intrinsic gene signatures, four major breast cancer subtypes were initially classified: luminal, HER2-enriched, basal-like and normal breast-like subtype. Subsequent studies by Perou et al. and others have expanded these initial findings by providing additional information for further refinements and adjustments of the breast cancer classification [3], [4]. Within the luminal subtype characterized by the expression of luminal epithelial markers, three groups are currently recognized: luminal A, luminal B/HER2-negative and luminal B/HER2-positive. Basal-like breast cancer is a heterogeneous group of tumors comprising different histologies, which express basal epithelial markers. The normal breast-like subtype was located in a cluster containing normal breast and benign tumor samples and showed overexpression of genes related to adipose tissue and non-epithelial cell types in the original and subsequent validation studies [3], [4], [5]. This subtype may also be a technical artifact due to low tumor cellularity [6]. Hence, the normal breast-like subtype was often overlooked and was consequently poorly characterized.

The classification of breast cancer based on gene expression patterns has resulted into attempts to characterize clinically meaningful subgroups showing correlation with survival [7], [8], disease relapse [8], site of preference of metastatic spread [9] and chemotherapy response [8], [10]. Since microarray techniques are rather expensive and not readily available, immunohistochemistry (IHC) is an important method to define surrogate protein biomarkers for the classification of breast cancer [11]. The main advantages of IHC are its lower costs and easy implementation into standard pathology workflow. It has been shown that the molecular classification by microarray analysis corresponds reasonably well to IHC classification of different breast carcinomas [12], [13]. Consequently, molecular and IHC classifications are concomitantly used to define the breast cancer subtypes (Table 1).

Ongoing research will identify new subtypes within the designated breast cancer classification [14]. Complementary to the genomic-based approach, proteomics might provide new insights into aberrant processes among breast cancer subtypes and may identify additional proteins or protein profiles to refine current breast cancer classifications. Moreover, proteomics might reveal biological insights and identify protein biomarkers defining differences in therapy resistance, prognosis and metastatic spread within a specific subtype. The purpose of this review is to discuss the current state of knowledge of proteomic studies conducted in relation with the molecular classification of breast cancer.