The need for complex 3D culture models to unravel novel pathways and identify accurate biomarkers in breast cancer

Abstract

The recent cataloging of the genomic aberrations in breast cancer has revealed the diversity and complexity of the disease at the genetic level. To unravel the functional consequences of specific repertoires of mutations and copy number changes on signaling pathways in breast cancer, it is crucial to develop model systems that truly recapitulate the disease. Here we discuss the three-dimensional culture models currently being used or recently developed for the study of normal mammary epithelial cells and breast cancer, including primary tumors and dormancy. We discuss the insights gained from these models in regards to cell signaling and potential therapeutic strategies, and the challenges that need to be met for the generation of heterotypic breast cancer model systems that are amenable for high-throughput approaches.

Introduction

Breast cancer is a heterogeneous disease, encompassing multiple entities with distinct biological and clinical features [1]. The massively parallel sequencing endeavors performed by The Cancer Genome Atlas (TCGA; www.cancergenome.nih.gov), the International Cancer Genome Consortium (ICGC [2]) and individual investigators have provided a comprehensive characterization of breast cancer mainly at the genomic, but also the transcriptomic and epigenomic level. The use of this technology has demonstrated that breast cancers harbor heterogeneous constellations of somatic mutations and only few highly recurrently mutated driver genes [3], [4], [5], [6]. In fact, at base-pair resolution each breast cancer appears to be unique in its repertoire of genetic aberrations [6]. Despite this genetic heterogeneity seen between breast cancers, it is important to note that the number of specific signaling pathways activated in each molecular subtype of the disease seems to be limited [5]. In addition, massively parallel sequencing analyses of breast cancers have revealed intra-tumor genetic heterogeneity in a substantial proportion of cases [4], [7], [8]. In fact, it is currently accepted that at least a subset of breast cancers are composed of mosaics of tumor cell clones, which in addition to the founder genetic events present in all cells, also display additional genomic alterations.

It has been posited that the microenvironment exerts selective pressures on cancer cells, such as during the metastatic process or when the environment is changed due to an external selective pressure, such as drug treatment. Indeed, there is burgeoning evidence stemming from sequencing endeavors to demonstrate that primary breast cancers and their matched distant metastases are distinct in their mutational landscapes, and enrichment of populations of cancer cells harboring specific genetic alterations in the primary versus the metastatic site and vice versa has been observed [9], [10]. Also drug treatment has been reported to result in the selection of subclones, present in varying frequencies in the primary tumors, harboring mutations conferring resistance to the therapeutic agent [11], [12], [13], [14].

The impact of environmental cues on cancer is not restricted to biological or exogenous bottlenecks as exemplified above. In fact, it is plausible that throughout tumorigenesis and tumor progression, the microenvironment plays a pivotal role, as cancer cells are exposed to local selective pressures stemming from the structural and cellular microenvironment. In fact, a tumor cell is not an island [15]; instead, breast cancer cells interact with each other and with their surrounding non-malignant cells, hormones, secreted factors and the extracellular matrix (ECM). These complex microenvironmental interactions and forces contribute profoundly to the behavior, phenotype and evolution of cancer cells. For example, in estrogen receptor-negative breast cancer, increased expression levels of immune response pathway genes or increased presence of lymphocytic infiltration have been shown by independent investigators and studies to be the strongest predictor of outcome and, potentially, of chemotherapy benefit [16], [17], [18], [19].

Given the genomic complexity of breast cancer, understanding the epistatic interactions between mutations, as well as their effects on tissue function and endocrine, paracrine and autocrine signaling is germane for the development and validation of prognostic and predictive strategies. Most studies investigating the effect of genetic/epigenetic aberrations in vitro on specific aspects of cellular processes such as transformation, proliferation or signaling have been performed in oversimplified model systems, not taking alterations in tissue architecture, cell–cell interactions, or cell–microenvironment interactions into account. The understanding of the functional consequences of specific repertoires of genomic aberrations on signaling and pathway dependencies within and between the cancers cells but also with their surrounding microenvironment require model systems that truly recapitulate the disease. To date, the vast majority of functional studies using cancer cell lines are performed in traditional monolayer cultures, however, and culture systems that fully mirror human breast cancer, primary and metastatic, and its diverse cellular microenvironment have yet to be developed further.

Here, we provide an overview of the three-dimensional (3D) cell culture models currently being employed for the study of breast cancer, including co-culture systems. In addition, we discuss how these models can be used for the dissection of cell–cell and cell–stroma interactions and of the role of specific genetic aberrations or signaling pathways in normal and malignant mammary epithelial cells.