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Anstine et al. J Cancer Metastasis Treat 2019;5:50 I http://dx.doi.org/10.20517/2394-4722.2019.24 Page 9 of 16

upon transplantation [22,23] . Several epigenetic factors have been shown to play a role in defining mammary
epithelial cell fate. These include the histone methylation reader PYGO2 , the polycomb-repressive complex-1
[59]
member, BMI1 [60,61] , and the polycomb-repressive complex 3 member, EZH2 . BMI1 and EZH2 also play
[62]
key roles in metastasis of breast cancers, likely due to their activation of more primitive cell fates [63-66] . Yet
how these players collaborate to orchestrate the epigenetic continuum that drives fate determination and
heterogeneity is not fully understood.

Differential chromatin accessibility of both myoepithelial and luminal genes in basal cells may explain
the ability of transcriptional drivers to induce cell fate switching in committed cells. In a recent example,
overexpression of Notch1 in Smooth muscle actin (SMA)+ or K5+ myoepithelial cells, was sufficient to
commit cells to a luminal fate . Complementary to this, overexpression of p63 in luminal cells was sufficient
[67]
to reprogram them into a myoepithelial state . Although the mechanism of p63-mediated cell fate switching
[52]
is unknown, chromatin remodeling is likely required as mature luminal cells exhibit repressed chromatin
at basal gene loci . SOX10 has also emerged as a major transcriptional regulator of epithelial cell fate .
[58]
[58]
Within fMaSCs, SOX10 motifs are enriched at accessible chromatin regions flanking highly expressed genes.
Furthermore, tumors expressing high SOX10 levels exhibit neural crest-like features and high SOX10
[58]
expression is correlated with the aggressive, basal-like breast cancer subtype. As embryonic neural crest cells
are multipotent and highly mobile , SOX10 reprograming may lead to primitive cellular states that could
[68]
contribute to aggressive tumor phenotypes.

A NEW MODEL FOR THE MAMMARY EPITHELIAL HIERARCHY
Cumulative evidence from the recent papers utilizing sc-RNA-sequencing has revealed that the historical
models by which the mammary epithelial hierarchy has been traditionally represented do not accurately
portray the complexity of the system [11-14,53] . Previous models in which cellular states are depicted as discrete
populations that differentiate along restricted paths is an oversimplification [Figure 1]. Instead, recent
results indicate that heterogeneous cell populations gradually advance, and likely also retreat, through a
differentiation trajectory [11,12,53] . This is supported by the work from several groups, reporting a vast array
of epithelial transcriptional profiles throughout the stages of mammary gland development [11-14,53] . Similar
findings have redefined the hierarchical visualization of hematopoiesis . Using the new visual representation
[69]
of hematopoietic differentiation suggested by Laurenti and Gottgens as an example, we propose a similar
paradigm to represent the mammary epithelial hierarchy [Figure 2]. As depicted in this model, groups of
heterogeneous epithelial cells traverse through the differentiation landscape, passing through cellular states
that have been previously defined including fMaSCs, luminal and myoepithelial progenitors, and mature
luminal and myoepithelial lineages. The newly reported heterogeneity of these populations implies that
each cell may take a slightly different transcriptional path from the next as it undergoes differentiation.
Additionally, the array of cellular states detected within the gland at any one time suggests that variation
in temporal dynamics of differentiation may exist between individual cells. Moreover, this model implies
significant forward and reverse plasticity of cell states that could be impacted by the microenvironment. This
could partially explain historical difficulty in attempting to isolate and characterize specific subpopulations;
however, further studies are needed to test these predictions.

IMPLICATIONS FOR TUMOR INITIATION AND METASTASIS
Breast cancer is an amalgam of diseases that exhibit both inter- and intra-tumoral heterogeneity . Gene
[70]
expression profiling has led to the classification of five overarching subtypes, including luminal A, luminal B,
HER2+, basal-like, and claudin-low [71-74] . However, within each subtype, tumors can exhibit further variability
in gene expression, molecular function, and drug susceptibility conveying distinct patient outcomes. The
heterogenic nature of breast cancer is thought to arise from the combination of cellular origin, genetic and
epigenetic changes, and environmental context [1,10,70,75] .