Reciprocal coevolution of tumors and their microenvironments underlies disease progression, yet intrinsic limitations of patient-derived xenografts and simpler cell-based models present challenges towards a deeper understanding of these intercellular communication networks. To help overcome these barriers and complement existing models, we have developed a human microphysiological system (MPS) model of the human liver acinus, a common metastatic site, and have applied this system to estrogen receptor (ER)+ breast cancer. In addition to their hallmark constitutive (but ER-dependent) growth phenotype, different ESR1 missense mutations, prominently observed during estrogen deprivation therapy, confer distinct estrogen-enhanced growth and drug resistant phenotypes not evident under cell autonomous conditions. Under low molecular oxygen within the physiological range (~5-20%) of the normal liver acinus, the estrogen-enhanced growth phenotypes are lost, a dependency not observed in monoculture. In contrast, the constitutive growth phenotypes are invariant within this range of molecular oxygen suggesting that ESR1 mutations confer a growth advantage not only during estrogen deprivation but also at lower oxygen levels. We discuss the prospects and limitations of implementing human MPS, especially in conjunction with in situ single cell hyperplexed computational pathology platforms, to identify biomarkers mechanistically linked to disease progression that inform optimal therapeutic strategies for patients.
Publication: Modeling the Effect of the Metastatic Microenvironment on Phenotypes Conferred by Estrogen Receptor Mutations Using a Human Liver Microphysiological System. Scientific Reports, June 6, 2019