2022

Jokela, Tiina A.; Carlson, Eric G.; LaBarge, Mark A.

Predicting how anticancer therapeutics will function in people based on preclinical studies remains a significant challenge. High rates of phase II clinical trial failures indicate that many candidate therapeutics that pass preclinical studies lack efficacy in patients. The discovery of oncogenes and tumor suppressors has led to vast investments into developing technologies that enable exploration of the total complexity of genomes and proteomes intrinsic to cells. These technologies seek to define how mutations contribute to cancer development and progression. An important and unexpected outcome of those massive investments to understand cancer as a cell-intrinsic problem is the undeniable conclusion that mutations do not explain everything. Indeed, the fact that frankly malignant cells can be phenotypically normal, when exposed to a normal tissue microenvironment (ME), suggests that there is a dominant role of the ME. Tumor microenvironments modulate the malignant phenotypes of cells and impact drug responses. In most drug screens, conventional two-dimensional plastic dishes are the substrate of choice for cell culture and rodents are used as the primary in vivo model, but these modalities lack context in a way that is relevant to predicting drug activity. Alternatively, combinatorial microenvironment microarray platforms provide a high-throughput means of exploring cell-based functional responses in diverse microenvironmental milieus. Data from these techniques are single-cell resolution and encapsulate cell–cell heterogeneity, which provides direct linkages between cellular phenotypes, such as drug responses, and MEs. This chapter focuses on the applications and analytic approaches used for functional cell-based exploration of combinatorial MEs using microarray technology.