Cancer is the second leading cause of death worldwide. Despite the immense research focused in this area, one is still not able to predict disease trajectory. To overcome shortcomings in cancer disease study and monitoring, we describe an exciting research direction: cellular mechanophenotyping. Cancer cells must overcome many challenges involving external forces from neighboring cells, the extracellular matrix, and the vasculature to survive and thrive. Identifying and understanding their mechanical behavior in response to these forces would advance our understanding of cancer. Moreover, used alongside traditional methods of immunostaining and genetic analysis, mechanophenotyping could provide a comprehensive view of a heterogeneous tumor. In this perspective, we focus on new technologies that enable single-cell mechanophenotyping. Single-cell analysis is vitally important, as mechanical stimuli from the environment may obscure the inherent mechanical properties of a cell that can change over time. Moreover, bulk studies mask the heterogeneity in mechanical properties of single cells, especially those rare subpopulations that aggressively lead to cancer progression or therapeutic resistance. The technologies on which we focus include atomic force microscopy, suspended microchannel resonators, hydrodynamic and optical stretching, and mechano-node pore sensing. These technologies are poised to contribute to our understanding of disease progression as well as present clinical opportunities.

Elucidating how the spatial organization of extrinsic signals modulates cell behavior and drives biological processes remains largely unexplored because of challenges in controlling spatial patterning of multiple microenvironmental cues in vitro. Here, we describe a high-throughput method that directs simultaneous assembly of multiple cell types and solid-phase ligands across length scales within minutes. Our method involves lithographically defining hierarchical patterns of unique DNA oligonucleotides to which complementary strands, attached to cells and ligands-of-interest, hybridize. Highlighting our method's power, we investigated how the spatial presentation of self-renewal ligand fibroblast growth factor-2 (FGF-2) and differentiation signal ephrin-B2 instruct single adult neural stem cell (NSC) fate. We found that NSCs have a strong spatial bias toward FGF-2 and identified an unexpected subpopulation exhibiting high neuronal differentiation despite spatially occupying patterned FGF-2 regions. Overall, our broadly applicable, DNA-directed approach enables mechanistic insight into how tissues encode regulatory information through the spatial presentation of heterogeneous signals.