Spatially resolved analysis of microenvironmental gradient impact on cancer cell phenotypes

Despite the physiological and pathophysiological significance of microenvironmental gradients, e.g., for diseases such as cancer, tools for generating such gradients and analyzing their impact are lacking. Here, we present an integrated microfluidic-based workflow that mimics extracellular pH gradients characteristic of solid tumors while enabling high-resolution live imaging of, e.g., cell motility and chemotaxis, and preserving the capacity to capture the spatial transcriptome. Our microfluidic device generates a pH gradient that can be rapidly controlled to mimic spatiotemporal microenvironmental changes over cancer cells embedded in a 3D matrix. The device can be reopened allowing immunofluorescence analysis of selected phenotypes, as well as the transfer of cells and matrix to a Visium slide for spatially resolved analysis of transcriptional changes across the pH gradient. This workflow is easily adaptable to other gradients and multiple cell types and can therefore prove invaluable for integrated analysis of roles of microenvironmental gradients in biology.
Despite the physiological and pathophysiological significance of microenvironmental gradients, e.g., for diseases such as cancer, tools for generating such gradients and analyzing their impact are lacking. Here, we present an integrated microfluidic-based workflow that mimics extracellular pH gradients characteristic of solid tumors while enabling high-resolution live imaging of, e.g., cell motility and chemotaxis, and preserving the capacity to capture the spatial transcriptome. Our microfluidic device generates a pH gradient that can be rapidly controlled to mimic spatiotemporal microenvironmental changes over cancer cells embedded in a 3D matrix. The device can be reopened allowing immunofluorescence analysis of selected phenotypes, as well as the transfer of cells and matrix to a Visium slide for spatially resolved analysis of transcriptional changes across the pH gradient. This workflow is easily adaptable to other gradients and multiple cell types and can therefore prove invaluable for integrated analysis of roles of microenvironmental gradients in biology.