Microfluidic source-sink model reveals effects of biophysically distinct CXCL12 isoforms in breast cancer chemotaxis

Abstract

Chemokines critically regulate chemotaxis in normal and pathologic states, but there is limited understanding of how multicellular interactions generate gradients needed for cell migration. Previous studies of chemotaxis of CXCR4+ cells toward chemokine CXCL12 suggest the requirement of cells expressing scavenger receptor CXCR7 in a source-sink system. We leveraged an established microfluidic device to discover that chemotaxis of CXCR4 cells toward distinct isoforms of CXCL12 required CXCR7 scavenging only under conditions with higher than optimal levels of CXCL12. Chemotaxis toward CXCL12-β and -γ isoforms, which have greater binding to extracellular molecules and have been largely overlooked, was less dependent on CXCR7 than the more commonly studied CXCL12-α. Chemotaxis of CXCR4+ cells toward even low levels of CXCL12-γ and CXCL12-β still occurred during treatment with a FDA-approved inhibitor of CXCR4. We also detected CXCL12-γ only in breast cancers from patients with advanced disease. Physiological gradient formation within the device facilitated interrogation of key differences in chemotaxis among CXCL12 isoforms and suggests CXCL12-γ as a biomarker for metastatic cancer.

Surface-templated hydrogel patterns prompt matrix-dependent migration of breast cancer cells towards chemokine-secreting cells

“…We previously described culture, lentiviral transduction, and migration of 231 cells expressing CXCR4 towards 231 cells secreting CXCL12. [17, 18] Briefly, we transduced 231 cells sequentially with a CXCR4-GFP fusion [29] and NLS-AcGFP to facilitate receptor-based migration and image-based tracking of nuclei [18], respectively. We expressed CXCL12-isoforms fused to Gaussia luciferase (GL) upstream of the fluorescent protein mCherry in a pLVX IRES vector, to facilitate proportional fluorescence sorting for CXCL12-expressing cells [18].…”

“…Parameters for diffusion of CXCL12 (MW ≈ 10 kDa) were estimated based on the Stokes-Einstein equation relating hydrodynamic radius with diffusion rate, and published values in the literature for diffusion of large molecules in collagen [34]. Flux of CXCL12 molecules at one end of the model was calculated based on the estimated rate of CXCL12 production by cells [18] and on the geometry of the hydrogel system. A reaction-diffusion COMSOL module was used to simulate binding of the secreted soluble factors to uniformly distributed binding sites, representing matrigel proteoglycans in the collagen matrix.…”

“…Although these assays isolate individual aspects of gradient formation and sensing, they fail to replicate how multiple cell types and matrix interactions together define a gradient. We previously developed an experimental source-sink system to replicate the formation of defined soluble gradients between spatially-patterned cells that secrete ligands (source) and cells that scavenge ligands (sink) [17, 18]. These previous studies capture the involvement of multiple cell types in source-sink gradient formation and the role of ligand binding to the device- and cell-surfaces.…”

A Comprehensive Analysis of CXCL12 Isoforms in Breast Cancer1,2

“…Gene expression also forms the basis of the PAM50 molecular subtyping of breast cancer as well as Oncotype Dx, a widely used predictive model for chemotherapy response in breast cancer [59], [60], [61], [62]. Specifically for CXCL12-α, -β, and -γ, mRNA levels as measured by quantitative reverse transcription–polymerase chain reaction correlate with protein levels as measured by ELISA [63]. We also recognize that this study has limitations based on the data publicly available through the TCGA.…”

Gradient generation platforms: new directions for an established microfluidic technology

“…The generation of lumens and in vitro blood capillaries are another area of interest which will yield important insights into cell migration, particularly for oncology applications (Figure 2B, e.g. liver cancer 71 , breast cancer 72 , bonne marrow lymphoma 73 ). Lumen-based organotypic models have the ability to reproduce interfaces between a 2D environment and a 3D environment in a situation where form imparts function (i.e.…”