multi-step-variable-height-photolithography-for-valved-multilayer

Multi-step Variable Height Photolithography for Valved Multilayer Microfluidic Devices

Microfluidic systems have enabled powerful new approaches to high-throughput biochemical and biological analysis. However, there remains a barrier to ...

Stanford University

Secreted proteins including cytokines, chemokines, and growth factors represent important functional regulators mediating a range of cellular behavior and cell-cell paracrine/autocrine signaling, e.g., in the immunological system (Rothenberg, 2007), tumor microenvironment (Hanahan and Weinberg, 2011), or stem cell niche (Gnecchi etal., 2008). Detection of these proteins is of great value not only in basic cell biology but also for diagnosis and therapeutic monitoring of human diseases such as cancer. However, due to co-production of multiple effector proteins from a single cell, referred to as polyfunctionality, it is biologically informative to measure a panel of secreted proteins, or secretomic signature, at the level of single cells. Recent evidence further indicates that a genetically identical cell population can give rise to diverse phenotypic differences (Niepel etal., 2009). Non-genetic heterogeneity is also emerging as a potential barrier to accurate monitoring of cellular immunity and effective pharmacological therapies (Cohen etal., 2008; Gascoigne and Taylor, 2008), but can hardly assessed using conventional approaches that do not examine cellular phenotype at the functional level. It is known that cytokines, for example, in the immune system define the effector functions and lineage differentiation of immune cells. In this article, we hypothesize that protein secretion profile may represent a universal measure to identify the definitive correlate in the larger context of cellular functions to dissect cellular heterogeneity and evolutionary lineage relationship in human cancer.

Single-cell protein secretomic signatures as potential correlates to tumor cell lineage evolution and cell-cell interaction.

Erratum: single-cell protein secretomic signatures as potential correlates to tumor cell lineage evolution and cell-cell interaction.

It is increasingly recognized that infiltrating immune cells contribute to the pathogenesis of a wide range of solid tumors. The paracrine signaling between the tumor and the immune cells alters the functional state of individual tumor cells and, correspondingly, the anticipated response to radiation or chemotherapies, which is of great importance to clinical oncology. Here we present a high-density microchip platform capable of measuring a panel of paracrine signals associated with heterotypic tumor-immune cell interactions in the single-cell, pair-wise manner. The device features a high-content cell capture array of 5000+ sub-nanoliter microchambers for the isolation of single and multi-cell combinations and a multi-plex antibody "barcode" array for multiplexed protein secretion analysis from each microchamber. In this work, we measured a panel of 16 proteins produced from individual glioma cells, individual macrophage cells and varying heterotypic multi-cell combinations of both on the same device. The results show changes of tumor cell functional phenotypes that cannot be explained by an additive effect from isolated single cells and, presumably, can be attributed to the paracrine signaling between macrophage and glioma cells. The protein correlation analysis reveals the key signaling nodes altered by tumor-macrophage communication. This platform enables the novel pair-wise interrogation of heterotypic cell-cell paracrine signaling at the individual cell level with an in-depth analysis of the changing functional phenotypes for different co-culture cell combinations.

A microchip platform for interrogating tumor-macrophage paracrine signaling at the single-cell level.

Despite recent advances in single-cell genomic, transcriptional, and mass-cytometric profiling, it remains a challenge to collect highly multiplexed measurements of secreted proteins from single cells for comprehensive analysis of functional states. Herein, we combine spatial and spectral encoding with polydimethylsiloxane (PDMS) microchambers for codetection of 42 immune effector proteins secreted from single cells, representing the highest multiplexing recorded to date for a single-cell secretion assay. Using this platform to profile differentiated macrophages stimulated with lipopolysaccharide (LPS), the ligand of Toll-like receptor 4 (TLR4), reveals previously unobserved deep functional heterogeneity and varying levels of pathogenic activation. Uniquely protein profiling on the same single cells before and after LPS stimulation identified a role for macrophage inhibitory factor (MIF) to potentiate the activation of LPS-induced cytokine production. Advanced clustering analysis identified functional subsets including quiescent, polyfunctional fully activated, partially activated populations with different cytokine profiles. This population architecture is conserved throughout the cell activation process and prevails as it is extended to other TLR ligands and to primary macrophages derived from a healthy donor. This work demonstrates that the phenotypically similar cell population still exhibits a large degree of intrinsic heterogeneity at the functional and cell behavior level. This technology enables full-spectrum dissection of immune functional states in response to pathogenic or environmental stimulation, and opens opportunities to quantify deep functional heterogeneity for more comprehensive and accurate immune monitoring.

Article	Year
Single-cell protein secretomic signatures as potential correlates to tumor cell lineage evolution and cell-cell interaction. Frontiers in oncology\| PubMed ID: 23390614	2013
Erratum: single-cell protein secretomic signatures as potential correlates to tumor cell lineage evolution and cell-cell interaction. Frontiers in oncology\| PubMed ID: 23579430	2013
A microchip platform for interrogating tumor-macrophage paracrine signaling at the single-cell level. Lab on a chip\| PubMed ID: 25057779	2014
Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands. Proceedings of the National Academy of Sciences of the United States of America\| PubMed ID: 25646488	2015

Kara Brower

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