Here we present a strategy for the fabrication of biomimetic nanoarrays, based on the use of DNA origami, that permit the multivalent investigation of ligand-receptor molecule interactions in cancer cell spreading, with nanoscale spatial resolution and single-molecule control. We employed DNA-origami to control the nanoscale spatial organization of integrin-and epidermal growth factor (EGF)-binding ligands that modulate epidermal cancer cell behaviour. By organizing these multivalent DNA nanostructures in nanoarray configurations on nanopatterned surfaces, we demonstrated the cooperative behaviour of integrin-and EGF-ligands in the spreading of human cutaneous melanoma cells: this cooperation was shown to depend on both the number and ratio of the selective ligands employed. Notably, the multivalent biochips we have developed allowed for this cooperative effect to be demonstrated with single-molecule control and nanoscale spatial resolution. By and large, the platform presented here is of general applicability for the study, with molecular control, of different multivalent interactions governing biological processes, from the function of cell-surface receptors, to protein-ligand binding and pathogen inhibition.
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as
To develop new therapeutics, researchers are exploring the role of the immune system in defending the body against tumors. Modelling induced malignant cell death in vitro is of paramount importance. Tumor and immune cell co-cultures were created in 96 well plates and using live-cell analysis, various parameters of tumor killing were quantified in real-time. Red nuclear labeled target cells and various densities of pre-activated PBMCs (α-CD3/IL2, 4 d) were seeded in combination with IncuCyte Annexin V green apoptosis detection reagent. Images were acquired every 2 h for 3 d using IncuCyte. Analysis of the fluorescence images provides measurement of target cell number and apoptosis. Enhancement of the phase contrast image analytics enabled single cell segmentation, permitting determination of effector cell parameters; cell number, shape and, using fluorescently labeled surface marker antibodies, protein expression levels. In addition, studies into spatial interactions of target and effector cells were conducted. To exemplify how these new analytical features can be used to investigate the biology of tumor cell killing, studies of a α-hCD3xCD19 bi-specific T-cell engager antibody induced cytotoxicity were performed. Further characterization of effects on cell cycle during target cell death and use of more advanced 3D models of immune cell killing were also assessed, demonstrating the flexibility of live-cell analysis as a powerful tool for analyzing immune cell killing. Advances in data analytics has enabled the multiplexing of target cell quantification alongside the interrogation of effector cell properties in live cells. The added insight gained from these approaches will hopefully lead to improved immuno-therapeutics.
The ability to perform concurrent, dynamic measurements of multiple parameters of tumor cell health can provide valuable mechanistic insight. For example, a single compound may exhibit cytotoxic and/or cytostatic properties, depending on the tumor cell type being targeted as well as concentration and duration of treatment. In addition, evaluating immune-cancer cell interactions or metabolic exchange between cancer and stromal cells can be a critical component of elucidating mechanism of action. However, standard methods of evaluating compound effects on tumor cell health are largely limited to single parameter, population-based, endpoint measurements. Here we describe a new live-cell imaging solution providing flexibility in fluorescent readouts of cancer cell health, metabolism, and cell-cell interactions. Phase and fluorescent images were acquired and analyzed using an IncuCyte live cell analysis system. Changeable filter sets enabled selection of fluorescent readouts in designated combinations of green, orange, red, and/or NIR spectra as well as a dual excitation, single emission filter set to provide ratiometric measurements of cytoplasmic ATP. Using this approach, we demonstrate concentration- and time-dependent effects of compounds on cell cycle and cell death. Kazusamycin A (0.08-20 nM) treatment of HT-1080 cells resulted in a concentration-dependent cell cycle arrest as measured by a fluorescence ubiquitination-based cell cycle indicator. An increase in the percentage of cells in G1 (22% vs 31% of vehicle or kazusamycin A-treated cells, respectively) was observed as early as four hours after treatment and increased over the 3-day time course. Cell death was evaluated concurrently using an Annexin V reagent. Apoptosis was observed only at high concentrations (6.67-20 nM) and after 18 hours of incubation. Similar results were observed in MDA-MB-231 cells. Incorporation of genetically encoded and/or live-cell immunocytochemistry reagents enables monitoring subpopulations of cells in co-culture models. We utilized these techniques to monitor dynamic readouts in target and effector populations in an immune cell killing assay. MDA-MB-231 cells were transduced to express a fluorescent nuclear marker and were co-cultured with PBMCs with and without activation (ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator + IL-2). A decrease in nuclear counts accompanied by apoptosis (Annexin V-positive cells) of MDA-MB-231 target cells was observed within 27 hours in the presence of activated PBMCs. Measurements of target cell proliferation and apoptosis were unaffected by the presence of PBMCs without activation cocktail. Additional example datasets of cancer cell metabolism, proliferation, and death readouts in mono- and co-culture models will be shared to illustrate the value of flexible, multi-parameter live cell analysis. Citation Format: Cicely L. Schramm, John N. Rauch, Libuse Oupicka, Laura A. Skerlos, Nicola J. Bevan, Gillian F. Lovell, Sandra Perez-Garrido, Grigory S. Filonov, Yong X. Chen, Ilya Kovalenko, Susan Foltin, Hinnah Campwala, Timothy J. Dale, Daniel M. Appledorn. Real-time visualization and quantification of flexible, multi-parameter indicators of cancer cell heath and metabolism using live-cell analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1834.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.