Multicellular tumor spheroid model to study the multifaceted role of tumor-associated macrophages in PDAC.

While considerable efforts have been made to develop new therapies, progress in the treatment of pancreatic cancer has so far fallen short of patients' expectations. This is due in part to the lack of predictive in vitro models capable of accounting for the heterogeneity of this tumor and its low immunogenicity. To address this point, we have established and characterized a 3D spheroid model of pancreatic cancer composed of tumor cells, cancer-associated fibroblasts, and blood-derived monocytes. The fate of the latter has been followed from their recruitment into the tumor spheroid to their polarization into a tumor-associated macrophage (TAM)-like population, providing evidence for the formation of an immunosuppressive microenvironment.This 3D model well reproduced the multiple roles of TAMs and their influence on drug sensitivity and cell migration. Furthermore, we observed that lipid-based nanosystems consisting of sphingomyelin and vitamin E could affect the phenotype of macrophages, causing a reduction of characteristic markers of TAMs. Overall, this optimized triple coculture model gives a valuable tool that could find useful application for a more comprehensive understanding of TAM plasticity as well as for more predictive drug screening. This could increase the relevance of preclinical studies and help identify effective treatments.

Programmable synthetic cell networks regulated by tuneable reaction rates.

Coupled compartmentalised information processing and communication via molecular diffusion underpin network based population dynamics as observed in biological systems. Understanding how both compartmentalisation and communication can regulate information processes is key to rational design and control of compartmentalised reaction networks. Here, we integrate PEN DNA reactions into semi-permeable proteinosomes and characterise the effect of compartmentalisation on autocatalytic PEN DNA reactions. We observe unique behaviours in the compartmentalised systems which are not accessible under bulk conditions; for example, rates of reaction increase by an order of magnitude and reaction kinetics are more readily tuneable by enzyme concentrations in proteinosomes compared to buffer solution. We exploit these properties to regulate the reaction kinetics in two node compartmentalised reaction networks comprised of linear and autocatalytic reactions which we establish by bottom-up synthetic biology approaches.

A weakly supervised deep learning approach for label-free imaging flow-cytometry-based blood diagnostics.

The application of machine learning approaches to imaging flow cytometry (IFC) data has the potential to transform the diagnosis of hematological diseases. However, the need for manually labeled single-cell images for machine learning model training has severely limited its clinical application. To address this, we present iCellCnn, a weakly supervised deep learning approach for label-free IFC-based blood diagnostics. We demonstrate the capability of iCellCnn to achieve diagnosis of Sézary syndrome (SS) from patient samples on the basis of bright-field IFC images of T cells obtained after fluorescence-activated cell sorting of human peripheral blood mononuclear cell specimens. With a sample size of four healthy donors and five SS patients, iCellCnn achieved a 100% classification accuracy. As iCellCnn is not restricted to the diagnosis of SS, we expect such weakly supervised approaches to tap the diagnostic potential of IFC by providing automatic data-driven diagnosis of diseases with so-far unknown morphological manifestations.

Microfluidic formation of proteinosomes.

Herein we describe a novel microfluidic method for the generation of proteinosome micro-droplets, based on bovine serum albumin and glucose oxidase conjugated to PNIPAAm chains. The size of such water-in-oil droplets is regulated via control of the input reagent flow rate, with generated proteinosome populations exhibiting narrower size distributions than those observed when using standard bulk methodologies. Importantly, proteinosomes transferred from an oil to an aqueous-environment remain intact, become fully hydrated and exhibit an increase in average size. Moreover, functional proteinosomes prepared via microfluidics exhibit lower Km values and higher enzymatic activities than proteinosomes produced by bulk methodologies.