No abstract

One of the obstacles limiting progress in the development of effective cancer therapies is the shortage of preclinical models that capture the dynamic nature of tumor microenvironments. Interstitial flow strongly impacts tumor response to chemotherapy; however, conventional in vitro cancer models largely disregard this key feature. Here, a proof of principle microfluidic platform for the generation of large arrays of breast tumor spheroids that are grown under close-to-physiological flow in a biomimetic hydrogel is reported. This cancer spheroids-on-a-chip model is used for time-and labor-efficient studies of the effects of drug dose and supply rate on the chemosensitivity of breast tumor spheroids. The capability to grow large arrays of tumor spheroids from patient-derived cells of different breast cancer subtypes is shown, and the correlation between in vivo drug efficacy and on-chip spheroid drug response is demonstrated. The proposed platform can serve as an in vitro preclinical model for the development of personalized cancer therapies and effective screening of new anticancer drugs.

Many applications of inorganic nanoparticles (NPs), including photocatalysis, photovoltaics, chemical and biochemical sensing, and theranostics, are governed by NP optical properties. Exploration and identification of reaction conditions for the synthesis of NPs with targeted spectroscopic characteristics is a time-, labor-, and resource-intensive task, as it involves the optimization of multiple interdependent reaction conditions. Integration of machine learning (ML) and microfluidics (MF) offers accelerated identification and optimization of reaction conditions for NP synthesis. Here, an autonomous ML-driven, oscillatory MF platform for the synthesis of NPs is reported. The platform utilized multiple recipes and reaction times for the synthesis of NPs with different dimensions, conducted spectroscopic NP characterization, and employed ML approaches to analyze multiple yet prioritized spectroscopic NP characteristics, and identified reaction conditions for the synthesis of NPs with targeted optical properties. The platform is also used to develop an understanding of the relationship between reaction conditions and NP properties. This study shows the strong potential of ML-driven oscillatory MF platforms in materials science and paves the way for automated NP development.

Chiral packing of ligands on the surface of nanoparticles (NPs) is of fundamental and practical importance, as it determines how NPs interact with each other and with the molecular world. Here, for gold nanorods (NRs) capped with end-grafted nonchiral polymer ligands, we show a new mechanism of chiral surface patterning. Under poor solvency conditions, an originally smooth polymer layer segregates into helicoidally organized surface-pinned micelles (patches). The unique helicoidal morphology is dictated by the polymer grafting density and the ratio of the polymer ligand length-to-nanorod radius, while outside this specific parameter space, small random and shish-kebob patches, as well as a uniformly thick polymer layer are formed. We characterize polymer surface morphology by the theoretical and experimental state diagrams. The helicoidally organized polymer patches on the NR surface can be used as a template for the helicoidal organization of other NPs, masked synthesis on the NR surface, as well as the exploration of new NP self-assembly modes.

Interactions between tumor cells and the extracellular matrix (ECM) are an important factor contributing to therapy failure in cancer patients. Current in vitro breast cancer spheroid models examining the role of mechanical properties on spheroid response to chemotherapy are limited by the use of two-dimensional cell culture, as well as simultaneous variation in hydrogel matrix stiffness and other properties, e.g., hydrogel composition, pore size, and cell adhesion ligand density. In addition, currently used hydrogel matrices do not replicate the filamentous ECM architecture in a breast tumor microenvironment. Here, we report a collagen-alginate hydrogel with a filamentous architecture and a 20-fold variation in stiffness, achieved independently of other properties, used for the evaluation of estrogen receptor-positive breast cancer spheroid response to doxorubicin. The variation in hydrogel mechanical properties was achieved by altering the degree of cross-linking of alginate molecules. We show that soft hydrogels promote the growth of larger MCF-7 tumor spheroids with a lower fraction of proliferating cells and enhance spheroid resistance to doxorubicin. Notably, the stiffness-dependent chemotherapeutic response of the spheroids was temporally mediated: it became apparent at sufficiently long cell culture times, when the matrix stiffness has influenced the spheroid growth. These findings highlight the significance of decoupling matrix stiffness from other characteristics in studies of chemotherapeutic resistance of tumor spheroids and in development of drug screening platforms.