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Review
. 2022 Jun 2;13(1):3086.
doi: 10.1038/s41467-022-30384-7.

A role for microfluidic systems in precision medicine

Affiliations
Review

A role for microfluidic systems in precision medicine

Jose M Ayuso et al. Nat Commun. .

Abstract

Precision oncology continues to challenge the "one-size-fits-all" dogma. Under the precision oncology banner, cancer patients are screened for molecular tumor alterations that predict treatment response, ideally leading to optimal treatments. Functional assays that directly evaluate treatment efficacy on the patient's cells offer an alternative and complementary tool to improve the accuracy of precision oncology. Unfortunately, traditional Petri dish-based assays overlook much tumor complexity, limiting their potential as predictive functional biomarkers. Here, we review past applications of microfluidic systems for precision medicine and discuss the present and potential future role of functional microfluidic assays as treatment predictors.

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Conflict of interest statement

D.J. Beebe holds equity in Bellbrook Labs LLC, Tasso Inc., Stacks to the Future LLC, Lynx Biosciences LLC, Onexio Biosystems LLC, Turba LLC, Flambeau Diagnostics LLC, and Salus Discovery LLC. D.J.J. Lang holds equity in Salus Discovery LLC. J.M. Lang holds equity in Salus Discovery LLC. Lang financial interests: Pfizer (Advisory Board, Personal), Janssen (Advisory Board, Personal), Gilead (Advisory Board, Personal), 4D Pharma (Advisory Board, Personal), Arvinas (Advisory Board, Personal), Astellas (Advisory Board, Personal), Myovant (Advisory Board, Personal), AstraZeneca (Advisory Board, Personal), SeaGen (Advisory Board, Personal). J.M. Ayuso and M. Virumbrales-Muñoz declare no competing interests.

Figures

Fig. 1
Fig. 1. Representative microfluidic models for functional analysis.
The figure shows schematic representations of the model (left column), a microscopy image of a functional output of the model (middle column), main highlights of the model, and functional assays demonstrated (right column). Chimeric-antigen receptor (CAR) T cells,,,,.
Fig. 2
Fig. 2. Timeline of intersections between biology (green) and engineering-driven (orange) research.
The figure illustrates the rising tendency since the 2000s of increasingly translational publications (blue) that have brought us closer to patient-on-a-chip models. A number of recent publications provide a more detailed review of specific technical advances,,,–.
Fig. 3
Fig. 3. Microfluidic models for molecular diagnostics.
Theoretical device design for back-to-back analysis of CTCs and circulating proteins and DNA from whole blood. Whole blood is perfused through a series of microchambers and microchannels that leverage several microscale-based separation techniques to isolate multiple components such as immune cells, CTCs, ctDNA, proteins, and exosomes. Next, cells and analytes are either retrieved or analyzed in situ.
Fig. 4
Fig. 4. Microfluidic devices for disease modeling and functional diagnostics.
A Microfluidic devices offer great potential to evaluate treatment response in a patient-specific manner. Surgical samples or biopsy cores are used for histopathological analysis and molecular profiling. Additionally, the tissue is also digested to isolate patient-derived cells and then cultured in vitro. Tumor, stromal, endothelial, and/or lymphatic cells are cultured in the microfluidic device. Next, functional response is monitored, providing valuable information about tumor evolution and patient prognostic. Adapted from ref. . B Microfluidic devices can leverage other advances in in vitro culture such as 3D bioprinting to generate highly complex structures with biologically derived extracellular matrices. Adapted from ref. . C The high-throughput potential of microfluidic devices makes them amenable for large drug screening to evaluate the optimal drug candidate for each individual patient. Adapted from ref. .
Fig. 5
Fig. 5. Potential workflow for microfluidic devices in molecular and functional diagnostics.
Patients are first subjected to standard molecular panels to identify known predictors. If molecular data is insufficient to make a clinical decision on patient treatment, tissues of interest would be sampled to build an organotypic model for functional drug testing. This model would be used to test several potential drugs (and drug combinations), and then compared to the patient outcome for validation. Several steps of model enrichment may be needed. Ideally, the organotypic model would lead to the identification of new biomarkers, or to a simpler model that can be integrated into the healthcare pipeline.

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