Validating microfluidics-based personalized cancer therapy in mouse models
Bioinformatics and Theoretical Biology
Hematology, Oncology
Final Report Abstract
Cancers of the hepato-pancreatico-biliary (HPB) tract are characterized by a very poor prognosis. which is largely explained by robust therapy resistance of HPB cancers. Even though the impressive advances of recent years have resulted in a much better understanding of the molecular pathogenesis of cancer in general and HPB tumors in particular, these developments have not yet translated in an improved prognosis of patients with this malignancy. In principle, strategies aiming at therapy individualization are able to significantly improve clinical care. However, until today only few results from genetic analyses have successfully been translated into the clinics, e.g. for the treatment of leukemias, breast and colon cancer. Phenotypical analyses allowing for sensitivity testing of tumor cells of individual patients against a wide battery of antiproliferative substances (and combinations thereof) could be an alternative to define personalized therapies, but they require cell numbers that are normally not available from biopsies. In preliminary studies our research groups could show that a newly developed microfluidics platform is able to predict therapy sensitivity of established human cell lines and small biopsies from patients with pancreatic cancer. We used it to identify particularly potent drug combinations whose synergistic effects had not been described before. For example, we could show that a combined application of PHT-427 and Selumetinib is highly efficient by blocking two independent pathways downstream of KRAS. Our platform allows for rapid and automated testing of systematic combinations of antiproliferative drugs on patient tumor material, which is usually available only in very small amounts. Due to the low number of cells per sample (~ 100) we are able to analyse one to two orders of magnitude more treatment conditions than with existing methods. Our platform has additional unique advantages compared to existing technologies, such as the avoidance of cell cultivating steps, which can potentially confound drug effects. Furthermore, our method is rapid (results are available within 48h) and cost effective (~150 euros consumables costs per patient sample). We now aim for a functional in vivo validation of this approach, which has not been possible previously using human samples, exploiting different HPB tumors mouse models. In comprehensive experiments with expanded readouts we will a) predict the optimal therapy ex vivo, b) perform signaling pathway modelling to understand resistance mechanisms and identify potentially new drug sensitizers and c) validate the predicted best treatment option in vivo.
Publications
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A microfluidic Braille valve platform for on-demand production, combinatorial screening and sorting of chemically distinct droplets. Nature Protocols, 17(12), 2920-2965.
Utharala, Ramesh; Grab, Anna; Vafaizadeh, Vida; Peschke, Nicolas; Ballinger, Martine; Turei, Denes; Tuechler, Nadine; Ma, Wenwei; Ivanova, Olga; Ortiz, Alejandro Gil; Saez-Rodriguez, Julio & Merten, Christoph A.
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Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets. Nature Communications, 13(1).
Mathur, L.; Szalai, B.; Du, N. H.; Utharala, R.; Ballinger, M.; Landry, J. J. M.; Ryckelynck, M.; Benes, V.; Saez-Rodriguez, J. & Merten, C. A.
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Integrating knowledge and omics to decipher mechanisms via large‐scale models of signaling networks. Molecular Systems Biology, 18(7).
Garrido‐Rodriguez, Martin; Zirngibl, Katharina; Ivanova, Olga; Lobentanzer, Sebastian & Saez‐Rodriguez, Julio
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Design and construction of a microfluidics workstation for high-throughput multi-wavelength fluorescence and transmittance activated droplet analysis and sorting. Nature Protocols, 18(4), 1090-1136.
Panwar, Jatin; Autour, Alexis & Merten, Christoph A.
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Fluorescence crosstalk reduction by modulated excitation-synchronous acquisition for multispectral analysis in high-throughput droplet microfluidics. Lab on a Chip, 23(11), 2514-2520.
Panwar, Jatin & Merten, Christoph A.
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iSort enables automated complex microfluidic droplet sorting in an effort to democratize technology. Cell Reports Methods, 3(5), 100478.
Panwar, Jatin; Utharala, Ramesh; Fennelly, Laura; Frenzel, Daniel & Merten, Christoph A.
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NetworkCommons: bridging data, knowledge, and methods to build and evaluate context-specific biological networks. Bioinformatics, 41(2).
Paton, Victor; Türei, Denes; Ivanova, Olga; Müller-Dott, Sophia; Rodriguez-Mier, Pablo; Venafra, Veronica; Perfetto, Livia; Garrido-Rodriguez, Martin & Saez-Rodriguez, Julio
