This proposal addresses the Group D Provocative Question (PQD5): Since current methods to predict the efficacy or toxicity of new drug candidates in humans are often inaccurate, can we develop new methods to test potential therapeutic agents that yield better predictions of response? We will address critical shortcomings in predicting therapeutic responses to anticipate tumor recurrence and improve patient outcome, which is usually based on tumor heterogeneity. We will accomplish this goal by developing and applying a novel single-cell response measuring technology, termed a High-Throughput Screening Live Cell Interferometer (HTS-LCI), to quantify single-cell biomass changes temporally, before and during drug exposure. With 10,000s of time-dependent biomass profiles, we will rapidly characterize a tumor's heterogeneous kinetic response to therapy in order to provide a quantitative statistical classifier. Our proposal is transformative with broad implications for all types of cancer, but here we focus on metastatic melanoma (mainly stage III-IV) because 1) it is a common cancer with increasing incidence, 2) is often rapidly fatal, and 3) much is known about targeted therapy and resistance. Specifically, MAPK pathway-activating BRAF serine/threonine kinase mutations are present in ~50% of melanomas. Importantly, well-characterized BRAF-inhibitor (BRAFi) sensitive and resistant cell lines and fresh patient melanoma samples are readily available for proof-of-principle preclinical studies. Approaches in personalized medicine rely on static biomarker, genomic, and epigenetic parameters to refine therapy choice and predict prognosis, but they all fail to incorporate therapeutic response, which is a critical omission. Validated, individualized tumor cell response profiling could have enormous impact on therapeutic efficacy, rapid cancer diagnosis, prognosis, and prediction of tumor recurrence. To reach this goal we propose a new approach with three innovative components that include 1) engineering the HTS-LCI to quantify tumor cell biomass changes in response therapeutic agents, in real time; 2) using paired BRAFi sensitive and resistant patient-derived metastatic melanoma cell lines that have been extensively characterized for genomic, epigenomic, and expression profiling by our collaborators; and 3) utilizing our immediate access to de-identified patient samples through collaboration with Jonsson Comprehensive Cancer Center clinicians and their ongoing early phase clinical trials.
The Specific Aims of our proposal are:
Aim 1 : To generate a BRAFi sensitive and resistant paired melanoma cell line statistical classifier.
Aim 2 : To engineer the HTS-LCI for multi-drug growth rate profiling in a 36-well plate format.
Aim 3 : To evaluate the HTS-LCI for rapid response detection of BRAFi sensitive and resistant lines.
Aim 4 : To apply the HTS-LCI platform for biomass profiling of fresh melanoma patient samples.
The clinical course and outcome for melanoma patients remains variable despite therapies that are usually guided by a combination of clinical assessments, including tumor subtype, clinical grade and stage, and activating mutations of the MAPK cell growth and signaling pathway, including BRAF (~50% of cases) and N-RAS (~10% of cases) protein kinases. Real-time biomass profiling of live tumor cell growth and regression responses to therapeutic agents with an incubator-based High-Throughput Screening Live Cell Interferometry (HTS-LCI) is a new and reproducible biophysical quantifier that promises to rapidly (within hours) identify optimal therapeutic agents and sub-classify tumors based on therapeutic response in order to improve predictions of patient prognosis and tumor recurrence.
| Waters, Lynnea R; Ahsan, Fasih M; Wolf, Dane M et al. (2018) Initial B Cell Activation Induces Metabolic Reprogramming and Mitochondrial Remodeling. iScience 5:99-109 |
| Yu, Jingyi; Seldin, Marcus M; Fu, Kai et al. (2018) Topological Arrangement of Cardiac Fibroblasts Regulates Cellular Plasticity. Circ Res 123:73-85 |
| Patananan, Alexander N; Sercel, Alexander J; Teitell, Michael A (2018) More than a powerplant: the influence of mitochondrial transfer on the epigenome. Curr Opin Physiol 3:16-24 |
| Huang, Dian; Leslie, Kevin A; Guest, Daniel et al. (2018) High-Speed Live-Cell Interferometry: A New Method for Quantifying Tumor Drug Resistance and Heterogeneity. Anal Chem 90:3299-3306 |
| Mikheikin, Andrey; Olsen, Anita; Leslie, Kevin et al. (2017) DNA nanomapping using CRISPR-Cas9 as a programmable nanoparticle. Nat Commun 8:1665 |
| Wu, Ting-Hsiang; Sagullo, Enrico; Case, Dana et al. (2016) Mitochondrial Transfer by Photothermal Nanoblade Restores Metabolite Profile in Mammalian Cells. Cell Metab 23:921-9 |
| Setoguchi, Kiyoko; TeSlaa, Tara; Koehler, Carla M et al. (2016) P53 Regulates Rapid Apoptosis in Human Pluripotent Stem Cells. J Mol Biol 428:1465-75 |
| TeSlaa, Tara; Setoguchi, Kiyoko; Teitell, Michael A (2016) Mitochondria in human pluripotent stem cell apoptosis. Semin Cell Dev Biol 52:76-83 |
| TeSlaa, Tara; Chaikovsky, Andrea C; Lipchina, Inna et al. (2016) ?-Ketoglutarate Accelerates the Initial Differentiation of Primed Human Pluripotent Stem Cells. Cell Metab 24:485-493 |
| Patananan, Alexander N; Wu, Ting-Hsiang; Chiou, Pei-Yu et al. (2016) Modifying the Mitochondrial Genome. Cell Metab 23:785-96 |
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