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Characterizing heterogeneous single-cell dose responses computationally and experimentally using threshold inhibition
Patrick C Kinnunen1, Brock A Humphries2, Gary D Luker2,3,4
1Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Abstract:
Single cancer cells within a tumor exhibit variable levels of resistance to drugs, ultimately leading to treatment failures. While tumor heterogeneity is recognized as a major obstacle to cancer therapy, standard dose-response measurements for the potency of targeted kinase inhibitors aggregate populations of cells, obscuring intercellular variations in responses. In this work, we develop an analytical and experimental framework to quantify and model dose responses of individual cancer cells to drugs. We first explore the connection between population and single-cell dose responses using a computational model, revealing that multiple heterogeneous populations can yield nearly identical population dose responses. We demonstrate that a single-cell analysis method, which we term a threshold inhibition surface, can differentiate among these populations. To demonstrate the applicability of this method, we develop a dose-titration assay to measure dose responses in single cells. We apply this assay to breast cancer cells responding to phosphatidylinositol-3-kinase inhibition (PI3Ki), using clinically relevant PI3Kis on breast cancer cell lines expressing fluorescent biosensors for kinase activity. We demonstrate that MCF-7 breast cancer cells exhibit heterogeneous dose responses with some cells requiring over ten-fold higher concentrations than the population average to achieve inhibition. Our work reimagines dose-response relationships for cancer drugs in an emerging paradigm of single-cell tumor heterogeneity.
Insights
Single cancer cells show varied drug resistance, impacting treatment success. This study introduces a new method to measure individual cell responses, revealing critical differences missed by population-level analysis for targeted cancer therapies.
Area of Science:
- Oncology
- Pharmacology
- Biophysics
Background:
- Tumor heterogeneity causes variable drug resistance in individual cancer cells, leading to treatment failure.
- Standard drug testing aggregates cell populations, masking crucial single-cell response variations.
- Targeted kinase inhibitors are vital, but their efficacy is limited by heterogeneous cellular responses.
Purpose of the Study:
- To develop a framework for quantifying and modeling single-cancer cell drug dose responses.
- To differentiate between heterogeneous cell populations using a novel single-cell analysis method.
- To apply this method to understand breast cancer cell responses to phosphatidylinositol-3-kinase inhibition.
Main Methods:
- Computational modeling to connect population and single-cell dose responses.
- Development of a "threshold inhibition surface" method for single-cell analysis.
- A dose-titration assay using fluorescent biosensors in breast cancer cell lines.
Main Results:
- Computational models showed that diverse cell populations can exhibit similar population-level dose responses.
- The threshold inhibition surface method successfully differentiated between these heterogeneous populations.
- MCF-7 breast cancer cells displayed significant dose response heterogeneity to PI3K inhibitors, with some cells needing 10x higher drug concentrations.
Conclusions:
- Single-cell analysis is essential for understanding drug response heterogeneity in cancer.
- The developed framework and assay can reveal critical variations in drug potency at the individual cell level.
- This work advances the understanding of targeted cancer therapies in the context of tumor heterogeneity.
