QPI Allows in vitro Drug Screening of Triple Negative Breast Cancer PDX Tumors and Fine Needle Biopsies

Abstract

The development of resistance to initially successful cancer therapies is a major cause of the morbidity and mortality associated with cancer. Identifying evolving resistance at an early stage could inform clinical decision making to adapt therapies before resistant cancer cell phenotypes have become clonally dominant or metastasized. This goal of early detection has prompted heavy investments in liquid biopsy, organoid, and high-throughput screening methodologies. Recently, High-Speed Live-Cell Interferometry (HSLCI), a quantitative phase imaging (QPI) methodology, was shown to predict triple-negative breast cancer (TNBC) patient-derived xenograft (PDX) sensitivity to carboplatin only 40 h after tumor removal from a mouse. In this paper we discuss barriers to applying HSLCI to therapy selection in human TNBC patients, and present preliminary results addressing some of those barriers. Our results include engineering improvements to increase sample throughput and demonstrating that HSLCI can measure drug response of agents with a variety of mechanisms of action. Finally, we show proof of concept data for direct testing of samples obtained from minimally invasive, fine needle biopsies.

Addressing cancer invasion and cell motility with quantitative light microscopy

“…Vasilenko et al used laser-based QPI to address the morphology of circulating tumor cells in relationship to their metastatic potential 24 . We were more interested in drug screening and Murray et al 25 and Mir et al 26 successfully used QPI exactly for that purpose but only evaluated cell growth. As our biological results indicate, our main interest was in the motility of cancer cells, and Frame et al 27 evaluated translocation of cancer cells using ptychography phase measurements, and Hellesvik et al 28 used the coherent laser-based Holomonitor system for 3D tracking of osteosarcoma cells.…”

Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer

“…QPI mass versus time data have several key features that underlie the ability of QPI to distinguish multiple dynamic characteristics of cell response to drugs. First, the rate of mass accumulation (dm/dt) can be used to characterize cell growth 17,18,26,27,32,33 . In healthy cells the mass accumulation rate is constant as cells grow during each cell cycle (DMSO control, green line in Fig.…”

“…A dose-dependent change in growth, as indicated by a change in the rate of mass accumulation or loss, is the first key parameter that can be extracted from QPI dose-response data 18,27 . For example, the SGR distribution for MCF-7 cells decreases with increasing doxorubicin concentration to a minimum of -0.003 +/-0.004 h -1 (mean +/-standard deviation, SD) at 20 µM, the highest dose tested, indicating cellular response to the drug (Fig.…”

“…QPI is a real-time, high throughput tool for measuring the growth response of individual cells to therapy. However, previous applications of QPI have narrowly focused on measuring the overall sensitivity 26 or toxicity 27 of potential therapies with only limited studies of the heterogeneity of response 28 .…”

Drug screening at single-organoid resolution via bioprinting and interferometry

“…We monitor bioprinted organoids with HSL-CI that uses quantitative phase imaging (QPI) in order to rapidly monitor changes in dry biomass and biomass distribution of organoids over time [23][24][25][26][27]27,28 . QPI measurements of biomass changes allowed to distinguish drug-resistant from -sensitive cells in 2D cell culture models within hours of treatment [23][24][25][27][28][29][30] . Moreover, HSLCI-measured response profiles were found to match drug sensitivity observed in patient-derived xenograft (PDX) mouse models of breast cancer 24 .…”