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 hours after tumor removal from a mouse. Before HSLCI can be tested in the clinic, it must be adapted for minimally invasive sample acquisition techniques, throughput must be increased to enhance drug screening capacity, and, like any screening method, protocols must be adjusted to reflect drug-specific effects. To overcome these barriers, the system’s hardware was redesigned to increase throughput six-fold and enable the simultaneous screening of multiple therapeutics, and experiments were expanded to include several new classes of drugs. Additionally, the updated system was then incorporated into fine needle biopsy-compatible protocols that were developed for HSLCI and yielded data concordant with recently-published in vivo screens.
Highlights
One third of triple-negative breast cancer (TNBC) patients experience drug-resistant metastatic disease that is often fatal [1]
We show that High-Speed Live-Cell Interferometry (HSLCI) delivers qualitatively and quantitatively similar measurements using two classes of investigational TNBC therapeutics, proteasome inhibitors and CDK 4/6 inhibitors
This has been attributed to the ability of the resistant cells’ proteosomes to utilize alternative enzymatic sites not blocked by the inhibitor molecule [16]. These findings provide a rationale for screening with a method like HSLCI that can resolve intra-tumor heterogeneity to better identify risks of failure due to minority resistant populations
Summary
One third of triple-negative breast cancer (TNBC) patients experience drug-resistant metastatic disease that is often fatal [1]. Current guidelines attempt to personalize cancer therapy based on a patient’s general state of health, clinical tumor staging, hormone receptor status, and mutation profile. These guidelines are often inadequate at predicting therapeutic resistance before bulk tumor growth restarts and potentially metastasizes [2,3,4]. Liquid biopsies, which detect circulating biomarkers, exosomes, microRNAs, circulating tumor DNA, and tumor cells in blood, accurately reflect tumor heterogeneity and are easy to acquire This approach still depends on sequencing and requires an understanding of the clinical significance of each detected mutation. In more than one third of cases, potential resistance-related mutations are not found, or the QPI Enables FNB Drug Screening significance of detected mutations is unknown, resulting in the incorrect prediction of susceptibility to therapeutics
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