As interest grows in using three-dimensional (3D) tumor organoids as models for drug discovery and precision medicine, platforms for the reliable functional testing and analysis of these organoids are needed. Our group previously developed high-speed live cell interferometry (HSLCI), a powerful high-throughput functional drug screening platform which employs automated, repeated quantitative phase imaging (QPI) to longitudinally track drug-induced changes in biomass accumulation dynamics over time. Here, we present a method for the automated bioprinting of 3D tumor organoids coupled with real-time, highly parallel biomass quantification using HSLCI, and demonstrate its utility for drug screening.
Cell size and growth are tightly regulated processes balancing synthesis and metabolism to ensure proper cell function. Deviations from normal growth in response to drug treatment provide insights into the induced cellular dysfunction caused by pharmacotherapy. These changes in biomass growth have shown promise as a marker for drug sensitivity. However, like many biomarkers, the output cannot be treated as binary. Just as cancer cells are heterogenous on the molecular level, individual cells’ biomass response to drug treatment can range from cell death to no effect. It is therefore important to begin to survey for the full range of biomass growth responses to drug treatment to understand the dysfunction induced. Here, we explore the response of different cancer cell lines to treatments that induce biomass growth changes ranging from apoptosis to senescence to simply delayed regrowth. These longer-term studies, ranging up to six days of constant monitoring, aid in the interpretation of more commonly performed shorter-term biomass growth experiments and identify cells of interest for further molecular characterization in these cell lines.
The robustness of Quantitative Phase Imaging (QPI) has enabled QPI to be used in applications to answer both research and clinical questions. QPI requires no labels, is non-destructive, and has nanoscale sensitivity to 3-d morphology. Various applications have included recording cellular force dynamics, identifying parasite-infected red blood cells, detecting cancer prognosis from colon cancer samples, and most recently predicting therapeutic sensitivity from live cell biomass accumulation measurements in patient derived xenograft (PDX) mice. However, challenges remain for clinical adoption, as QPI-based methods must first be proven more effective than current standards of care and patient inconvenience and costs must be minimized. Here we applied basic upgrades to previously described High Speed Live Cell Interferometry (HSLCI) to predict in vivo and in vitro PDX mouse tumor sensitivity to a range of cancer drugs from only Fine Needle Biopsy of the tumor. As demonstrated by our group and many others, the applications of QPI are not limited to the clinical realm. Using HSLCI, we revealed the growth dynamics of senescent and control H460 lung large cell carcinoma cells treated with cancer chemotherapy. The continued improvements in optics and throughput of QPI promise to answer many more clinical and basic science questions.
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