TY - JOUR
T1 - Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment
AU - Sharick, Joe T.
AU - Walsh, Christine M.
AU - Sprackling, Carley M.
AU - Pasch, Cheri A.
AU - Pham, Dan L.
AU - Esbona, Karla
AU - Choudhary, Alka
AU - Garcia-Valera, Rebeca
AU - Burkard, Mark E.
AU - McGregor, Stephanie M.
AU - Matkowskyj, Kristina A.
AU - Parikh, Alexander A.
AU - Meszoely, Ingrid M.
AU - Kelley, Mark C.
AU - Tsai, Susan
AU - Deming, Dustin A.
AU - Skala, Melissa C.
N1 - Publisher Copyright:
© Copyright © 2020 Sharick, Walsh, Sprackling, Pasch, Pham, Esbona, Choudhary, Garcia-Valera, Burkard, McGregor, Matkowskyj, Parikh, Meszoely, Kelley, Tsai, Deming and Skala.
PY - 2020/5/15
Y1 - 2020/5/15
N2 - New tools are needed to match cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity was characterized in breast cancer (BC) and pancreatic cancer (PC) patient-derived organoids. Baseline heterogeneity was analyzed for each patient, demonstrating that single-cell techniques, such as OMI, are required to capture the complete picture of heterogeneity present in a sample. Treatment-induced changes in heterogeneity were also analyzed, further demonstrating that these measurements greatly complement current techniques that only gauge average cellular response. Finally, OMI of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response for the first time. Organoids were treated with the same drugs as the patient's prescribed regimen, and OMI measurements of heterogeneity were compared to patient outcome. OMI distinguished subpopulations of cells with divergent and dynamic responses to treatment in living organoids without the use of labels or dyes. OMI of organoids agreed with long-term therapeutic response in patients. With these capabilities, OMI could serve as a sensitive high-throughput tool to identify optimal therapies for individual patients, and to develop new effective therapies that address cellular heterogeneity in cancer.
AB - New tools are needed to match cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity was characterized in breast cancer (BC) and pancreatic cancer (PC) patient-derived organoids. Baseline heterogeneity was analyzed for each patient, demonstrating that single-cell techniques, such as OMI, are required to capture the complete picture of heterogeneity present in a sample. Treatment-induced changes in heterogeneity were also analyzed, further demonstrating that these measurements greatly complement current techniques that only gauge average cellular response. Finally, OMI of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response for the first time. Organoids were treated with the same drugs as the patient's prescribed regimen, and OMI measurements of heterogeneity were compared to patient outcome. OMI distinguished subpopulations of cells with divergent and dynamic responses to treatment in living organoids without the use of labels or dyes. OMI of organoids agreed with long-term therapeutic response in patients. With these capabilities, OMI could serve as a sensitive high-throughput tool to identify optimal therapies for individual patients, and to develop new effective therapies that address cellular heterogeneity in cancer.
KW - breast cancer
KW - cellular metabolism
KW - heterogeneity
KW - optical metabolic imaging
KW - organoid
KW - pancreatic cancer
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U2 - 10.3389/fonc.2020.00553
DO - 10.3389/fonc.2020.00553
M3 - Article
C2 - 32500020
AN - SCOPUS:85085504111
SN - 2234-943X
VL - 10
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 553
ER -