Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment

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Abstract

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.

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Most cited references 53

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Measurement of residual breast cancer burden to predict survival after neoadjuvant chemotherapy.

W Symmans, Florentia Peintinger, Christos Hatzis … (2007)

To measure residual disease after neoadjuvant chemotherapy in order to improve the prognostic information that can be obtained from evaluating pathologic response. Pathologic slides and reports were reviewed from 382 patients in two different treatment cohorts: sequential paclitaxel (T) then fluorouracil, doxorubicin, and cyclophosphamide (FAC) in 241 patients; and a single regimen of FAC in 141 patients. Residual cancer burden (RCB) was calculated as a continuous index combining pathologic measurements of primary tumor (size and cellularity) and nodal metastases (number and size) for prediction of distant relapse-free survival (DRFS) in multivariate Cox regression analyses. RCB was independently prognostic in a multivariate model that included age, pretreatment clinical stage, hormone receptor status, hormone therapy, and pathologic response (pathologic complete response [pCR] v residual disease [RD]; hazard ratio = 2.50; 95% CI 1.70 to 3.69; P < .001). Minimal RD (RCB-I) in 17% of patients carried the same prognosis as pCR (RCB-0). Extensive RD (RCB-III) in 13% of patients was associated with poor prognosis, regardless of hormone receptor status, adjuvant hormone therapy, or pathologic American Joint Committee on Cancer stage of residual disease. The generalizability of RCB for prognosis of distant relapse was confirmed in the FAC-treated validation cohort. RCB determined from routine pathologic materials represented the distribution of RD, was a significant predictor of DRFS, and can be used to define categories of near-complete response and chemotherapy resistance.

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Organoid profiling identifies common responders to chemotherapy in pancreatic cancer

Hervé Tiriac, Pascal Belleau, Dannielle D. Engle … (2018)

Pancreatic cancer is the most lethal common solid malignancy. Systemic therapies are often ineffective and predictive biomarkers to guide treatment are urgently needed. We generated a pancreatic cancer patient-derived organoid (PDO) library that recapitulates the mutational spectrum and transcriptional subtypes of primary pancreatic cancer. New driver oncogenes were nominated and transcriptomic analyses revealed unique clusters. PDOs exhibited heterogeneous responses to standard-of-care chemotherapeutics and investigational agents. In a case study manner, we find that PDO therapeutic profiles paralleled patient outcomes and that PDOs enable longitudinal assessment of chemo-sensitivity and evaluation of synchronous metastases. We derived organoid-based gene expression signatures of chemo-sensitivity that predicted improved responses for many patients to chemotherapy in both the adjuvant and advanced disease settings. Finally, we nominated alternative treatment strategies for chemo-refractory PDOs using targeted agent therapeutic profiling. We propose that combined molecular and therapeutic profiling of PDOs may predict clinical response and enable prospective therapeutic selection.

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3D tumor spheroid models for in vitro therapeutic screening: a systematic approach to enhance the biological relevance of data obtained

Michele Zanoni, Filippo Piccinini, Chiara Arienti … (2016)

The potential of a spheroid tumor model composed of cells in different proliferative and metabolic states for the development of new anticancer strategies has been amply demonstrated. However, there is little or no information in the literature on the problems of reproducibility of data originating from experiments using 3D models. Our analyses, carried out using a novel open source software capable of performing an automatic image analysis of 3D tumor colonies, showed that a number of morphology parameters affect the response of large spheroids to treatment. In particular, we found that both spheroid volume and shape may be a source of variability. We also compared some commercially available viability assays specifically designed for 3D models. In conclusion, our data indicate the need for a pre-selection of tumor spheroids of homogeneous volume and shape to reduce data variability to a minimum before use in a cytotoxicity test. In addition, we identified and validated a cytotoxicity test capable of providing meaningful data on the damage induced in large tumor spheroids of up to diameter in 650 μm by different kinds of treatments.

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Author and article information

Contributors

Joe T. Sharick: URI : http://loop.frontiersin.org/people/889565/overview

Cheri A. Pasch: URI : http://loop.frontiersin.org/people/893505/overview

Dan L. Pham: URI : http://loop.frontiersin.org/people/893640/overview

Mark C. Kelley: URI : http://loop.frontiersin.org/people/906521/overview

Susan Tsai: URI : http://loop.frontiersin.org/people/847580/overview

Dustin A. Deming: URI : http://loop.frontiersin.org/people/660344/overview

Melissa C. Skala: URI : http://loop.frontiersin.org/people/776302/overview

Journal

Journal ID (nlm-ta): Front Oncol

Journal ID (iso-abbrev): Front Oncol

Journal ID (publisher-id): Front. Oncol.

Title: Frontiers in Oncology

Publisher: Frontiers Media S.A.

ISSN (Electronic): 2234-943X

Publication date (Electronic): 15 May 2020

Publication date Collection: 2020

Volume: 10

Electronic Location Identifier: 553

Affiliations

[1] ¹Department of Biomedical Engineering, Vanderbilt University , Nashville, TN, United States

[2] ²Morgridge Institute for Research , Madison, WI, United States

[3] ³University of Wisconsin Carbone Cancer Center , Madison, WI, United States

[4] ⁴Department of Biomedical Engineering, University of Wisconsin , Madison, WI, United States

[5] ⁵Department of Pathology and Laboratory Medicine, University of Wisconsin , Madison, WI, United States

[6] ⁶Department of Medicine, University of Wisconsin , Madison, WI, United States

[7] ⁷Tecnológico de Monterrey, Escuela de Ingeniería y Ciencias , Zapopan, Mexico

[8] ⁸William S. Middleton Memorial Veterans Hospital , Madison, WI, United States

[9] ⁹Division of Surgical Oncology, East Carolina University Brody School of Medicine , Greenville, NC, United States

[10] ¹⁰Department of Surgery, Vanderbilt University , Nashville, TN, United States

[11] ¹¹Department of Surgery, Medical College of Wisconsin , Milwaukee, WI, United States

[12] ¹²Division of Hematology and Oncology, Department of Medicine, University of Wisconsin , Madison, WI, United States

[13] ¹³McArdle Laboratory for Cancer Research, Department of Oncology, University of Wisconsin , Madison, WI, United States

Author notes

Edited by: Federica Sotgia, University of Salford, United Kingdom

Reviewed by: Amilcare Barca, University of Salento, Italy; Cinzia Antognelli, University of Perugia, Italy

*Correspondence: Melissa C. Skala mcskala@ 123456wisc.edu

This article was submitted to Cancer Metabolism, a section of the journal Frontiers in Oncology

Article

DOI: 10.3389/fonc.2020.00553

PMC ID: 7242740

PubMed ID: 32500020

SO-VID: 4ba39942-034d-4e79-a240-5375d7be1b36

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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 24 January 2020

Date accepted : 27 March 2020

Page count

Figures: 7, Tables: 0, Equations: 4, References: 74, Pages: 17, Words: 12074

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Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment

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Karger: Oncology

Most cited references 53

Measurement of residual breast cancer burden to predict survival after neoadjuvant chemotherapy.

Organoid profiling identifies common responders to chemotherapy in pancreatic cancer

3D tumor spheroid models for in vitro therapeutic screening: a systematic approach to enhance the biological relevance of data obtained

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Cited by 45

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