3D microgels to quantify tumor cell properties and therapy response dynamics. (April 2022)
- Record Type:
- Journal Article
- Title:
- 3D microgels to quantify tumor cell properties and therapy response dynamics. (April 2022)
- Main Title:
- 3D microgels to quantify tumor cell properties and therapy response dynamics
- Authors:
- Wu, Nila C.
Cadavid, Jose L.
Tan, Xinzhu
Latour, Simon
Scaini, Stefano
Makhijani, Priya
McGaha, Tracy L.
Ailles, Laurie
McGuigan, Alison P. - Abstract:
- Abstract: Tumors contain heterogeneous and dynamic populations of cells that do not all display the fast-proliferating properties that traditional chemotherapies target. There is a need therefore, to develop novel treatment strategies that target diverse tumor cell properties. Identifying therapy combinations is challenging however. Current approaches have relied on cell lines cultured in monolayers with treatment response being assessed using endpoint metabolic assays, which although enable large-scale throughput, do not capture tumor heterogeneity. Here, a 3D in vitro tumor model using micro-molded hydrogels (microgels), the Gels for Live Analysis of Compartmentalized Environments (GLAnCE) platform, is adapted into a 96-well plate format (96-GLAnCE) that integrates patient-derived organoids (PDOs) and is combined with longitudinal automated imaging to address these limitations. Using 96-GLAnCE, two measures of tumor aggressiveness are quantified, tumor cell growth and in situ regrowth after drug treatment, in both cell lines and PDOs. The use of longitudinal image-based readouts enables the identification of tumor cell phenotypes with cell population and subpopulation resolution that cannot be detected by standard bulk-soluble assays. 96-GLAnCE is a versatile and robust platform that combines 3D-ECM based models, PDOs, and real-time assay readouts, to provide an additional tool for pre-clinical anti-cancer drug discovery for the identification of novel targets withAbstract: Tumors contain heterogeneous and dynamic populations of cells that do not all display the fast-proliferating properties that traditional chemotherapies target. There is a need therefore, to develop novel treatment strategies that target diverse tumor cell properties. Identifying therapy combinations is challenging however. Current approaches have relied on cell lines cultured in monolayers with treatment response being assessed using endpoint metabolic assays, which although enable large-scale throughput, do not capture tumor heterogeneity. Here, a 3D in vitro tumor model using micro-molded hydrogels (microgels), the Gels for Live Analysis of Compartmentalized Environments (GLAnCE) platform, is adapted into a 96-well plate format (96-GLAnCE) that integrates patient-derived organoids (PDOs) and is combined with longitudinal automated imaging to address these limitations. Using 96-GLAnCE, two measures of tumor aggressiveness are quantified, tumor cell growth and in situ regrowth after drug treatment, in both cell lines and PDOs. The use of longitudinal image-based readouts enables the identification of tumor cell phenotypes with cell population and subpopulation resolution that cannot be detected by standard bulk-soluble assays. 96-GLAnCE is a versatile and robust platform that combines 3D-ECM based models, PDOs, and real-time assay readouts, to provide an additional tool for pre-clinical anti-cancer drug discovery for the identification of novel targets with translatable clinical significance. Highlights: 96-GLAnCE is a 3D in vitro tumor model in a standard 96-well plate format. Flat and thin microgels facilitate widefield image-based acquisition and analysis. Enables continuous monitoring of multi-cell and patient-derived organoid cultures. Quantifies dynamic metrics including tumor growth and regrowth after treatment. Longitudinal readouts distinguish and identify heterogeneous cellular responses. … (more)
- Is Part Of:
- Biomaterials. Volume 283(2022)
- Journal:
- Biomaterials
- Issue:
- Volume 283(2022)
- Issue Display:
- Volume 283, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 283
- Issue:
- 2022
- Issue Sort Value:
- 2022-0283-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-04
- Subjects:
- 3D tumor model -- Image-based analysis -- Drug response -- Growth -- Regrowth -- Patient-derived organoids
Biomedical materials -- Periodicals
Biocompatible Materials -- Periodicals
Biomatériaux -- Périodiques
610.28 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01429612 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/01429612 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/01429612 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.biomaterials.2022.121417 ↗
- Languages:
- English
- ISSNs:
- 0142-9612
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2087.715000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21280.xml