Author
Listed:
- Tomoyuki Koga
(Ludwig Cancer Research San Diego Branch
University of Minnesota)
- Isaac A. Chaim
(University of California San Diego
University of California San Diego)
- Jorge A. Benitez
(Ludwig Cancer Research San Diego Branch)
- Sebastian Markmiller
(University of California San Diego)
- Alison D. Parisian
(Ludwig Cancer Research San Diego Branch
University of California San Diego)
- Robert F. Hevner
(University of California San Diego)
- Kristen M. Turner
(Ludwig Cancer Research San Diego Branch)
- Florian M. Hessenauer
(Ludwig Cancer Research San Diego Branch)
- Matteo D’Antonio
(University of California San Diego)
- Nam-phuong D. Nguyen
(University of California San Diego)
- Shahram Saberi
(University of California San Diego)
- Jianhui Ma
(Ludwig Cancer Research San Diego Branch)
- Shunichiro Miki
(Ludwig Cancer Research San Diego Branch)
- Antonia D. Boyer
(Ludwig Cancer Research San Diego Branch)
- John Ravits
(University of California San Diego)
- Kelly A. Frazer
(University of California San Diego
University of California San Diego)
- Vineet Bafna
(University of California San Diego)
- Clark C. Chen
(University of Minnesota)
- Paul S. Mischel
(Ludwig Cancer Research San Diego Branch
University of California San Diego)
- Gene W. Yeo
(University of California San Diego
University of California San Diego)
- Frank B. Furnari
(Ludwig Cancer Research San Diego Branch
University of California San Diego)
Abstract
Many cellular models aimed at elucidating cancer biology do not recapitulate pathobiology including tumor heterogeneity, an inherent feature of cancer that underlies treatment resistance. Here we introduce a cancer modeling paradigm using genetically engineered human pluripotent stem cells (hiPSCs) that captures authentic cancer pathobiology. Orthotopic engraftment of the neural progenitor cells derived from hiPSCs that have been genome-edited to contain tumor-associated genetic driver mutations revealed by The Cancer Genome Atlas project for glioblastoma (GBM) results in formation of high-grade gliomas. Similar to patient-derived GBM, these models harbor inter-tumor heterogeneity resembling different GBM molecular subtypes, intra-tumor heterogeneity, and extrachromosomal DNA amplification. Re-engraftment of these primary tumor neurospheres generates secondary tumors with features characteristic of patient samples and present mutation-dependent patterns of tumor evolution. These cancer avatar models provide a platform for comprehensive longitudinal assessment of human tumor development as governed by molecular subtype mutations and lineage-restricted differentiation.
Suggested Citation
Tomoyuki Koga & Isaac A. Chaim & Jorge A. Benitez & Sebastian Markmiller & Alison D. Parisian & Robert F. Hevner & Kristen M. Turner & Florian M. Hessenauer & Matteo D’Antonio & Nam-phuong D. Nguyen &, 2020.
"Longitudinal assessment of tumor development using cancer avatars derived from genetically engineered pluripotent stem cells,"
Nature Communications, Nature, vol. 11(1), pages 1-14, December.
Handle:
RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14312-1
DOI: 10.1038/s41467-020-14312-1
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