Author
Listed:
- Flaminia Talos
(Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center)
- Antonina Mitrofanova
(Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Present address: Department of Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, New Jersey 07107, USA)
- Sarah K. Bergren
(Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center)
- Andrea Califano
(Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center)
- Michael M. Shen
(Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center
Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center)
Abstract
To date, reprogramming strategies for generating cell types of interest have been facilitated by detailed understanding of relevant developmental regulatory factors. However, identification of such regulatory drivers often represents a major challenge, as specific gene combinations may be required for reprogramming. Here we show that a computational systems approach can identify cell type specification genes (master regulators) that act synergistically, and demonstrate its application for reprogramming of fibroblasts to prostate tissue. We use three such master regulators (FOXA1, NKX3.1 and androgen receptor, AR) in a primed conversion strategy starting from mouse fibroblasts, resulting in prostate tissue grafts with appropriate histological and molecular properties that respond to androgen-deprivation. Moreover, generation of reprogrammed prostate does not require traversal of a pluripotent state. Thus, we describe a general strategy by which cell types and tissues can be generated even with limited knowledge of the developmental pathways required for their specification in vivo.
Suggested Citation
Flaminia Talos & Antonina Mitrofanova & Sarah K. Bergren & Andrea Califano & Michael M. Shen, 2017.
"A computational systems approach identifies synergistic specification genes that facilitate lineage conversion to prostate tissue,"
Nature Communications, Nature, vol. 8(1), pages 1-12, April.
Handle:
RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms14662
DOI: 10.1038/ncomms14662
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