Human embryonic stem cells (hESCs) are capable of unlimited reproduction and retain the ability to differentiate into all cell types in the human body. Therefore, hESCs hold great promise for human cell and tissue replacement therapy. However, our knowledge on how to differentiate them into desired cell types for therapy remains limited. The overall goal of this proposal is to address this lack of knowledge to improve the feasibility of large production of hESCs and routine derivation of therapeutically valuable cells from hESCs. We propose to establish a systems biology approach, which will be continuously optimized with our experimental data, to provide intelligent guidance on how to differentiate hESCs into various cell lineages for therapy. The combination of the proposed bioinformatics and experimental approaches will provide a unique opportunity to address the needs for hESC-based replacement therapy.
Human embryonic stem cells (hESCs) are capable of unlimited self-renewal and retain the ability to differentiate into all cell types in the human body. Therefore, hESCs hold great promise for human cell and tissue replacement therapy. However, due to our limited knowledge of the mechanism underlying the self-renewal and lineage-specific differentiation, it becomes increasingly urgent that more effort must be made to address these knowledge bottlenecks. Our overall goal is to establish a systems biology approach to provide intelligent guidance for our experimental effort to elucidate the mechanisms underlying the lineage-specific differentiation. Achieving this goal will significantly improve our capacity for reliable differentiation of these cells into therapeutically useful cell types. Therefore, the proposed research will benefit California citizens by contributing to the eventual realization of the therapeutic potential of hESCs.
This Fundamental Mechanisms application intends to elucidate how human embryonic stem cells (hESC) make differentiation decisions. Using existing genome-wide information obtained from hESC and various differentiated derivatives, the applicants plan to construct a comprehensive roadmap of gene regulatory networks operating in these cell types. The networks will be used to predict combinations of gene expression regulators, such as transcription factors, that drive specific fates from hESC. The effectiveness of predicted regulator combinations will then be tested through overexpression studies in hESC. The team hopes this network-based, or systems biology, approach will eventually enable scientists to selectively and efficiently drive hESC to therapeutically relevant cells types for clinical use.
Significance and Innovation
- If successful, this work would provide a much needed and useful resource for understanding and manipulating basic stem cell biology.
- Although the project may not provide immediate benefits for clinical application, it has the potential for revolutionizing stem cell research by elucidating rational methods to produce a variety of therapeutically useful cell types.
- The project is likely to yield novel and interesting results, but the proposed work is largely an expansion of recent collaborations that make it less innovative.
Feasibility and Experimental Design
- The comprehensive approach and planned experiments are clearly feasible. Key steps are sufficiently outlined with achievable milestones clearly delineated.
- Collaboration with an epigenetics center strengthens the application.
- The utility of the approach requires generation of reliably predictive network-based computational models; this has to date been challenging for the field. The panel suggested a better measure of accuracy than evidence from the literature be used to confirm the strength of these networks and models.
- Preliminary data and the proposed budget may not support completion of the entire body of work proposed. However, reviewers felt even successful completion of some of the aims would benefit the field and therefore remained enthusiastic about the proposal.
- Appropriate facilities are available to conduct the proposed research.
Principal Investigator (PI) and Research Team
- The PI has experience in stem cell biology. In addition, the team has strong bioinformatics and stem cell reprogramming expertise. The level of committed time heightens the project’s probability for success.
- The applicant team has been productive and has the skills required to successfully complete the project.
Responsiveness to the RFA
- The proposal is highly responsive to the RFA. It seeks to elucidate cellular mechanisms and hESCs and hESC-derived cell types are critical to the proposed research.