Tian, Anhao; Kang, Bo; Li, Baizhou; Qiu, Biying; Jiang, Wenhong; Shao, Fangjie; Gao, Qingqing; Liu, Rui; Cai, Chengwei; Jing, Rui; Wang, Wei; Chen, Pengxiang
Glioblastoma is the most malignant cancer in the brain and currently incurable. It is urgent to identify effective targets for this lethal disease. Inhibition of such targets should suppress the growth of cancer cells and, ideally also precancerous cells for early prevention, but minimally affect their normal counterparts. Using genetic mouse models with neural stem cells (NSCs) or oligodendrocyte precursor cells (OPCs) as the cells‐of‐origin/mutation, it is shown that the susceptibility of cells within the development hierarchy of glioma to the knockout of insulin‐like growth factor I receptor (IGF1R) is determined not only by their oncogenic states, but also by their cell identities/states. Knockout of IGF1R selectively disrupts the growth of mutant and transformed, but not normal OPCs, or NSCs. The desirable outcome of IGF1R knockout on cell growth requires the mutant cells to commit to the OPC identity regardless of its development hierarchical status. At the molecular level, oncogenic mutations reprogram the cellular network of OPCs and force them to depend more on IGF1R for their growth. A new‐generation brain‐penetrable, orally available IGF1R inhibitor harnessing tumor OPCs in the brain is also developed. The findings reveal the cellular window of IGF1R targeting and establish IGF1R as an effective target for the prevention and treatment of glioblastoma.
The authors thank Drs. J. Eisen, QR. Lu, S. Duan, Z‐H. Li, W. Mo, and Q. Wu for their critical comments on the manuscript. They also thank Dr. H. Zong for providing the CKO_NG2‐CreER model. This work is supported by the National Key Research and Development Program of China, Stem Cell and Translational Research (2016YFA0101201 to C.L., 2016YFA0100303 to Y.J.W.), the National Natural Science Foundation of China (81673035 and 81972915 to C.L., 81472722 to Y.J.W.), the Science Foundation for Distinguished Young Scientists of Zhejiang Province (LR17H160001 to C.L.), Fundamental Research Funds for the Central Universities (2016QNA7023 and 2017QNA7028 to C.L.) and the Thousand Talent Program for Young Outstanding Scientists, China (to C.L.), IST Austria institutional funds (to S.H.), European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (725780 LinPro to S.H.). C.L. is a scholar of K. C. Wong Education Foundation.
Tian A, Kang B, Li B, et al. Oncogenic state and cell identity combinatorially dictate the susceptibility of cells within glioma development hierarchy to IGF1R targeting. Advanced Science. 2020;7(21). doi:10.1002/advs.202001724
Tian, A., Kang, B., Li, B., Qiu, B., Jiang, W., Shao, F., … Liu, C. (2020). Oncogenic state and cell identity combinatorially dictate the susceptibility of cells within glioma development hierarchy to IGF1R targeting. Advanced Science. Wiley. https://doi.org/10.1002/advs.202001724
Tian, Anhao, Bo Kang, Baizhou Li, Biying Qiu, Wenhong Jiang, Fangjie Shao, Qingqing Gao, et al. “Oncogenic State and Cell Identity Combinatorially Dictate the Susceptibility of Cells within Glioma Development Hierarchy to IGF1R Targeting.” Advanced Science. Wiley, 2020. https://doi.org/10.1002/advs.202001724.
A. Tian et al., “Oncogenic state and cell identity combinatorially dictate the susceptibility of cells within glioma development hierarchy to IGF1R targeting,” Advanced Science, vol. 7, no. 21. Wiley, 2020.
Tian A, Kang B, Li B, Qiu B, Jiang W, Shao F, Gao Q, Liu R, Cai C, Jing R, Wang W, Chen P, Liang Q, Bao L, Man J, Wang Y, Shi Y, Li J, Yang M, Wang L, Zhang J, Hippenmeyer S, Zhu J, Bian X, Wang Y, Liu C. 2020. Oncogenic state and cell identity combinatorially dictate the susceptibility of cells within glioma development hierarchy to IGF1R targeting. Advanced Science. 7(21), 2001724.
Tian, Anhao, et al. “Oncogenic State and Cell Identity Combinatorially Dictate the Susceptibility of Cells within Glioma Development Hierarchy to IGF1R Targeting.” Advanced Science, vol. 7, no. 21, 2001724, Wiley, 2020, doi:10.1002/advs.202001724.
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