The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Sequential Application of Anticancer Drugs Enhances Cell Death by Rewiring Apoptotic Signaling Networks
Open accessAbstract
SUMMARY Crosstalk and complexity within signaling pathways, and their perturbation by oncogenes, limits component-by-component approaches to understanding human disease. Network analysis of how normal and oncogenic signaling can be re-wired by drugs may provide opportunities to target tumors with high specificity and efficacy. Using targeted inhibition of oncogenic signaling pathways combined with DNA damaging chemotherapy, we report that time-staggered EGFR inhibition, but not simultaneous co-administration, dramatically sensitizes a subset of triple-negative breast cancer cells to genotoxic drugs. Systems-level analysis—using high-density time-dependent measurements of signaling networks, gene expression profiles, and cell phenotypic responses in combination with mathematical modeling— revealed an approach for altering the intrinsic state of the cell through dynamic re-wiring of oncogenic signaling pathways. This process converts these cells to a less tumorigenic state that is more susceptible to DNA damage-induced cell death by re-activation of an extrinsic apoptotic pathway whose function is suppressed in the oncogene-addicted state.
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Chou, T.-C., & Talalay, P. (1984) · Advances in Enzyme Regulation · doi:10.1016/0065-2571(84)90007-4 · Cited by 7,178
Triple-negative breast cancer: clinical features and patterns of recurrence
Dent, R., Trudeau, M., Pritchard, K. I., Hanna, W. M., Kahn, H. K., Sawka, C. A., Lickley, L. A., Rawlinson, E., Sun, P., & Narod, S. A. (2007) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-06-3045 · Cited by 5,091
The DNA Damage Response: Ten Years After
Harper, J. W., & Elledge, S. J. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.11.015 · Cited by 1,705
Systems biology and combination therapy in the quest for clinical efficacy
Fitzgerald, J. B., Schoeberl, B., Nielsen, U. B., & Sorger, P. K. (2006) · Nature Chemical Biology · doi:10.1038/nchembio817 · Cited by 570
Self-citation
Cited by
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Al-Lazikani, B., Banerji, U., & Workman, P. (2012) · Nature Biotechnology · doi:10.1038/nbt.2284 · Cited by 1,070
Structure and dynamics of molecular networks: A novel paradigm of drug discovery
Csermely, P., Korcsmáros, T., Kiss, H. J. M., London, G., & Nussinov, R. (2013) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2013.01.016 · Cited by 892
Next-generation proteomics: towards an integrative view of proteome dynamics
Altelaar, A. F. M., Munoz, J., & Heck, A. J. R. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3356 · Cited by 782
Systems genetics approaches to understand complex traits
Civelek, M., & Lusis, A. J. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3575 · Cited by 621
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Metadata
- Authors
- Lee, M. J., Ye, A. S., Gardino, A. K., Heijink, A. M., Sorger, P. K., MacBeath, G., & Yaffe, M. B.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2012-05
- Volume
- 149
- Issue
- 4
- Pages
- 780-794
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2123183032
- Cited by
- 680
- References
- 6
- FWCI
- 27.42
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Lee, M. J., Ye, A. S., Gardino, A. K., Heijink, A. M., Sorger, P. K., MacBeath, G., & Yaffe, M. B. (2012). Sequential Application of Anticancer Drugs Enhances Cell Death by Rewiring Apoptotic Signaling Networks. Cell. https://doi.org/10.1016/j.cell.2012.03.031
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
