The DOI matches its Crossref record; 39 of the 40 references it cites were found in a registry or an index.
Drug Resistance via Feedback Activation of Stat3 in Oncogene-Addicted Cancer Cells
Open accessAbstract
Pathway-targeted cancer drugs can produce dramatic responses that are invariably limited by the emergence of drug-resistant cells. We found that many drug-treated "oncogene-addicted" cancer cells engage a positive feedback loop leading to Stat3 activation, consequently promoting cell survival and limiting overall drug response. This was observed in cancer cells driven by diverse activated kinases, including EGFR, HER2, ALK, and MET, as well as mutant KRAS. Specifically, MEK inhibition led to autocrine activation of Stat3 via the FGF receptor and JAK kinases, and pharmacological inhibition of MEK together with JAK and FGFR enhanced tumor regression. These findings suggest that inhibition of a Stat3 feedback loop may augment the response to a broad spectrum of drugs that target pathways of oncogene addiction.
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“Lee et al. found that transient STAT3 activation mediated by IL-6 and FGFR in response to oncogenic kinase inhibition significantly contributes to survival of several different oncogene-addicted cancer cell lines [67].”
From Emerging Insights into Targeted Therapy-Tolerant Persister Cells in Cancer (2021) · cites this paper as [67]
In the citing paper
“Similarly, Lee et al., found that many oncogene-addicted cancer cells (including EGFR, HER2, ALK, MET, KRAS) engage an IL-6 dependent feedback loop leading to STAT3 activation [67]. This STAT3 activation promotes cell survival and limits the overall drug response.”
From Emerging Insights into Targeted Therapy-Tolerant Persister Cells in Cancer (2021) · cites this paper as [67]
Citations
Cites
Differential expression analysis for sequence count data
Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Glioma stem cells promote radioresistance by preferential activation of the DNA damage response
Bao, S., Wu, Q., McLendon, R. E., Hao, Y., Shi, Q., Hjelmeland, A. B., Dewhirst, M. W., Bigner, D. D., & Rich, J. N. (2006) · Nature · doi:10.1038/nature05236 · Cited by 6,363
Cancer drug resistance: an evolving paradigm
Holohan, C., Van Schaeybroeck, S., Longley, D. B., & Johnston, P. G. (2013) · Nature Reviews Cancer · doi:10.1038/nrc3599 · Cited by 4,681
MET Amplification Leads to Gefitinib Resistance in Lung Cancer by Activating ERBB3 Signaling
Engelman, J. A., Zejnullahu, K., Mitsudomi, T., Song, Y., Hyland, C., Park, J. O., Lindeman, N., Gale, C.-M., Zhao, X., Christensen, J., et al. (2007) · Science · doi:10.1126/science.1141478 · Cited by 4,496
STATs in cancer inflammation and immunity: a leading role for STAT3
Yu, H., Pardoll, D., & Jove, R. (2009) · Nature reviews. Cancer · doi:10.1038/nrc2734 · Cited by 4,383
Györffy, B., Lanczky, A., Eklund, A. C., Denkert, C., Budczies, J., Li, Q., & Szallasi, Z. (2010) · Breast Cancer Research and Treatment · doi:10.1007/s10549-009-0674-9 · Cited by 4,169
Epidermal growth factor receptor mutations in lung cancer
Sharma, S. V., Bell, D. W., Settleman, J., & Haber, D. A. (2007) · Nature Reviews Cancer · doi:10.1038/nrc2088 · Cited by 3,170
Self-citationBromberg, J. F., Wrzeszczynska, M. H., Devgan, G., Zhao, Y., Pestell, R. G., Albanese, C., & Darnell, J. E. (1999) · Cell · doi:10.1016/s0092-8674(00)81959-5 · Cited by 2,790
A Chromatin-Mediated Reversible Drug-Tolerant State in Cancer Cell Subpopulations
Sharma, S. V., Lee, D. Y., Li, B., Quinlan, M. P., Takahashi, F., Maheswaran, S., McDermott, U., Azizian, N., Zou, L., Fischbach, M. A., et al. (2010) · Cell · doi:10.1016/j.cell.2010.02.027 · Cited by 2,770
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Targeting the IL-6/JAK/STAT3 signalling axis in cancer
Johnson, D. E., O'Keefe, R. A., & Grandis, J. R. (2018) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2018.8 · Cited by 3,110
Emerging Biological Principles of Metastasis
Lambert, A. W., Pattabiraman, D. R., & Weinberg, R. A. (2017) · Cell · doi:10.1016/j.cell.2016.11.037 · Cited by 3,191
Hata, A. N., Niederst, M. J., Archibald, H. L., Gomez-Caraballo, M., Siddiqui, F. M., Mulvey, H. E., Maruvka, Y. E., Ji, F., Bhang, H.-E. C., Krishnamurthy Radhakrishna, V., et al. (2016) · Nature Medicine · doi:10.1038/nm.4040 · Cited by 985
Understanding and targeting resistance mechanisms in NSCLC
Rotow, J. K., & Bivona, T. G. (2017) · Nature reviews. Cancer · doi:10.1038/nrc.2017.84 · Cited by 997
JAK-STAT Signaling: A Double-Edged Sword of Immune Regulation and Cancer Progression
Owen, K. L., Brockwell, N. K., & Parker, B. S. (2019) · Cancers · doi:10.3390/cancers11122002 · Cited by 728
Metadata
- Authors
- Lee, H.-J., Zhuang, G., Cao, Y., Du, P., Kim, H.-J., & Settleman, J.
- Affiliations
- Genentech (US)
- Corresponding author
- Settleman, Jeff
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2014-08
- Volume
- 26
- Issue
- 2
- Pages
- 207-221
- ISSN
- 1535-6108 (ISSN-L)
- OpenAlex
- W2102365935
- Cited by
- 555
- References
- 40
- Citations by year
- 2026: 23 · 2025: 27 · 2024: 36 · 2023: 41 · 2022: 38 · 2021: 61 · 2020: 55 · 2019: 63 · 2018: 46 · 2017: 65 · 2016: 54 · 2015: 42 · 2014: 4
- FWCI
- 26.52
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cancer Cell (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Cytokine Signaling Pathways and Interactions
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Melanoma and MAPK Pathways
- Keywords
- STAT3, drug resistance, oncogene addiction, positive feedback loop, MEK inhibition, JAK inhibition, fibroblast growth factor receptor, EGFR, HER2, anaplastic lymphoma kinase, MET, mutant KRAS, autocrine signaling, combination therapy, tumor regression
- MeSH terms
- Erlotinib Hydrochloride, Adenocarcinoma of Lung, Adenocarcinoma, Animals, Antineoplastic Agents, Cell Survival, Humans, Imidazoles, Lung Neoplasms, Mutation, Nitriles, Oncogenes, Proto-Oncogene Proteins, Pyrazoles, Pyridazines, Pyrimidines, Quinazolines, Signal Transduction, Interleukin-6, Proto-Oncogene Proteins p21(ras), Mice, SCID, Receptors, Fibroblast Growth Factor, ras Proteins, Drug Resistance, Neoplasm, Phosphatidylinositol 3-Kinases, Xenograft Model Antitumor Assays, Cell Line, Tumor, STAT3 Transcription Factor, Mice, Kaplan-Meier Estimate, Janus Kinase 1, ErbB Receptors
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