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BIM expression in treatment-naive cancers predicts responsiveness to kinase inhibitors
Open accessPublished version of a preprint
Abstract
Cancers with specific genetic mutations are susceptible to selective kinase inhibitors. However, there is a wide spectrum of benefit among cancers harboring the same sensitizing genetic mutations. Herein, we measured apoptotic rates among cell lines sharing the same driver oncogene following treatment with the corresponding kinase inhibitor. There was a wide range of kinase inhibitor-induced apoptosis despite comparable inhibition of the target and associated downstream signaling pathways. Surprisingly, pretreatment RNA levels of the BH3-only pro-apoptotic BIM strongly predicted the capacity of EGFR, HER2, and PI3K inhibitors to induce apoptosis in EGFR-mutant, HER2-amplified, and PIK3CA-mutant cancers, respectively, but BIM levels did not predict responsiveness to standard chemotherapies. Furthermore, BIM RNA levels in EGFR-mutant lung cancer specimens predicted response and duration of clinical benefit from EGFR inhibitors. These findings suggest assessment of BIM levels in treatment-naïve tumor biopsies may indicate the degree of benefit from single-agent kinase inhibitors in multiple oncogene-addiction paradigms. Significance: In several oncogene-addiction paradigms, assessment of BIM RNA levels identifies those cancers that fail to have substantial apoptotic responses to kinase inhibitors. BIM RNA levels may be assessed in diagnostic cancer specimens to predict which patients will receive less benefit from single-agent kinase inhibitors. Cancer Discovery: 1(4); 352–65. ©2011 AACR. Read the Commentary on this article by Yoshida and Haura, p. 289 This article is highlighted in the In This Issue feature, p. 275
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“Previous studies have shown that high levels of pretreatment BIM can predict the apoptotic response of oncogene-addicted cancers to their cognate kinase inhibitors (Faber et al., 2011).”
From A Landscape of Therapeutic Cooperativity in KRAS Mutant Cancers Reveals Principles for Controlling Tumor Evolution (2017) · cites this paper as Faber et al., 2011
In the citing paper
“Patients harbouring BIM deletion polymorphisms23 or patients with low-to-intermediate levels of BIM mRNA18 are associated with reduced clinical efficacy when treated with EGFR-TKIs.25”
From Mechanisms of resistance to EGFR-targeted drugs: lung cancer (2016) · cites this paper as [25]
In the citing paper
“Indeed, we observed that levels of the pro-apoptotic BH3-only Bcl2 family member, BIM, are predictive of response to targeted therapy in EGFR mutant lung cancers, HER2-amplified breast cancers and PIK3CA mutant cancers (Faber et al., 2011).”
From ERBB Receptors: From Oncogene Discovery to Basic Science to Mechanism-Based Cancer Therapeutics (2014) · cites this paper as Faber et al., 2011
In the citing paper
“In this study, although erlotinib or lapatinib inhibited EGFR and HER2 and downstream signaling in EGFR mutant and HER2-amplified cancers, respectively, only those cell lines with high levels of BIM underwent marked apoptosis.”
From ERBB Receptors: From Oncogene Discovery to Basic Science to Mechanism-Based Cancer Therapeutics (2014) · cites this paper as Faber et al., 2011
In the citing paper
“BIM protein normally is induced following inhibition of EGFR and HER2 in these cancers.”
From ERBB Receptors: From Oncogene Discovery to Basic Science to Mechanism-Based Cancer Therapeutics (2014) · cites this paper as Faber et al., 2011
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Lynch, T. J., Bell, D. W., Sordella, R., Gurubhagavatula, S., Okimoto, R. A., Brannigan, B. W., Harris, P. L., Haserlat, S. M., Supko, J. G., Haluska, F. G., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040938 · Cited by 11,486
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
Self-citationAnaplastic Lymphoma Kinase Inhibition in Non–Small-Cell Lung Cancer
Kwak, E. L., Bang, Y., Camidge, D. R., Shaw, A. T., Solomon, B., Maki, R. G., Ou, S. I., Dezube, B. J., Janne, P. A., Costa, D. B., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1006448 · Cited by 4,477
Self-citationInhibition of Mutated, Activated BRAF in Metastatic Melanoma
Flaherty, K. T., Puzanov, I., Kim, K. B., Ribas, A., McArthur, G. A., Sosman, J. A., O'Dwyer, P. J., Lee, R. J., Grippo, J. F., Nolop, K., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1002011 · Cited by 3,103
ABT-263: A Potent and Orally Bioavailable Bcl-2 Family Inhibitor
Tse, C., Shoemaker, A. R., Adickes, J., Anderson, M. G., Chen, J., Jin, S., Johnson, E. F., Marsh, K. C., Mitten, M. J., Nimmer, P., et al. (2008) · Cancer Research · doi:10.1158/0008-5472.can-07-5836 · Cited by 1,992
Clinical Features and Outcome of Patients With Non–Small-Cell Lung Cancer Who Harbor EML4-ALK
Shaw, A. T., Yeap, B. Y., Mino-Kenudson, M. A., Digumarthy, S. R., Costa, D. B., Heist, R. S., Solomon, B., Stubbs, H., Admane, S., McDermott, U., et al. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2009.22.6993 · Cited by 1,873
Self-citationCerto, M. V., Moore, V. D. G., Nishino, M., Wei, G., Korsmeyer, S. J., Armstrong, S. A., & Letai, A. G. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.03.027 · Cited by 1,278
Xiao, C., Srinivasan, L., Calado, D. P., Patterson, H. C., Zhang, B., Wang, J., Henderson, J., Kutok, J. L., & Rajewsky, K. (2008) · Nature Immunology · doi:10.1038/ni1575 · Cited by 1,248
Apoptosis Initiated When BH3 Ligands Engage Multiple Bcl-2 Homologs, Not Bax or Bak
Willis, S. N., Fletcher, J. I., Kaufmann, T., van Delft, M. F., Chen, L., Czabotar, P. E., Ierino, H., Lee, E. F., Fairlie, W. D., Bouillet, P., et al. (2007) · Science · doi:10.1126/science.1133289 · Cited by 1,146
Preexistence and clonal selection of MET amplification in EGFR mutant NSCLC
Turke, A. B., Zejnullahu, K., Wu, Y.-L., Song, Y., Dias-Santagata, D., Lifshits, E., Toschi, L., Rogers, A., Mok, T., Sequist, L., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2009.11.022 · Cited by 1,059
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Items 201–282 of 282
Luo, J., Makhnin, A., Tobi, Y. Y., Ahn, L. S. H., Hayes, S. A., Iqbal, A. N., Ng, K., Arcila, M. E., Riely, G. J., Kris, M. G., et al. (2021) · JCO Precision Oncology · doi:10.1200/po.20.00315 · Cited by 12
Targeting apoptosis to manage acquired resistance to third generation EGFR inhibitors
Sun, S. (2022) · Frontiers of Medicine · doi:10.1007/s11684-022-0951-0 · Cited by 11
Rice, S. J., Liu, X., Wang, H., & Belani, C. P. (2019) · PLoS ONE · doi:10.1371/journal.pone.0217657 · Cited by 11
High BIM mRNA levels are associated with longer survival in advanced gastric cancer
Wu, N., Huang, Y., Zou, Z., Giménez-Capitán, A. A., Yu, L., Hu, W., Zhu, L., Sun, X., Sánchez, J. J., Guan, W., et al. (2017) · Oncology Letters · doi:10.3892/ol.2017.5660 · Cited by 11
Pharmacologic Inhibition of SHP2 Blocks Both PI3K and MEK Signaling in Low-epiregulin HNSCC via GAB1
Kurupi, R., Floros, K. V., Jacob, S., Chawla, A. T., Cai, J., Hu, B., Puchalapalli, M., Coon, C. M., Khatri, R., Crowther, G. S., et al. (2022) · Cancer Research Communications · doi:10.1158/2767-9764.crc-21-0137 · Cited by 12
Self-citationKim, N., Cho, A., Watanabe, H., Choi, Y., Aziz, M., Kassner, M., Joung, J., Park, A. K.-J., Francis, J. M., Bae, J. S., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.7318 · Cited by 10
Kim, B. W., Cho, H., Ylaya, K., Kitano, H., Chung, J., Hewitt, S. M., & Kim, J. (2017) · Anticancer Research · doi:10.21873/anticanres.11896 · Cited by 10
May, L., Hu, B., Jerajani, P., Jagdeesh, A., Alhawiti, O., Cai, L., Semenova, N., Guo, C., Isbell, M., Deng, X., et al. (2024) · Cancer Research · doi:10.1158/0008-5472.can-24-0585 · Cited by 9
Self-citationIncharoen, P., Charonpongsuntorn, C., Saowapa, S., Sirachainan, E., Dejthevaporn, T. S., Kampreasart, K., Trachu, N., Muntham, D., & Ruengwetwattana, T. (2019) · Asian Pacific Journal of Cancer Prevention · doi:10.31557/apjcp.2019.20.12.3581 · Cited by 9
Zheng, L., Lin, B., Song, Z., Xie, F., Hong, W., Feng, J., Shao, L., & Zhang, Y. (2013) · Europe PMC (PubMed Central) · doi:10.3779/j.issn.1009-3419.2013.12.03 · Cited by 9
Association of BIM Deletion Polymorphism and BIM-γ RNA Expression in NSCLC with EGFR Mutation
Isobe, K., Kakimoto, A., MIKAMI, T., Kaburaki, K., Kobayashi, H., YOSHIZAWA, T., MAKINO, T., OTSUKA, H., Sano, G., Sugino, K., et al. (2016) · Cancer Genomics & Proteomics · doi:10.21873/cgp.20010 · Cited by 9
Wang, J., Wei, H., Zhao, B.-X., Li, M., Lv, W., Lv, L., Song, B., & Lv, S. (2014) · Journal of Molecular Histology · doi:10.1007/s10735-014-9583-2 · Cited by 9
Shao, Y., Chang, Y.-L., Huang, C.-Y., Hsu, C., & Cheng, A. (2013) · Oncology · doi:10.1159/000356019 · Cited by 7
Siddik, Z. H. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-396521-9.00012-7 · Cited by 6
Takeuchi, S., Yoshimura, K., Fujiwara, T., Ando, M., Shimizu, S., Nagase, K., Hasegawa, Y., Takahashi, T., Katakami, N., Inoue, A., et al. (2017) · The Journal of Medical Investigation · doi:10.2152/jmi.64.321 · Cited by 7
Lv, F., Sun, L., Yang, Q., Pan, Z., & Zhang, Y. (2021) · BioMed Research International · doi:10.1155/2021/3621828 · Cited by 7
Mahfoudhi, E., Ricordel, C., Lécuyer, G., Mouric, C., Léna, H., & Pedeux, R. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.853501 · Cited by 7
Clinical importance of Bcl-2-like 11 deletion polymorphism in idiopathic pulmonary fibrosis
Isobe, K., Issiki, T., Sakamoto, S., Sano, G., Takai, Y., Tochigi, N., & Homma, S. A. (2019) · Journal of Thoracic Disease · doi:10.21037/jtd.2019.07.25 · Cited by 5
Precursor B-ALL Cell Lines Differentially Respond to SYK Inhibition by Entospletinib
Sender, S., Sekora, A., Perez, S. V., Chabanovska, O., Becker, A., Ngezahayo, A., Junghanß, C., & Escobar, H. M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22020592 · Cited by 6
Development of personalized treatments in lung cancer: focusing on the EGFR mutations and beyond
Mitsudomi, T., & Suda, K. (2013) · Lung Cancer Targets and Therapy · doi:10.2147/lctt.s49603 · Cited by 6
The Potential Benefits of BIM in the Further Pursuit of Biomarker Discovery in Cancer Therapeutics
Yoshida, T., & Haura, E. B. (2011) · Cancer Discovery · doi:10.1158/2159-8290.cd-11-0193 · Cited by 6
Bringing target-matched PI3King from the bench to the clinic
Jankú, F. (2013) · Cell Cycle · doi:10.4161/cc.25118 · Cited by 6
Single Nucleotide Polymorphisms (SNPs) in Non-Small Cell Lung Cancer (NSCLC) Patients
Rosell, R., & Wei, J. (2012) · The Oncologist · doi:10.1634/theoncologist.2012-0205 · Cited by 6
Minimal residual disease in EGFR-mutant non-small-cell lung cancer
Bain, N. T., Wang, Y., & Arulananda, S. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.1002714 · Cited by 5
Arai, S., Takeuchi, S., Fukuda, K., Tanimoto, A., Nishiyama, A., Konishi, H., Takagi, A., Takahashi, H., Ong, S. T., & Yano, S. (2020) · The Journal of Medical Investigation · doi:10.2152/jmi.67.343 · Cited by 5
Yao, Y., Chu, H., Wang, J., & Wang, B. (2018) · International Journal of Molecular Medicine · doi:10.3892/ijmm.2018.3835 · Cited by 5
Pathak, A., Rajappa, S. J., & Gore, A. A. (2017) · Indian Journal of Cancer · doi:10.4103/ijc.ijc_505_17 · Cited by 4
[Research Progress of the Role of EMT in EGFR-TKIs Resistance of Non-small Cell Lung Cancer].
Li, Y., Huang, S., Lv, W., He, Z., & Hu, J. (2018) · Europe PMC (PubMed Central) · doi:10.3779/j.issn.1009-3419.2018.12.08 · Cited by 4
Sale, M. J., & Cook, S. J. (2014) · Biochemical Journal · doi:10.1042/bj20131346 · Cited by 4
[Enhanced Lung Recovery after Surgery, Is It A Necessary for Precision Therapy?]
Qian, K., Zhang, Y., & Zhi, X. (2017) · Europe PMC (PubMed Central) · doi:10.3779/j.issn.1009-3419.2017.08.08 · Cited by 4
Zhao, J., Gao, J., Guo, L., Hu, X., Liu, Q., Zhao, J., Liu, L., Jiang, J., Wang, M., Liang, Z., et al. (2017) · Europe PMC (PubMed Central) · doi:10.3779/j.issn.1009-3419.2017.09.05 · Cited by 4
The PDE4DIP-AKAP9 axis promotes lung cancer growth through modulation of PKA signalling
Fu, Y., Huang, S., Pan, R., Chen, X., Liu, T., Zhang, R. X., Zhu, F., Fang, Q., Wu, L., Dai, J., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-07621-y · Cited by 3
Zheng, W., Niu, N., Zeng, J., Ke, X., & Jin, S. K. (2022) · Translational Cancer Research · doi:10.21037/tcr-22-1050 · Cited by 3
Spraggs, C. F., Parham, L. R., Song, K. S., Briley, L. P., Johnson, T., Russo, M., Tada, H., du Bois, A., & Xu, C. (2015) · Annals of Oncology · doi:10.1093/annonc/mdv211 · Cited by 3
Iommelli, F., Rosa, V. D., Fonti, R., & Vecchio, S. D. (2014) · Clinical and Translational Imaging · doi:10.1007/s40336-014-0050-6 · Cited by 4
Upadhyay, S. K., Rai, R. C., Gehtori, R., Paliwal, A., Gautam, P., & Joshi, P. (2017) · Springer eBooks · doi:10.1007/978-3-319-48683-3_20 · Cited by 4
Sakashita, S., Shiba‐Ishii, A., Murata, Y., Sekimoto, R., Minami, Y., Sato, Y., & Noguchi, M. (2018) · Pathology - Research and Practice · doi:10.1016/j.prp.2018.05.016 · Cited by 3
Fennell, D. A. (2013) · Europe PMC (PubMed Central) · doi:10.3978/j.issn.2218-6751.2013.01.03 · Cited by 3
Epithelial to Mesenchymal Transition (EMT)
Malviya, R., Singh, A. K., & Yadav, D. (2023) · doi:10.1002/9781394209866.ch7 · Cited by 3
Regulated cell death plasticity in cancer: thresholds, reversibility, and therapeutic failure
Jawwad, T., Baba, S. K., Surendranath, A., Chaudhary, E., Jeelani, G., Akil, A. S. A.-S., Menhali, A. A., Bhat, A. A., & Mirza, S. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-08584-2 · Cited by 2
Yoshimori, T., Kawami, M., Kumagai, Y., Futatsugi, S., Yumoto, R., Uchida, Y., & Takano, M. (2024) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/j.biocel.2024.106601 · Cited by 2
[Effect and significance of BH3-only protein in targeted therapy of non-small cell lung cancer].
Gao, W., Huang, W., & Liu, K. (2014) · Europe PMC (PubMed Central) · doi:10.3779/j.issn.1009-3419.2014.11.08 · Cited by 2
Ultra-micro samples can be used for mRNA quantification of lung cancer biomarkers
Sandfeld‐Paulsen, B., Demuth, C., Folkersen, B. H., Rasmussen, T. R., Madsen, L. B., Sørensen, B. S., & Meldgaard, P. (2016) · Scandinavian Journal of Clinical and Laboratory Investigation · doi:10.3109/00365513.2016.1143114 · Cited by 2
Xie, B., Qiu, Y., Zhou, J., Du, D., Ma, H., Ji, J., Zhu, L., & Zhang, W. (2022) · Clinical & Translational Oncology · doi:10.1007/s12094-022-02884-x · Cited by 2
Chu, C., Lin, C., Lin, C., Li, C., Wu, S., Tsai, J., Yang, S., Chen, C., Lin, C., Chang, C., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-30565-4 · Cited by 2
Brosseau, S., Oulkhouir, Y., Naltet, C., & Zalcman, G. (2015) · Bulletin du Cancer · doi:10.1016/s0007-4551(15)31215-7 · Cited by 2
Rosell, R. (2012) · doi:10.2217/ebo.12.11 · Cited by 2
Ma, L., Zhang, J., Dai, Z., Liao, P., Guan, J., & Luo, Z. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1512349 · Cited by 1
AMPK Limits MNNG-Induced Parthanatos by Inhibiting BH3-Only Protein Bim
Hamano, S., Maruyama, T., Suzuki, M., Mitsuya, M., Yokosawa, T., Hirata, Y., Matsuzawa, A., & Noguchi, T. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms262110519 · Cited by 1
Perurena, N., Watanabe, M., Schade, A. E., Brown, W. R., Luo, E. Y., Gardner, A., Indeglia, A., Yoshinaga, A., Sahu, R., Yang, Y., et al. (2026) · Cancer Research · doi:10.1158/0008-5472.can-24-3113 · Cited by 1
Resistance to EGFR Inhibitors in NSCLC: Mechanistic Insights and Emerging Therapies
Khoury, R., Raffoul, C., Hanna, C., Saleh, K., Shayya, A., Nahouli, M., & Ghanem, H. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27125197 · Cited by 2
Signals Delivered By Interleukin-7 Regulate The Activities Of Bim And Jund In T Lymphocytes
Ruppert, S. M. (2012) · Journal of International Crisis and Risk Communication Research · Cited by 1
Sensitivity and Resistance to BH3 Mimetics in Cancer Therapy
Floros, K. V., Faber, A. C., & Harada, H. (2018) · Resistance to targeted anti-cancer therapeutics · doi:10.1007/978-3-319-67932-7_7 · Cited by 1
Self-citationOne gene to rule them all…and in the darkness bind them
Floros, K. V., & Faber, A. C. (2018) · Molecular & Cellular Oncology · doi:10.1080/23723556.2018.1465881 · Cited by 1
Self-citationSchrock, A. B. (2013) · Digital Access to Scholarship at Harvard (DASH) (Harvard University)
Strategy on Patients with EGFR Mutation
Früh, M., Zhou, Q. H., Leung, L. K. S., & Mok, T. S. K. (2014) · Springer eBooks · doi:10.1007/978-3-319-06062-0_9
Cappuzzo, F. (2015) · Springer eBooks · doi:10.1007/978-3-319-20741-4_3
Ebi, H., & Mitsudomi, T. (2012) · Informa Healthcare eBooks · doi:10.3109/9781841848679.005
Self-citationUse of genetically engineered mouse models in preclinical drug development
Creedon, H. (2015) · ERA
Resistance to Tyrosine Kinase Inhibitors in Different Types of Solid Cancer
Mirone, G., Perna, S., & Marfè, G. (2016) · Resistance to targeted anti-cancer therapeutics · doi:10.1007/978-3-319-46091-8_2
Characterization of regulatory mechanisms for BIM exon 3 alternative splicing
Bhadra, M. (2017) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/69548
Development of Therapy for Overcoming EGFR-TKI Resistance due to BIM Polymorphisms
Takeuchi, S. (2015) · Haigan · doi:10.2482/haigan.55.941
Korth, M. (2017) · OPen Access Repositorium der Universität Ulm (OPARU) (Ulm University) · doi:10.18725/oparu-4364
Les rebiopsies : pourquoi ? Comment ?
Saint-Paul, A., Ballouhey, J., & Vergnenégre, A. (2017) · Revue des Maladies Respiratoires Actualités · doi:10.1016/s1877-1203(17)30044-7
Calvayrac, O., Pradines, A., Mazières, J., & Favre, G. (2018) · médecine/sciences · doi:10.1051/medsci/20183401003
[Research Progress of New Generation EGFR-TKIs after Third-generation].
Liu, Y., Yihui, L. I., & Wang, J. (2020) · PubMed Central · doi:10.3779/j.issn.1009-3419.2020.102.28
Epithelial-mesenchymal transition and resistance to EGFR inhibitors
Jacob, S., Kurupi, R., & Faber, A. C. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-822833-3.00009-7
Self-citationRole of epithelial to mesenchymal transition in the resistant mechanism of EGFR-TKIs
Adachi, Y., & Ebi, H. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-822833-3.00005-x
Self-citationApoptosis signaling in EGFR inhibitor resistance in NSCLC
Aka, Y., Karakaş, B., & Kütük, Ö. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-822833-3.00001-2
Lugin, M. L., Lei, W., Lee, R. T., Chung, J. Y., Katritsis, N. M., Hwang, W., Fleischman, A. G., Han, N., & Kwon, Y. J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.26.656072
Byerly, J. H., Port, E. R., & Irie, H. Y. (2020) · Figshare · doi:10.6084/m9.figshare.12586300
Daraxonrasib (RMC-6236) is an effective targeted therapy for RAS -mutant neuroblastomaPreprint
Hill, R. D., Dalton, K. M., Kurupi, R., Slaughter, J. M., Roberts, J., Xing, Y., Kehinde, V., Zhang, K., Hu, B., Kraskauskiene, V., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.19.706849
Self-citationEl-Gharbawi, N., Ellithy, H. N., Eldesouky, M., & ElMaraashly, A. H. (2026) · The Egyptian Journal of Haematology · doi:10.4103/ejh.ejh_154_25
Molecular mechanisms of drug-tolerance to EGFR-targeted therapies in lung adenocarcinoma
Léonce, C. (2021) · theses.fr (ABES) · doi:10.70675/0611e924z7044z428cz90dcz9235e0a4b5a2
Development of a G-Quadruplex-Forming DNA Aptamer Against EGFR-Driven MalignanciesPreprint
Singh, D., Kumar, V., Kumar, A., Kushwaha, T., Baswal, K., Kulandaisamy, R., Kumar, M., Kumar, S., Malik, P. S., Prafullakumar, T., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-9758197/v1
Development of a G-Quadruplex-Forming DNA Aptamer Against EGFR-Driven MalignanciesPreprint
Singh, D., Kumar, V., Kumar, A., Kushwaha, T., Baswal, K., Kulandaisamy, R., Kumar, M., Kumar, S., Malik, P. S., Prafullakumar, T., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-9758197/v2
Agha, L. T. H. A. (2026) · Gaziantep Islam Science and Technology University · doi:10.46871/eams.1774236
Giri, S., Selvadurai, B. R., Gupta, N., Nieves, A. S., Genna, A., Lindzen, M., Chatterjee, R., Daele, M. V., Ramesh-Kumar, D., Zerbib, M., et al. (2026) · Advanced Science · doi:10.1002/advs.78290
Novel Role of ErbB-2 in Inhibition of Jagged-1-Mediated Trans-Activation of Notch in Breast Cancer
Pandya, K. (2013) · Loyola eCommons (Loyola University of Chicago)
Metadata
- Authors
- Faber, A. C., Corcoran, R. B., Ebi, H., Sequist, L. V., Waltman, B. A., Chung, E., Incio, J., Digumarthy, S. R., Pollack, S. F., Song, Y., Muzikansky, A., Lifshits, E., Roberge, S., Coffman, E. J., Benes, C. H., Gómez, H. L., Baselga, J., Arteaga, C. L., Rivera, M. N., Dias-Santagata, D., Jain, R. K., & Engelman, J. A.
- Affiliations
- Harvard University (US)
- Authors' Affiliations: 1Pathology and 2Radiology, Massachusetts General Hospital, Boston; 3Massachusetts General Hospital Cancer Center, Boston; 4Department of Medicine, Harvard Medical School, Boston; 5Radiation Oncology, Steele Lab for Tumor Biology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts; 6Department of Medicine, 7Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, Tennessee; 8Instituto Nacional de Enfermedades Neoplásicas, Lima, Perú
- Corresponding author
- Engelman, Jeffrey A.
- ORCID
- Venue
- Cancer Discovery
- Published
- 2011-09-01
- Volume
- 1
- Issue
- 4
- Pages
- 352-365
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- PMC
- PMC3229203
- OpenAlex
- W2117986690
- Cited by
- 283
- References
- 50
- Citations by year
- 2026: 9 · 2025: 6 · 2024: 4 · 2023: 11 · 2022: 13 · 2021: 15 · 2020: 15 · 2019: 8 · 2018: 27 · 2017: 26 · 2016: 27 · 2015: 31 · 2014: 34 · 2013: 33 · 2012: 22
- FWCI
- 24.81
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cancer Discovery (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Vanderbilt University
- Vanderbilt-Ingram Cancer Center
- National Cancer Institute (P50CA127003, R01CA080195, R01CA140594, P50CA090578, P01CA080124, P20CA090578, R01CA135257, K08CA120060, P50CA098131, R01CA137008)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Cell death mechanisms and regulation
- Health Sciences › Medicine › Oncology › HER2/EGFR in Cancer Research
- Keywords
- building information modeling, BH3-only proteins, kinase inhibitors, predictive biomarkers, apoptosis, EGFR inhibitors, HER2 inhibitors, PI3K inhibitors, oncogene addiction, EGFR-mutant lung cancer, PIK3CA mutation, treatment-naive tumors, drug response prediction
- MeSH terms
- Bcl-2-Like Protein 11, Phosphoinositide-3 Kinase Inhibitors, Animals, Female, Humans, Lung Neoplasms, Membrane Proteins, Mice, Nude, Oncogenes, Proto-Oncogene Proteins, Retrospective Studies, Cohort Studies, Signal Transduction, Apoptosis, Receptor, ErbB-2, Erb-b2 Receptor Tyrosine Kinases, Phosphatidylinositol 3-Kinases, Cell Line, Tumor, Protein Kinase Inhibitors, Apoptosis Regulatory Proteins, BH3 Interacting Domain Death Agonist Protein, Mice, ErbB Receptors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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