Literature DB >> 30718357

Novel Third-Generation EGFR Tyrosine Kinase Inhibitors and Strategies to Overcome Therapeutic Resistance in Lung Cancer.

Ayesha Murtuza1, Ajaz Bulbul1, John Paul Shen1, Parissa Keshavarzian1, Brian D Woodward1, Fernando J Lopez-Diaz1, Scott M Lippman1, Hatim Husain2.   

Abstract

EGFR-activating mutations are observed in approximately 15% to 20% of patients with non-small cell lung cancer. Tyrosine kinase inhibitors have provided an illustrative example of the successes in targeting oncogene addiction in cancer and the role of tumor-specific adaptations conferring therapeutic resistance. The compound osimertinib is a third-generation tyrosine kinase inhibitor, which was granted full FDA approval in March 2017 based on targeting EGFR T790M resistance. The compound has received additional FDA approval as first-line therapy with improvement in progression-free survival by suppressing the activating mutation and preventing the rise of the dominant resistance clone. Drug development has been breathtaking in this space with other third-generation compounds at various stages of development: rociletinib (CO-1686), olmutinib (HM61713), nazartinib (EGF816), naquotinib (ASP8273), mavelertinib (PF-0647775), and AC0010. However, therapeutic resistance after the administration of third-generation inhibitors is complex and not fully understood, with significant intertumoral and intratumoral heterogeneity. Repeat tissue and plasma analyses on therapy have revealed insights into multiple mechanisms of resistance, including novel second site EGFR mutations, activated bypass pathways such as MET amplification, HER2 amplification, RAS mutations, BRAF mutations, PIK3CA mutations, and novel fusion events. Strategies to understand and predict patterns of mutagenesis are still in their infancy; however, technologies to understand synthetically lethal dependencies and track cancer evolution through therapy are being explored. The expansion of combinatorial therapies is a direction forward targeting minimal residual disease and bypass pathways early based on projected resistance. ©2019 American Association for Cancer Research.

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Year:  2019        PMID: 30718357     DOI: 10.1158/0008-5472.CAN-18-1281

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  51 in total

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Authors:  Min Yuan; Li-Li Huang; Jian-Hua Chen; Jie Wu; Qing Xu
Journal:  Signal Transduct Target Ther       Date:  2019-12-17

Review 3.  Comprehensive review of targeted therapy for colorectal cancer.

Authors:  Yuan-Hong Xie; Ying-Xuan Chen; Jing-Yuan Fang
Journal:  Signal Transduct Target Ther       Date:  2020-03-20

4.  Detection of MET amplification by droplet digital PCR in peripheral blood samples of non-small cell lung cancer.

Authors:  Ying Fan; Rui Sun; Zhizhong Wang; Yuying Zhang; Xiao Xiao; Yizhe Liu; Beibei Xin; Hui Xiong; Daru Lu; Jie Ma
Journal:  J Cancer Res Clin Oncol       Date:  2022-05-18       Impact factor: 4.553

5.  Does the natural product, honokiol, have value in the battle against osimertinib resistance?

Authors:  Karin A Vallega; Shi-Yong Sun
Journal:  Oncoscience       Date:  2020-09-09

6.  Concurrent inhibition of ErbB family and MEK/ERK kinases to suppress non-small cell lung cancer proliferation.

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Journal:  Am J Transl Res       Date:  2020-03-15       Impact factor: 4.060

7.  Overcoming acquired resistance of epidermal growth factor receptor-mutant non-small cell lung cancer cells to osimertinib by combining osimertinib with the histone deacetylase inhibitor panobinostat (LBH589).

Authors:  Hongjing Zang; Guoqing Qian; Dan Zong; Songqing Fan; Taofeek K Owonikoko; Suresh S Ramalingam; Shi-Yong Sun
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8.  Targeting LRIG2 overcomes resistance to EGFR inhibitor in glioblastoma by modulating GAS6/AXL/SRC signaling.

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Journal:  Cancer Gene Ther       Date:  2020-01-28       Impact factor: 5.987

Review 9.  Recent advances in the development of AHR antagonists in immuno-oncology.

Authors:  Lijun Sun
Journal:  RSC Med Chem       Date:  2021-04-06

10.  Gene-Set Integrative Analysis of Multi-Omics Data Using Tensor-based Association Test.

Authors:  Sheng-Mao Chang; Meng Yang; Wenbin Lu; Yu-Jyun Huang; Yueyang Huang; Hung Hung; Jeffrey C Miecznikowski; Tzu-Pin Lu; Jung-Ying Tzeng
Journal:  Bioinformatics       Date:  2021-03-01       Impact factor: 6.937

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