scholarly journals Afatinib for the treatment of EGFR mutation-positive NSCLC: A review of clinical findings

2020 ◽  
Vol 26 (6) ◽  
pp. 1461-1474 ◽  
Author(s):  
R Donald Harvey ◽  
Val R Adams ◽  
Tyler Beardslee ◽  
Patrick Medina
Keyword(s):  
Adverse Events ◽  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Egfr Mutation ◽  
Kinase Inhibitor ◽  
Egfr Mutations ◽  
Real World Data ◽  
Egfr Tyrosine Kinase ◽  
Egfr Tyrosine Kinase Inhibitors

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors represent the standard of care in patients with EGFR mutation-positive ( EGFRm+) non-small cell lung cancer (NSCLC). The availability of several EGFR tyrosine kinase inhibitors approved for use in the first-line or later settings in NSCLC warrants an in-depth understanding of the pharmacological properties of, and clinical data supporting, these agents. The second-generation, irreversible ErbB-family blocker, afatinib, has been extensively studied in the context of EGFRm+ NSCLC. Results from the LUX-Lung 3 and 6 studies showed that afatinib was more active and better tolerated than chemotherapy in patients with tumors harboring EGFR mutations. Subanalysis of these trials, along with real-world data, indicates that afatinib is active in patients with certain uncommon EGFR mutations (S768I/G719X/L861Q) as well as common mutations (Del19/L858R), and in patients with active brain metastases. In LUX-Lung 7, a head-to-head phase IIb trial, afatinib improved progression-free survival and time-to-treatment failure versus the first-generation reversible EGFR tyrosine kinase inhibitor, gefitinib, albeit with a higher incidence of serious treatment-related adverse events. Nevertheless, afatinib is generally well tolerated, and adverse events are manageable through supportive care and a well-defined tolerability-guided dose adjustment scheme. In this review, we provide a detailed overview of the pharmacology, efficacy, and safety of afatinib, discuss treatment sequencing strategies following emergence of different resistance mechanisms, and shed light on the economic impact of afatinib. We also provide a comparison of afatinib with the available EGFR tyrosine kinase inhibitors and discuss its position within treatment strategies for patients with EGFRm+ NSCLC.

scholarly journals V843I, a Lung Cancer Predisposing EGFR Mutation, Is Responsible for Resistance to EGFR Tyrosine Kinase Inhibitors

2014 ◽  
Vol 9 (9) ◽  
pp. 1377-1384 ◽  
Author(s):  
Satsuki Matsushima ◽  
Kouki Ohtsuka ◽  
Hiroaki Ohnishi ◽  
Masachika Fujiwara ◽  
Hiroyuki Nakamura ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Egfr Mutation ◽  
Egfr Tyrosine Kinase ◽  
Egfr Tyrosine Kinase Inhibitors

CtDNA assay to detect EGFR mutations and mechanisms of resistance to EGFR tyrosine kinase inhibitors.

2016 ◽  
Vol 34 (15_suppl) ◽  
pp. e23042-e23042
Author(s):  
Lyudmila Bazhenova ◽  
Satya Das ◽  
Sandip Pravin Patel ◽  
Lyle Arnold ◽  
Veena M. Singh
Keyword(s):  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Egfr Mutations ◽  
Mechanisms Of Resistance ◽  
Egfr Tyrosine Kinase ◽  
Egfr Tyrosine Kinase Inhibitors

Prospective study for usefulness of circulating-free DNA on prediction of third generation EGFR tyrosine kinase inhibitors.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21510-e21510
Author(s):  
Hironori Yoshida ◽  
Chiho Nakashima ◽  
Naohisa Matsumoto ◽  
Kentaro Iwanaga ◽  
Noriyuki Ebi ◽  
...  
Keyword(s):  
Tyrosine Kinase ◽  
Disease Progression ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Egfr Mutations ◽  
Plasma Samples ◽  
Egfr Tyrosine Kinase ◽  
Egfr Tyrosine Kinase Inhibitors ◽  
Nsclc Patients ◽  
Egfr T790m

e21510 Background: Most non-small lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations develop resistance when exposed to EGFR-tyrosine kinase inhibitors (TKIs). T790M develops in about half of patients treated with TKI and can be detected by tumor tissue and cfDNA hotspot tests. However, co-occurring mutations at other loci may impact efficacy. We conducted a prospective, multi-center, observational study to assess the detection rates and predictive values of plasma-based EGFR T790M detection methods for Japanese NSCLC patients treated with osimertinib. Methods: NSCLC patients with tumor EGFR mutations and disease progression after treatment with 1st- or 2nd-generation EGFR-TKI were enrolled. Plasma was collected at the time of clinical disease progression, before osimertinib treatment. The collected plasma was tested for EGFR T90M by in-house plasma MBP-QP and ddPCR assays and compared to clinically tested cobas (Roche) results (including tissue, plasma). The primary endpoint was to demonstrate comparability of our MBP-QP system to cobas using plasma-based EGFR T790M detection to predict the therapeuitic effect of osimertinib via objective response rate (ORR) and disease control rate (DCR). As an exploratory analysis, we used Guardant360 to retrospectively test available banked plasma samples collected describe time points. Results: From Feb 2017 to Jan 2019, 145 patients enrolled. T790M was detected by cobas in 57 cases (44 tissue, 16 plasma, 3 both). ORR and DCR in plasma cobas-positive cases were 62.5% and 81.3%, respectively. MBP-QP found T790M in 9 patients with ORR and DCR 66.7% and 77.8%. ddPCR found 17 cases with ORR and DCR 70.6% and 82.4%. ORR was not correlated to AF. In plasma samples from 54 patients, Guardant360 detected T790M in 57%. Co-occurring alterations such as amplification or minor mutations in EGFR or other genes such as TP53 did not impact ORR, but in the group with poor response to osimertinib, the number of detected gene alterations tended to be large. Two patients with small cell carcinoma transformation had RB1 mutations and MYC amplification. Conclusions: Regardless of the test system, the detection of T790M could predict a good therapeutic effect of osimertinib, but there was no difference in response to osimertinib depending on EGFR T790M AF. Compared to single-gene assessment of EGFR, NGS of cfDNA may be useful for guiding treatment decisions for patients with TKI-resistant NSCLC. Clinical trial information: UMIN000025930.

Identification of RET fusion as mechanisms of resistance to EGFR tyrosine-kinase inhibitors.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e21074-e21074
Author(s):  
Zhongxing Bing ◽  
Weiran Wang ◽  
Danhua Wang ◽  
Tonghui Ma
Keyword(s):  
Lung Cancer ◽  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Next Generation Sequencing Data ◽  
Egfr Mutations ◽  
Egfr Tyrosine Kinase ◽  
Egfr Tyrosine Kinase Inhibitors ◽  
Egfr Tki ◽  
Egfr Tkis

e21074 Background: Responses to EGFR-targeted therapy are generally temporary, due to inevitable drug resistance. Although RET fusions have been identified in resistant EGFR-mutant non–small cell lung cancer (NSCLC), their characteristics acquired resistance to EGFR tyrosine-kinase inhibitors (TKIs) are rarely investigated. Methods: We retrospectively reviewed next-generation sequencing data of EGFR+ lung cancer patients, and 8 patients were identified coexisting of EGFR mutations and RET fusion. Their treatment history was collected. Results: The co-occurrence of RET fusion with EGFR oncogenic variations was observed in eight patients, and all of the 8 patients have received previous EGFR-TKI treatment. EGFR mutations were including 4 L858R mutations, 4 exon 19 deletions, and 6 T790M mutations. And the partner genes of RET identified by NGS were including TRIM33 (2/8), GPRC6A (1/8), TLN1 (1/8), KIAA1598 (1/8), SPECC1 (1/8), TRIM24 (1/8) and CCDC6 (1/8). The allelic fractions (AFs) of first-generation EGFR-TKI sensitizing mutations were higher than AFs of EGFR T790M mutations as well as AFs of RET fusion. These RET fusions are fused with rare partner genes, rather than the most common KIF5B in lung cancer. Conclusions: This study extended the knowledge of RET fusion as resistance mechanism to EGFR TKIs in lung cancer. The detection of RET fusions may uncover potential resistance mechanisms of EGFR TKIs, which might inform therapeutic strategies, such as combination-therapy approaches.[Table: see text]

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