scholarly journals Early prediction of resistance to tyrosine kinase inhibitors by plasma monitoring of EGFR mutations in NSCLC: a new algorithm for patient selection and personalized treatment

Oncotarget ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 982-991 ◽  
Author(s):  
Fiamma Buttitta ◽  
Lara Felicioni ◽  
Alessia Di Lorito ◽  
Alessio Cortellini ◽  
Luciana Irtelli ◽  
...  
Keyword(s):  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Patient Selection ◽  
Kinase Inhibitors ◽  
Personalized Treatment ◽  
Egfr Mutations ◽  
Early Prediction ◽  
Plasma Monitoring

scholarly journals Early Prediction of Response to Tyrosine Kinase Inhibitors by Quantification of EGFR Mutations in Plasma of NSCLC Patients

2015 ◽  
Vol 10 (10) ◽  
pp. 1437-1443 ◽  
Author(s):  
Antonio Marchetti ◽  
John F. Palma ◽  
Lara Felicioni ◽  
Tommaso M. De Pas ◽  
Rita Chiari ◽  
...  
Keyword(s):  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Egfr Mutations ◽  
Early Prediction ◽  
Prediction Of Response ◽  
Nsclc Patients

Mutational analysis of EGFR and KIT in thymic epithelial tumor

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 18049-18049
Author(s):  
K. Yoh ◽  
Y. Nishiwaki ◽  
G. Ishii ◽  
K. Goto ◽  
K. Kubota ◽  
...  
Keyword(s):  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Thymic Carcinoma ◽  
Kinase Inhibitors ◽  
Mutational Analysis ◽  
Direct Sequencing ◽  
Egfr Mutations ◽  
Epithelial Tumor ◽  
Thymic Epithelial Tumor ◽  
Number Of Patients

18049 Background: Thymic epithelial tumor has been reported to express the epidermal growth factor receptor (EGFR), and thymic carcinoma has recently been described to have overexpression of KIT. We investigated the prevalence of EGFR and KIT mutations in patients with thymoma and thymic carcinoma to explore the potential for a targeted therapy with tyrosine kinase inhibitors. Methods: Genomic DNA was isolated from 41 paraffin-embedded tumor samples including 24 thymoma and 17 thymic carcinoma. EGFR mutations in exons 18, 19 and 21, and KIT mutations in exons 9, 11, 13 and 17, were analyzed by PCR and direct sequencing. Protein expressions of EGFR and KIT were also evaluated by immunohistochemistry. Results: We detected the EGFR mutation in 2 of 20 thymoma, but none of thymic carcinoma had mutation. All of the detected EGFR mutations were missense mutations in exon 21 (L858R and G863D, respectively). Expression of EGFR was seen in 71% of thymoma and 53% of thymic carcinoma. On mutational analysis of KIT, only one thymic carcinoma displayed a missense mutation in exon 11 (L576P). Expression of KIT was observed in 88% of thymic carcinoma and 0% of thymoma. Conclusions: Our findings indicate that a small number of patients with thymic epithelial tumor exhibit somatic mutations of EGFR or KIT although expressions of EGFR or KIT are present frequently in thymic epithelial tumor. Further investigations are warranted to determine their susceptibility to tyrosine kinase inhibitors in the treatment of thymoma and thymic carcinoma with EGFR or KIT mutations. No significant financial relationships to disclose.

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.

scholarly journals Lung Cancer: Biomarkers, Tyrosine Kinase Inhibitors and Monoclonal Antibodies

2017 ◽  
Vol 1 (2) ◽  
pp. 41
Author(s):  
Made Putra Semadhi ◽  
Stefanus Layli Prasojo ◽  
Anandani Widarini
Keyword(s):  
Lung Cancer ◽  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Excision Repair ◽  
Neuron Specific Enolase ◽  
Egfr Mutations ◽  
Ca 125 ◽  
Cytokeratin 19 ◽  
Dna Mutation

Lung cancer is the most contributor of cancer cause death in the world. Lung cancer is related to cigarette consumption and genetic factor. Nicotine derived nitrosamine ketone is the most important inducer of lung cancer associated with DNA Mutations resulting in the activation of Kirsten rat sarcoma viral (KRAS) oncogenes. DNA Mutation in Lung cancer is mostly presence by epidermal growth factor receptor (EGFR) mutations. There were seven potential biomarkers to detect early lung cancer, whereas carcinoembryonic antigen (CEA), neuron specific enolase (NSE), cytokeratin-19 fragments (CYFRA 21-1), alpha-fetoprotein (AFP), cancer antigen 125 (CA-125), CA-199 and ferritin. The use of biomarkers in combination can improve the accuracy in diagnosing lung cancer. Other biomarkers include KRAS mutations, B-type Raf kinase (BRAF) mutation, mesenchymal-epithelial transition factor (MET) amplification and Excision repair cross-complementing group 1 (ERCC1) can be used to see whether there are any genetic mutations that lead to lung cancer. Treatment of lung cancer with chemotherapy can be done using tyrosine kinase inhibitors and monoclonal antibodies.Keywords: lung cancer, DNA mutation, EGFR, KRAS, BRAF, MET, tyrosine kinase 

scholarly journals Effective Tyrosine Kinase Inhibitors result in the intracellular accumulation of EGFR and allows response prediction in patients

2019 ◽  
Author(s):  
Maurice de Wit ◽  
Ya Gao ◽  
Darlene Mercieca ◽  
Iris de Heer ◽  
Bart Valkenburg ◽  
...  
Keyword(s):  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Conformational Changes ◽  
Clinical Benefit ◽  
Kinase Inhibitors ◽  
Response Prediction ◽  
Egfr Mutations ◽  
Tumor Type ◽  
Intracellular Accumulation ◽  
Egfr Tkis

AbstractClinical responses to EGFR tyrosine kinase inhibitors are restricted only to tumors harboring specific activating mutations and even then, not all tyrosine kinase inhibitors provide clinical benefit. We here show that the addition of EGFR-TKIs results in a strong and rapid intracellular accumulation of the protein. However, this accumulation was observed only in the context of a combination of a TKI-sensitive mutation with a clinically effective TKI: TKI-insensitive mutations did not show this accumulation nor did clinically ineffective TKIs induce accumulation. All TKIs effectively inhibited EGFR phosphorylation and downstream pathway activation, irrespective of the mutation present in EGFR. The discrepancy between molecular activity of TKIs and their efficacy in patients therefore is mimicked by the mutation- and TKI-specificity of intracellular accumulation. Using this intracellular accumulation as assay, we were able to predict response to gefitinib in a panel of cell-lines (harboring different EGFR mutations) and predicted clinical benefit to EGFR TKIs on a cohort of unselected pulmonary adenocarcinoma patients (hazard ratio 0.21, P=0.0004). Even in patients harboring rare mutations with unknown TKI-sensitivity, intracellular accumulation was predictive of the clinical response. The intracellular accumulation depended on a continued presence of TKI indicating that TKIs exert a continued effect on the protein even after its dephosphorylation. It is therefore possible that accumulation is caused by conformational changes induced by both the mutation and the TKI and this change induces a block in intracellular trafficking. Interestingly, intracellular accumulation was observed independent of the genetic background of the cell, indicating that accumulation is almost entirely dictated by the combination of mutation and TKI. Our results therefore suggest that TKI-sensitivity is tumor-type independent.

scholarly journals Early Dynamics of Chronic Myeloid Leukemia on Nilotinib Predicts Deep Molecular Response

2021 ◽  
Author(s):  
Yuji Okamoto ◽  
Mitsuhito Hirano ◽  
Kai Morino ◽  
Masashi K. Kajita ◽  
Shinji Nakaoka ◽  
...  
Keyword(s):  
Chronic Myeloid Leukemia ◽  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Myeloid Leukemia ◽  
Kinase Inhibitors ◽  
Myeloproliferative Disorder ◽  
Initial Time ◽  
Molecular Response ◽  
Early Prediction ◽  
Deep Molecular Response

AbstractChronic myeloid leukemia (CML) is a myeloproliferative disorder caused by the BCR-ABL1 tyrosine kinase1,2. ABL1-selective tyrosine kinase inhibitors (TKIs) including nilotinib have dramatically improved the prognosis of patients with CML3–7. The ultimate goal of CML treatment is likely to be TKI-free maintenance of deep molecular response (DMR), which is defined by quantitative measurement of BCR-ABL1 transcripts on the international scale (IS)8, and durable DMR is a prerequisite to reach this goal9. Thus, an algorithm to enable the early prediction of DMR achievement on TKI therapy is quite valuable. Here, we show that our mathematical framework based on a clinical trial dataset10 can accurately predict the response to frontline nilotinib. We found that our simple dynamical model can predict nilotinib response by using two common laboratory findings (observation values): IS11,12 and white blood cell (WBC) count. Furthermore, our proposed method identified patients who failed to achieve DMR with high fidelity according to the data collected only at three initial time points during nilotinib therapy. Since our model relies on the general properties of TKI response, our framework would be applicable to CML patients who receive frontline nilotinib or other TKIs in clinical practice.Significance StatementChronic myeloid leukemia (CML) is a myeloproliferative disorder caused by the BCR-ABL1 tyrosine kinase. The goal of this treatment is the sequential achievement of deep molecular response (DMR). Tyrosine kinase inhibitors (TKIs) are effective in the reduction because they inhibit CML cell proliferation. However, because of individual differences in the TKI efficacy, some patients are unable to achieve DMR, so that early prediction of DMR reachability is necessary for personalized medicine. By combining time series analysis and mathematical modeling, we developed a mathematical method that accurately predicts patients who do not achieve DMR in the early stages of TKI administration. Our prediction method gives a basis of effective personalized treatments for CML patients.

scholarly journals Defining the Sensitivity Landscape of 74,389 EGFR Variants to Tyrosine Kinase Inhibitors

2021 ◽  
Author(s):  
Lei An ◽  
Shuqing Chen ◽  
Guangyao Wu ◽  
Chang Liu ◽  
Zhenxing Wang ◽  
...  
Keyword(s):  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Small Cell Lung Carcinoma ◽  
Growth Factor Receptor ◽  
Saturation Mutagenesis ◽  
Egfr Mutations ◽  
Cell Lung Carcinoma ◽  
Treatment Regimens ◽  
Cytotoxicity Assays

Background: Tyrosine kinase inhibitors (TKIs) therapy is a standard treatment for patients with advanced non-small-cell lung carcinoma (NSCLC) when activating epidermal growth factor receptor (EGFR) mutations are detected. However, except for the well-studied EGFR mutations, most EGFR mutations lack treatment regimens. Methods: We constructed two EGFR variant libraries containing substitutions, deletions, or insertions using the saturation mutagenesis method. All the variants were located in the EGFR mutation hotspot (exons 18-21). The sensitivity of these variants to afatinib, erlotinib, gefitinib, icotinib, and osimertinib was systematically studied by determining their enrichment in massively parallel cytotoxicity assays using an endogenous EGFR-depleted cell line, PC9. Results: A total of 3,914 and 70,475 variants were detected in the constructed EGFR Substitution-Deletion (Sub-Del) and exon 20 Insertion (Ins) libraries, accounting for 99.3% and 55.8% of the designed variants, respectively. Of the 3,914 Sub-Del variants, 813 were highly enriched in the reversible TKI (erlotinib, gefitinib, icotinib) cytotoxicity assays and 51 were enriched in the irreversible TKI (afatinib, osimertinib) cytotoxicity assays. For the 70,475 Ins variants, insertions at amino acid positions 770-774 were highly enriched in all the five TKI cytotoxicity assays. Moreover, the top 5% of the enriched insertion variants included a glycine or serine insertion at high frequency. Conclusions: We present a comprehensive reference for the sensitivity of EGFR variants to five commonly used TKIs. The approach used here should be applicable to other genes and targeted drugs.

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