Lung cancer is one of the leading cause of cancer death worldwide, the most common histological type of lung cancer is non-small cell lung cancer (NSCLC), whose occurrence and development is closely related to the mutation and amplification of epidermal growth factor receptors (EGFR).
Although the EGF receptor tyrosine kinase inhibitors (EGFR-TKI) erlotinib and gefitinib have shown dramatic effects against EGFR mutant lung cancer, patients become resistant by various mechanisms, including gatekeeper EGFR-T790M mutation, Met amplification, and HGF overexpression, thereafter relapsing.
Treatment strategies for non-small-cell lung cancer, the most common form of lung cancer, continue to evolve, most recently with the positive trial results for EGF receptor (EGFR) tyrosine kinase inhibitors in the first-line setting in molecularly targeted populations.
Patients with advanced or metastatic forms of lung cancer with an activating mutation in <i>epidermal growth factor receptor</i> (<i>EGFR</i>) are given tyrosine kinase inhibitors (TKIs) targeted therapies that are more efficient than chemotherapy.
As both lesions were resected, were of the same histologic subtype and presented the same immunohistochemistry profile; we decided to perform mutational analysis of the epidermal growth factor (EGFR) gene to differentiate between recurrence and second primary lung cancer.
Since a high percentage of lung adenocarcinoma in Asian female nonsmokers contains activating hotspot mutations in epidermal growth factor receptors (EGFR), we hypothesized that NAT2 polymorphisms might represent a risk factor in lung cancer with EGFR mutations.
Collectively, our in vivo and in vitro findings support that TWIST1 collaborates with the EGF pathway in promoting EMT in EGFR mutated lung adenocarcinoma and that large series of EGFR mutated lung cancer patients are needed to further define the prognostic role of TWIST1 reactivation in this subgroup.
We created a proof-of-principle database [DNA-mutation Inventory to Refine and Enhance Cancer Treatment (DIRECT)], starting with lung cancer-associated EGF receptor (EGFR) mutations, to provide a resource for clinicians to prioritize treatment decisions based on a patient's tumor mutations at the point of care.
Epidermal growth factor (EGF) receptor (EGFR) mutations are the best illustration of the therapeutic relevance of identifying such molecular clusters of lung cancer based on driver genetic alterations that predict the efficacy of specific tyrosine kinase inhibitors, a strategy referred to as "personalized medicine."
To establish and develop a reliable and simple Real-time PCR assay with high resolution melting (Real-time PCR-HRM) method for detection epidermal growth factor (EGFR) and BIM mutation of lung cancer and looking for effective targeted drugs to control lung cancer.
Smoking patients with lung cancer with EBs were significantly younger (63.6 versus 67.7 years, p = 0.0179) and had tumors with a lower frequency of epidermal growth factor gene (EGFR) mutations (3.8% versus 24.2%, p = 0.0184) compared with those without EBs.
Epidermal growth factor (EGF)/DNA complexes targeted to cancer cells overexpressing the EGF receptor resulted in efficient transduction of several lung cancer cell lines in vitro.
In the present study, we assessed the diagnostic value of epidermal growth factor (egf) and cancer antigens 125 (ca125) and 15-3 (ca15-3) in bronchoalveolar lavage fluid (balf) of lung cancer from 79 enrolled patients with suspected lung cancer.
Stimulation of lung cancer cells with epidermal growth factor activated the signal transducer and activator of transcription 3 pathway and induced expression of Cten in all cell lines.
We investigated the time-dependent PIAS3 shuffling and binding to STAT3 in an EGF-dependent model in lung cancer by using confocal microscopy, immunoprecipitation, luciferase reporter assay, and protein analysis of segregated cellular components.
In particular, expression of BCR, which is required for EGFR protein degradation, was induced by EGF stimulation, suggesting a negative feedback loop in lung cancer.