Abstract
Background: Many studies have examined specific mutations in patients with resected lung adenocarcinoma across heterogeneous stages, comprising predominantly advanced/metastatic disease, but there is little data regarding the mutation profile of patients with early stage node negative disease. The aim of this study was to identify patterns of mutations in early stage node negative lung adenocarcinoma. Methods: A total of 204 patients who underwent resection for stage IB (sixth Ed American Joint Committee on Cancer) lung adenocarcinoma and received no neoadjuvant or adjuvant treatments were identified. Tumors were genotyped using the OncoCarta v1.0 kit (Sequenom, San Diego, CA) on the Sequenom MassARRAY platform. Fluorescence in situ hybridization for ALK rearrangement was also performed. Results: A total of 110 (54%) patients' tumors harbored at least one mutation. KRAS, EGFR, PIK3CA, ALK, PDGFRA, AKT1, BRAF, FGFR1, and HRAS mutations were detected in tumors from 77 (37.7%), 29 (14.2%), 9 (4.4%), 2 (1%), 2 (1%), 1 (0.5%), 1 (0.5%), 1 (0.5%), and 1 (0.5%) patients respectively. Synchronous mutations (either comutations or double mutations) were identified in 18 (8.8%) patients. KRAS and PIK3CA mutations were associated with poorly differentiated tumors (p = 0.03; p = 0.02), whereas EGFR mutations were associated with well-differentiated tumors (p = 0.001). Five tumours contained EGFR mutations (one T790M and four exon 20 insertions), which are associated with resistance to EGFR tyrosine kinase inhibitors (EGFR-TKIs). Conclusions: Diverse patterns of mutations are seen in resected node-negative lung adenocarcinoma including an unexpectedly low rate of ALK rearrangement, EGFR mutations associated with resistance to EGFR-TKIs and a high rate of synchronous mutations. These data may influence the design of future adjuvant targeted therapy trials.
| Original language | English |
|---|---|
| Pages (from-to) | 408-414 |
| Number of pages | 7 |
| Journal | Journal of Thoracic Oncology |
| Volume | 8 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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