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Updated: Mar 22, 2026

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
Published on: September 20, 2016
Non-small Cell Lung Cancer with Concomitant EGFR, KRAS, and ALK Mutation: Clinicopathologic Features of 12 Cases
Taebum Lee1, Boram Lee1, Yoon-La Choi1
1Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Background:
Although epidermal growth factor receptor (EGFR), v-Ki-ras2 Kirsten rat sarcoma viral oncogene (KRAS), and anaplastic lymphoma kinase (ALK) mutations in non-small cell lung cancer (NSCLC) were thought to be mutually exclusive, some tumors harbor concomitant mutations. Discovering a driver mutation on the basis of morphologic features and therapeutic responses with mutation analysis can be used to understand pathogenesis and predict resistance in targeted therapy.
Methods:
In 6,637 patients with NSCLC, 12 patients who had concomitant mutations were selected and clinicopathologic features were reviewed. Clinical characteristics included sex, age, smoking history, previous treatment, and targeted therapy with response and disease-free survival. Histologic features included dominant patterns, nuclear and cytoplasmic features.
Results:
All patients were diagnosed with adenocarcinoma and had an EGFR mutation. Six patients had concomitant KRAS mutations and the other six had KRAS mutations. Five of six EGFR-KRAS mutation patients showed papillary and acinar histologic patterns with hobnail cells. Three of six received EGFR tyrosine kinase inhibitor (TKI) and showed partial response for 7-29 months. All six EGFR-ALK mutation patients showed solid or cribriform patterns and three had signet ring cells. Five of six EGFR-ALK mutation patients received EGFR TKI and/or ALK inhibitor and four showed partial response or stable disease, except for one patient who had acquired an EGFR mutation.
Conclusions:
EGFR and ALK mutations play an important role as driver mutations in double mutated NSCLC, and morphologic analysis can be used to predict treatment response.
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