Clinicopathological features and diagnostic methods of ALK fusion-positive non-small cell lung cancer in Korea

Lung cancer is one of the most common malignancies and the leading cause of cancer-associated mortality in Korea. A significant amount of effort has been put into the development of new and more effective treatments and biological markers for the prediction of therapeutic responses, which has led to the identification of various genetic changes in cancer, that are the so-called ‘growth drivers’ of carcinogenesis. Certain genetic alterations have become new treatment targets, and it has been suggested that different mutations are associated with different clinicopathological characteristics and prognosis. The present study aimed to evaluate the status of the key ‘driver’ mutation anaplastic lymphoma kinase (ALK) fusion in Korean patients with non-small cell lung cancer (NSCLC) and its association with clinicopathological characteristics, including the presence of other genetic mutations. The present study also compared different methods for ALK fusion detection, including fluorescence in situ hybridization (FISH), immunohistochemistry (IHC) and next-generation sequencing (NGS) to evaluate which method is the most effective. A total of 482 patients with NSCLC who underwent ALK FISH analysis were evaluated for clinicopathological features, such as age, sex, smoking history, tumor stage, histological subtype, immunohistochemical profile, including ALK and EGFR mutation statuses, and survival. Some ALK FISH-positive and -negative cancers were newly submitted to NGS analysis for DNA and RNA alterations. The ALK fusion-positive tumors were associated with a younger age, female patients, frequent nodal metastases, advanced stage and shorter survival. Comparing the results of ALK FISH, IHC and NGS analyses, it was concluded that in practice, ALK testing should better be diversified concerning FISH and IHC, and NGS analysis would be a good alternative to FISH, with an additional advantage of being able to concurrently detect different mutations.