Precision medicine in NSCLC and pathology: how does ALK fit in the pathway?

The evolution of personalised medicine in lung cancer has dramatically impacted diagnostic pathology. Current challenges centre on the growing demands placed on small tissue samples by molecular diagnostic techniques. In this review, expert recommendations are provided regarding successful identification of anaplastic lymphoma kinase (ALK)-rearranged non-small-cell lung cancer (NSCLC). Steps to correctly process and conserve tumour tissue during diagnostic testing are essential to ensure tissue availability. For example, storing extra tissue sections ready for molecular diagnostic steps allows faster testing and preserves tissue. Fluorescence in situ hybridisation (FISH) is commonly used to detect ALK rearrangements, with most laboratories favouring screening by immunohistochemistry followed by a confirmatory FISH assay. Reverse transcription-polymerase chain reaction can also identify ALK fusion gene mRNA transcripts but can be limited by the quality of RNA and the risk that rare fusion variants may not be captured. Next-generation sequencing (NGS) technology has recently provided an alternative method for detecting ALK rearrangements. While current experience is limited, NGS is set to become the most efficient approach as an increasing number of genetic abnormalities is required to be tested. Upfront, reflex testing for ALK gene rearrangement should become routine as ALK tyrosine kinase inhibitor therapy moves into the first-line setting. Guidelines recommend that EGFR and ALK tests are carried out in parallel on all confirmed and potential adenocarcinomas, and this is more efficient in terms of tissue usage and testing turnaround time for both of these actionable gene alterations. The practice of sequential testing is not recommended. Identification of ALK rearrangements is now essential for the diagnosis of NSCLC, underpinned by the benefits of ALK inhibitors. As scientific understanding and diagnostic technology develops, ALK testing will continue to be an evolving and challenging paradigm.