An Unbalanced Exon-Expression qPCR-based Assay for Detection of ALK Translocation (Fusion) in Lung Cancer
Journal Title: Pulmonary Research and Respiratory Medicine – Open Journal - Year 2017, Vol 4, Issue 1
Abstract
Non-Small Cell Lung Cancer (NSCLC) constitutes 85-90% of all lung cancer. Accurate diagnosis and selection of targeted therapies in lung cancer depends on robust detection of the molecular events that underlie its pathogenesis. Since patients having a rearrangement in the Anaplastic Lymphoma Kinase (ALK) gene respond well to treatment with crizotinib, identification of such ALK mutations is necessary for the successful treatment of NSCLC. The most common rearrangement of the ALK gene in NSCLC involves fusion with echinoderm microtubule-associated protein-like 4 (EML 4) as the upstream partner. Current testing methods for this rearrangement (IHC and/or FISH) can be very subjective due to high operator variability. They require expert interpretation by a pathologist and have a long turnaround time. The FDAapproved Fluorescence In Situ Hybridization (FISH) test has been shown to lack sensitivity and is generally acknowledged to fail to detect rearrangements in up to 60% of patients. Here, we have adapted an approach described earlier and optimized it for use with degraded RNA obtained from Formalin-Fixed Paraffin-Embedded (FFPE) sections. This method is based on the unbalanced expression of 5’- and 3’-regions (exons) of the ALK gene. It is also applicable to the detection of other cancer-relevant gene rearrangements e.g. ROS 1 or RET that result in increased expression of the 3’-kinase domain. Patients with these rearrangements have been shown to respond to crizotinib and cabozantinib, respectively. Using NSCLC cell lines we demonstrate that our method is cost-effective, reproducible, sensitive, objective, and easy to use. Unlike FISH, it does not require interpretation by several scorers and it can be performed in any clinical laboratory with access to a qPCR instrument. Here we present the protocol for the method and validation with 197 clinical samples.
Authors and Affiliations
Rama K. Singh
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