Study Finds Immunohistochemistry Is More Effective Than FISH in Detecting EML4-ALK Rearrangments in Lung Cancer
A retrospective study by Pekar-Zlotin et al investigating fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) for detecting EML4-ALK rearrangement in patients with lung cancer has found that FISH may miss a significant number of patients who tested positive with immunohistochemistry and who may benefit from targeted ALK therapy. Screening for EML4-ALK by immunohistochemistry should be strongly considered, and next-generation sequencing analysis performed on borderline cases, concluded the researchers. The study is published in The Oncologist.
Study Details
This retrospective, cross-sectional study included 57 patients with lung adenocarcinoma who were assessed for EML4-ALK rearrangement between 2011 and 2013. Sufficient tumor samples for analysis were obtained from 51 patients. All tissue samples underwent testing with FISH and IHC (D5F3 antibody). Those with discordant results underwent further testing with next-generation sequencing analysis.
Of the 51 patients tested, four (7.8%) were positive by FISH, and eight (15.7%) were positive by IHC. Three were positive by both. Next-generation sequencing confirmed that four of the five patients who were positive by IHC and negative by FISH were positive for ALK. Two were treated with crizotinib (Xalkori) and had progression-free survivals of 18 and 6 months. Considering next-generation sequencing as the most accurate test, the sensitivity and specificity were 42.9% and 97.7%, respectively, for FISH, and 100% and 97.7%, respectively, for IHC.
Recommendations
Based on these findings, the researchers proposed an algorithm for molecular testing to improve the selection of individualized therapy for patients with advanced lung adenocarcinoma. The algorithm includes standard EGFR mutation analysis and IHC D5F3 antibody testing for ALK. If IHC testing is inconclusive for ALK, ALK genetic analysis with the next-generation sequencing assay should be considered.
“Such an algorithm will allow more patients to be treated with appropriate personalized medicine,” concluded the researchers.
Nir Peled, MD, PhD, is the corresponding author of this study.
For full disclosures of the study authors, visit http://theoncologist.alphamedpress.org.
The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
