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J Thorac Oncol. 2013 Mar;8(3):322-8. doi: 10.1097/JTO.0b013e31827db604.

Combined use of ALK immunohistochemistry and FISH for optimal detection of ALK-rearranged lung adenocarcinomas.

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Department of Pathology Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA.



ALK gene rearrangements occur in approximately 5% of lung adenocarcinomas (ACAs), leading to anaplastic lymphoma kinase (ALK) overexpression and predicting response to targeted therapy. Fluorescence in situ hybridization (FISH) is the standard procedure for detection of ALK rearrangements in lung ACA but requires specialized equipment and expertise. Immunohistochemistry (IHC) for ALK protein overexpression is a promising screening modality, with reports of newer antibodies showing excellent sensitivity and specificity for ALK-rearranged lung ACA.


In this study, we analyzed ALK IHC (5A4 clone) in 186 cases from our clinical service and compared it with ALK FISH and EGFR and KRAS mutation status.


Twelve cases had concordant ALK protein overexpression and ALK rearrangement by FISH. Three ALK-rearranged cases lacked ALK protein expression. Of these discrepant cases, one had a coexisting EGFR mutation and a subtle atypical ALK rearrangement manifested as a break in the 5' centromeric portion of the FISH probe. One case had a concurrent BRAF mutation. Follow-up testing on a metastasis revealed absence of the ALK rearrangement, with persistent BRAF mutation. In one ALK-rearranged protein negative case, very limited tissue remained for ALK IHC, raising the possibility of false negativity because of protein expression heterogeneity. Importantly, ALK protein expression was detected in one case initially thought not to have an ALK rearrangement. In this case, FISH was falsely negative because of interference by benign reactive nuclei. After correcting for these cases, ALK IHC was 93% sensitive and 100% specific as compared with FISH.


ALK IHC improves the detection of ALK rearrangements when used together with FISH, and its use in lung ACA genetic testing algorithms should be considered.

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