Application of Ventana immunocytochemical analysis on ThinPrep cytology slides for detection of ALK rearrangement in patients with advanced non–small-cell lung cancer - Hui Qin Guo (BMC Cancer, 2018)
Abstract Background Ventana ALK (D5F3) screening of anaplastic lymphoma kinase (ALK) gene rearrangement in tissue specimens has been approved by US FDA (Food and Drug Administration) to select treatment for non–small-cell lung carcinoma (NSCLC). However, tumor tissues are often not readily obtainable, and cytology specimens and may be the only tumor material available for diagnosis and molecular marker analysis. In this study, we evaluated the feasibility of ALK immunocytochemistry (ICC) on ThinPrep slides and determined a suitable scoring system for interpretation of the results. Methods One hundred twenty-one fine-needle aspirate (FNA) specimens from metastatic lesions of NSCLC were analyzed. ALK rearrangement was detected on ThinPrep cytology slides using the Ventana immunocytochemistry ALK-D5F3 system, which adopts two scoring systems for interpretation of the ICC results. The results were subsequently confirmed by reverse transcription polymerase chain reaction (RT-PCR) analysis and fluorescence in situ hybridization (FISH). Results Among the 121 ICC specimens, 16 that were considered ALK-positive by either scoring system were referred for PCR analysis. Among the ALK ICC-negative cases, 33 had correlated FISH ALK results. A total of 49 specimens that exhibited either a positive or negative ICC result with a correlated ALK status were analyzed statistically. ICC results showed a high concordance rate with the results of PCR/FISH analysis. The sensitivity and specificity of ALK ICC by the binary scoring algorithm were 68.75 and 96.97%, respectively. These values increased to 93.75 and 96.97%, respectively, when interpreted by the semiquantified interpretation system. Conclusions ALK ICC analysis on ThinPrep slides is a reliable ALK testing method, and the semiquantified interpretation system on cytology specimens is recommended rather than the binary scoring algorithm on tissue specimens.