Prediction of KIT Mutation in Gastrointestinal Stromal Tumors by the Immunoprofile of the Tumor Cells

• Main Authors: Chu-Chung Chou, Ming-Jen Chou, Chin-Yuan Tzen
• Format: Article
• Language: English
• Published: Elsevier 2010-01-01
• Series: Journal of the Formosan Medical Association
• Subjects: gastrointestinal stromal tumors; immunohistochemistry; KIT; mutation
• Online Access: http://www.sciencedirect.com/science/article/pii/S0929664610600186

Human KIT protooncogene is the cellular homolog of v-kit from the Hardy– Zuckerman 4 feline sarcoma virus, and encodes a 145-kDa type III tyrosine kinase growth factor receptor that is often mutated in gastrointestinal stromal tumors (GIST). Standardized mutation analysis is not available in many countries; therefore, we aimed to determine if the presence of KIT mutation in GIST can be predicted by the immunoprofile of the tumor cells. Methods: One hundred and forty-nine GIST were subjected to mutation analysis for KIT and immunohistochemical analysis for the expression of CD117, CD34, α-smooth muscle actin (SMA), and S100 protein. Mutation and immunohistochemistry data were correlated. Results: KIT mutation rates were higher in certain immunoprofile subsets of GIST than in GIST in general. Compared with the overall mutation rate of KIT (70%), all GIST with CD117+ and S100+ had > 80% probability of harboring mutated KIT, and the subset with additional CD34+ and SMA− had a mutation rate of 88%. The overall KIT mutation rate in CD117− GIST was 31%. However, the probability of KIT mutation in CD117− GIST with CD34+ SMA+S100−CD34−SMA−S100+ and CD34+SMA−S100+ was 100%, 100%, and 67%, respectively. Compared with the overall mutation rate (8.7%) of exon 9, GISTs with CD34+SMA+ had ≥ 20% probability of harboring an exon 9 mutation, and all GISTs in the small intestine had a probability of 19%. Conclusion: When mutation analysis is not available, immunoprofiles based on CD117, CD34, SMA, and S100 can be used to predict the presence of KIT mutation, but it is less useful for the prediction of exon 9 mutation in GISTs.