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DOI: 10.5146/tjpath.2019.01470
Morphological Correlates of KIT and PDGFRA Genotypes in Gastrointestinal Stromal Tumour
Valli PRIYA, Niraj KUMARI, Narendra KRISHNANI
Department of Pathology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, LUCKNOW, INDIA
Keywords: Gastrointestinal stromal tumours, Morphology, KIT, PDGFRA, Sequence analysis

Objective: The aim of the study was to study the clinicopathological and immunohistochemical features of gastrointestinal stromal tumours and correlation with KIT/PDGFRA mutations.

Material and Method: Eighty consecutive resected cases were genotyped for KIT exons 11, 9, 13, 17 and PDGFRA exons 18, 14, 12 and correlated with histomorphology by nonparametric tests.

Results: Forty-seven cases (58.8%) were in the high-risk group. Males had higher rates of KIT exon 11 and PDGFRA exon 18 mutations than females (p=0.03). KIT and PDGFRA mutation frequencies were lower (58.8%) than western data showing KIT exon 11 mutation in 63.8%, KIT exon 9 mutation in 19% and PDGFRA exon 18 mutation in 17% of the cases. Extragastrointestinal stromal tumours (n=6) showed 100% mutation. KIT exon 11 deletion was associated with gastric location (60%) (p=0.04), spindle cells (63.3%), and high-risk stratification (66.6%) (p=0.01) while KIT exon 9 mutation was common in small intestine (66.7%) (p=0.04), in higher risk groups (66.7%) (p=0.01) and 75% of codon 502-503 duplications (p=0.03). PDGFRA 18 mutation was common in males (p=0.03), in gastric location (62.5%) (p=0.04), in cases showing mild to moderate atypia (62.5%) (p=0.01) and lower risk stratification (62.5%) (p=0.01). KIT/PDGFRA mutations were significantly associated with gender (p=0.03), location (p=0.04), nuclear atypia (p=0.01) and risk stratification (p=0.01).

Conclusion: Morphological features and anatomic location may be useful in deciding molecular testing strategy, particularly in resource-limited settings, when a plethora of targetable mutations are present. An algorithm may be derived for genotyping with KIT exon 11 and PDGFRA exon 18 heading the list of targetable mutations. This approach may reduce financial burden on patients as well as workload on hospital staff.


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