Analysis of KIT mutations in sporadic and familial gastrointestinal stromal tumors: Therapeutic implications through protein modeling

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Abstract

Purpose: Gastrointestinal stromal tumors (GIST) are characterized by expressing a gain-of-function mutation in KIT, and to a lesser extent, PDGFR. Imatinib mesylate, a tyrosine kinase inhibitor, has activity against GISTs that contain oncogenic mutations of KIT. In this study, KIT and PDGFRα mutation status was analyzed and protein modeling approaches were used to assess the potential effect of KIT mutations in response to imatinib therapy. Experimental Design: Genomic DNA was isolated from GIST tumors. Exons 9, 11, 13, and 17 of c-KIT and exons 12, 14, and 18 of PDGFRα were evaluated for oncogenic mutations. Protein modeling was used to assess mutations within the juxtamembrane region and the kinase domain of KIT. Results: Mutations in KIT exons 9, 11, and 13 were identified in GISTs with the majority of changes involving the juxtamembrane region of KIT. Molecular modeling indicates that mutations in this region result in disruption of the KIT autoinhibited conformation, and lead to gain-of-function activation of the kinase. Furthermore, a novel germ-line mutation in KIT was identified that is associated with an autosomal dominant predisposition to the development of GIST. Conclusions: We have used proteih modeling and structural analyses to elucidate why patients with GIST tumors containing exon 11 mutations are the most responsive to imatinib mesylate treatment. Importantly, mutations detected in this exon and others displayed constitutive activation of KIT. Furthermore, we have found tumors that are both KIT and PDGFRα mutation negative, suggesting that additional, yet unidentified, abnormalities may contribute to GIST tumorigenesis. © 2005 American Association for Cancer Research.

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Tarn, C., Merkel, E., Canutescu, A. A., Shen, W., Skorobogatko, Y., Heslin, M. J., … Godwin, A. K. (2005). Analysis of KIT mutations in sporadic and familial gastrointestinal stromal tumors: Therapeutic implications through protein modeling. Clinical Cancer Research, 11(10), 3668–3677. https://doi.org/10.1158/1078-0432.CCR-04-2515

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