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Cited by 317

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Molecular Pathobiology of Gastrointestinal Stromal Sarcomas

Corless, Christopher L., Heinrich, Michael C.·2008·Annual Review of Pathology: Mechanisms of Disease

Abstract

Gastrointestinal stromal tumors (GISTs) form an interesting group of sarcomas whose unique pathobiology provides a model of how molecularly targeted therapeutics can have a major impact on patient welfare. Approximately 85% of GISTs are driven by oncogenic mutations in either of two receptor tyrosine kinases: KIT or platelet-derived growth factor receptor α. We review the pivotal relationship between specific mutations in these kinase genes, the origin and pathologic spectrum of GISTs, and the response of these tumors to treatment with kinase inhibitors such as imatinib and sunitinib. Mechanisms of resistance to kinase inhibitor therapy are discussed, and targets for the next generation of therapeutics are considered. The rapid evolution in our understanding of GISTs, which stems directly from the close alliance of basic and clinical researchers in the field, illustrates the growing role of the molecular classification of solid tumors in the development of modern oncological treatments.

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Crossref · 10.1146/annurev.pathmechdis.3.121806.151538

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Metadata

Authors
Corless, C. L., & Heinrich, M. C.
Venue
Annual Review of Pathology: Mechanisms of Disease
Published
2008-02-01
Volume
3
Issue
1
Pages
557-586
ISSN
  • 1553-4006 (ISSN-L)
  • 1553-4014
OpenAlex
W2160215400
Cited by
317
References
0
FWCI
3.53
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Molecular Pathobiology of Gastrointestinal Stromal Sarcomas. https://app.cochat.ai/papers/10.1146/annurev.pathmechdis.3.121806.151538
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Corless, C. L., & Heinrich, M. C. (2008). Molecular Pathobiology of Gastrointestinal Stromal Sarcomas. Annual Review of Pathology: Mechanisms of Disease. https://doi.org/10.1146/annurev.pathmechdis.3.121806.151538

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.