Related Experiment Video
Updated: Mar 14, 2026
Identification of OTX1 and OTX2 As Two Possible Molecular Markers for Sinonasal Carcinomas and Olfactory Neuroblastomas
Published on: February 28, 2019
Mutant KIT as imatinib-sensitive target in metastatic sinonasal carcinoma
S M Dieter1,2, C Heining1,2,3, A Agaimy4
1Department of Translational Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany.
Background:
Sinonasal carcinomas (SNCs) comprise various rare tumor types that are characterized by marked histologic diversity and largely unknown molecular profiles, yet share an overall poor prognosis owing to an aggressive clinical course and frequent late-stage diagnosis. The lack of effective systemic therapies for locally advanced or metastatic SNC poses a major challenge to therapeutic decision making for individual patients. We here aimed to identify actionable genetic alterations in a patient with metastatic SNC whose tumor, despite all diagnostic efforts, could not be assigned to any known SNC category and was refractory to multimodal therapy.
Patients And Methods:
We used whole-exome and transcriptome sequencing to identify a KIT exon 11 mutation (c.1733_1735del, p.D579del) as potentially druggable target in this patient and carried out cancer hotspot panel sequencing to detect secondary resistance-conferring mutations in KIT. Furthermore, as a step towards clinical exploitation of the recently described signatures of mutational processes in cancer genomes, we established and applied a novel bioinformatics algorithm that enables supervised analysis of the mutational catalogs of individual tumors.
Results:
Molecularly guided treatment with imatinib in analogy to the management of gastrointestinal stromal tumor (GIST) resulted in a dramatic and durable response with remission of nearly all tumor manifestations, indicating a dominant driver function of mutant KIT in this tumor. KIT dependency was further validated by a secondary KIT exon 17 mutation (c.2459_2462delATTCinsG, p.D820_S821delinsG) that was detected upon tumor progression after 10 months of imatinib treatment and provided a rationale for salvage therapy with regorafenib, which has activity against KIT exon 11/17 mutant GIST.
Conclusions:
These observations highlight the potential of unbiased genomic profiling for uncovering the vulnerabilities of individual malignancies, particularly in rare and unclassifiable tumors, and underscore that KIT exon 11 mutations represent tractable therapeutic targets across different histologies.
Insights
This study identified a KIT exon 11 mutation in a rare sinonasal carcinoma, leading to a dramatic response to imatinib therapy. This highlights KIT mutations as actionable targets in diverse cancers.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Sinonasal carcinomas (SNCs) are rare, histologically diverse tumors with poor prognosis and unknown molecular drivers.
- Metastatic SNC lacks effective systemic therapies, posing a significant clinical challenge.
- This study investigated a rare, unclassifiable metastatic SNC refractory to standard treatments.
Observation:
- Whole-exome and transcriptome sequencing identified a KIT exon 11 mutation (c.1733_1735del, p.D579del) in the patient's tumor.
- A novel bioinformatics algorithm was developed for analyzing tumor mutational catalogs.
- Secondary KIT exon 17 mutations (c.2459_2462delATTCinsG, p.D820_S821delinsG) emerged upon progression.
Findings:
- Molecularly guided imatinib treatment, analogous to gastrointestinal stromal tumor (GIST) therapy, yielded a dramatic and durable response.
- The patient achieved remission, indicating the KIT exon 11 mutation as a dominant driver.
- Salvage therapy with regorafenib was effective against the secondary KIT mutations.
Implications:
- Unbiased genomic profiling can reveal vulnerabilities in rare and unclassifiable cancers.
- KIT exon 11 mutations are druggable therapeutic targets across various cancer types.
- Personalized medicine approaches utilizing genomic data can improve outcomes for patients with rare malignancies.
