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Exome sequence analysis of Kaposiform hemangioendothelioma: identification of putative driver mutations*

Overview of attention for article published in Anais Brasileiros de Dermatologia, January 2016
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Title
Exome sequence analysis of Kaposiform hemangioendothelioma: identification of putative driver mutations*
Published in
Anais Brasileiros de Dermatologia, January 2016
DOI 10.1590/abd1806-4841.20165026
Pubmed ID
Authors

Sho Egashira, Masatoshi Jinnin, Miho Harada, Shinichi Masuguchi, Satoshi Fukushima, Hironobu Ihn

Abstract

Kaposiform hemangioendothelioma is a rare, intermediate, malignant tumor. The tumor's etiology remains unknown and there are no specific treatments. In this study, we performed exome sequencing using DNA from a Kaposiform hemangioendothelioma patient, and found putative candidates for the responsible mutations. The genomic DNA for exome sequencing was obtained from the tumor tissue and matched normal tissue from the same individual. Exome sequencing was performed on HiSeq2000 sequencer platform. Among oncogenes, germline missense single nucleotide variants were observed in the TP53 and APC genes in both the tumor and normal tissue. As tumor-specific somatic mutations, we identified 81 candidate genes, including 4 nonsense changes, 68 missense changes and 9 insertions/deletions. The mutations in ITGB2, IL-32 and DIDO1 were included in them. This is a pilot study, and future analysis with more patients is needed to clarify: the detailed pathogenesis of this tumor, the novel diagnostic methods by detecting specific mutations, and the new therapeutic strategies targeting the mutation.

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Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 17%
Researcher 2 17%
Unspecified 1 8%
Student > Master 1 8%
Student > Ph. D. Student 1 8%
Other 2 17%
Unknown 3 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 33%
Medicine and Dentistry 3 25%
Agricultural and Biological Sciences 1 8%
Unspecified 1 8%
Unknown 3 25%