叙利亚GIST患者KIT近膜结构域突变的生物信息学分析:拼图完成。

Nour Pharaon, Wafa Habbal, Fawza Monem
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引用次数: 0

摘要

背景:大量检测到的体细胞KIT突变凸显了在相关医学文献中几乎不存在的计算机分析的必要性。本研究的目的是报道一组叙利亚GIST患者中编码KIT基因近膜(JM)结构域的外显子11的突变谱分析。方法:从病理档案中检索2006 - 2016年收集的48例经福尔马林固定石蜡包埋的GIST组织样本,通过DNA测序分析KIT外显子11突变。使用几种生物信息学工具预测检测到的变异对结构/功能的影响。结果:在KIT基因的内含子10、外显子11和内含子11中检测到21个不同的变异,其中8个为新变异。48例GIST患者中有28例(58.3%)检测到KIT基因外显子11突变,并预测其具有致病性和促癌性。具体来说,60岁以上的年龄与缺失突变的负选择非常显著相关(p = .007),这一现象表明缺失的严重程度。结论:根据已发表的结构、实验和临床结果,六种生物信息学工具已被证明在预测检测到的KIT变异的影响方面是有效的。
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Bioinformatic analysis of KIT juxtamembrane domain mutations in Syrian GIST patients: jigsaw puzzle completed.

Background: The huge number of detected somatic KIT mutations highlights the necessity of in silico analyses that are almost absent in the relevant medical literature. The aim of this study is to report the mutation spectrum analysis of exon 11 encoding the juxtamembrane (JM) domain of the KIT gene in a group of Syrian GIST patients.

Methods: Forty-eight formalin-fixed paraffin-embedded GIST tissue samples, collected between 2006 and 2016, were retrieved from the pathological archives and analyzed for KIT exon 11 mutations by DNA sequencing. Structural/functional impact of detected variants was predicted using several bioinformatic tools.

Results: Twenty-one different variants have been detected in intron 10, exon 11, and intron 11 of the KIT gene, eight of which were novel changes. Mutations in exon 11 of the KIT gene were detected in 28 of 48 (58.3%) GIST patients and predicted to be pathogenic and cancer promoting. Specifically, age above 60 was very significantly associated with the negative selection of deletion mutations (p = .007), a phenomenon that points to deletion severity.

Conclusions: Six bioinformatic tools have proved efficient in predicting the impact of detected KIT variations in view of published structural, experimental, and clinical findings.

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来源期刊
CiteScore
3.50
自引率
0.00%
发文量
46
审稿时长
11 weeks
期刊介绍: As the official publication of the National Cancer Institute, Cairo University, the Journal of the Egyptian National Cancer Institute (JENCI) is an open access peer-reviewed journal that publishes on the latest innovations in oncology and thereby, providing academics and clinicians a leading research platform. JENCI welcomes submissions pertaining to all fields of basic, applied and clinical cancer research. Main topics of interest include: local and systemic anticancer therapy (with specific interest on applied cancer research from developing countries); experimental oncology; early cancer detection; randomized trials (including negatives ones); and key emerging fields of personalized medicine, such as molecular pathology, bioinformatics, and biotechnologies.
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