儿童癌症的遗传时代:高风险患者的鉴定和种系测序方法

IF 1 4区 生物学 Q4 GENETICS & HEREDITY
Oscar Alonso-Luna, Gabriela E Mercado-Celis, Jorge Melendez-Zajgla, Marta Zapata-Tarres, Elvia Mendoza-Caamal
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引用次数: 0

摘要

儿童癌症是5-14岁儿童因疾病死亡的一个主要原因,对此没有预防战略。由于早期诊断和短时间暴露于环境因素,越来越多的证据表明,儿童癌症可能与易感癌症基因的种系改变密切相关,但其频率和分布在很大程度上是未知的。已经做出了一些努力来开发工具,以识别可能从基因检测中受益的癌症风险增加的儿童,但它们的验证和大规模应用是必要的。儿童癌症的遗传基础研究正在进行中,其中已经使用了几种方法来识别与癌症易感性相关的遗传变异。在本文中,我们讨论了最新的努力,策略,分子机制和临床意义的生殖系易感基因改变和儿童癌症风险变异的特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The genetic era of childhood cancer: Identification of high-risk patients and germline sequencing approaches

The genetic era of childhood cancer: Identification of high-risk patients and germline sequencing approaches

Childhood cancer is a leading cause of death by disease in children ages 5–14, for which there are no preventive strategies. Due to early-age of diagnosis and short period of exposure to environmental factors, increasing evidence suggests childhood cancer could have strong association with germline alterations in predisposition cancer genes but, their frequency and distribution are largely unknown. Several efforts have been made to develop tools to identify children with increased risk of cancer who may benefit from genetic testing but their validation and application on a large scale is necessary. Research on genetic bases of childhood cancer is ongoing, in which several approaches for the identification of genetic variants related to cancer predisposition have been used. In this paper, we discuss the updated efforts, strategies, molecular mechanisms and clinical implications for germline predisposition gene alterations and the characterization of risk variants in childhood cancer.

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来源期刊
Annals of Human Genetics
Annals of Human Genetics 生物-遗传学
CiteScore
4.20
自引率
0.00%
发文量
34
审稿时长
3 months
期刊介绍: Annals of Human Genetics publishes material directly concerned with human genetics or the application of scientific principles and techniques to any aspect of human inheritance. Papers that describe work on other species that may be relevant to human genetics will also be considered. Mathematical models should include examples of application to data where possible. Authors are welcome to submit Supporting Information, such as data sets or additional figures or tables, that will not be published in the print edition of the journal, but which will be viewable via the online edition and stored on the website.
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