首页> 外文会议>IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology >Modelling the Effects of Genetic Changes in Tumour Progression
【24h】

Modelling the Effects of Genetic Changes in Tumour Progression

机译:建模遗传变化对肿瘤进展的影响

获取原文
获取外文期刊封面目录资料

摘要

Tumours can be considered a set of cells that accumulate genetic and epigenetic alterations. According to the Multi-stage Hit theory, the transformation of a normal into a tumour cell involves a number of limiting events that occur in a number of discrete stages (driver mutations). However, not all mutations that occur in the cell are directly involved in the development of cancer and some probably do not contribute in any way (passenger mutations). Moreover, the process of tumour evolution is punctuated by selection of advantageous mutations and clonal expansions. Actually, it is not known how many limiting-events, i.e., how many driver mutations are necessary or sufficient to promote a carcinogenic process. This conjecture should be explored and tested - mathematically and statistically, with the availability of genomic data on databanks. In this work, we explore the model proposed by Bozic and collaborators (2010) that describes the evolution of the tumour according to a Galton-Watson process. Besides, the model gives the relation between the numbers of passenger mutations giving a specific number of driver mutations. We intend to explore some of the model parameters and test some premises about the number of drive mutations and selective advantage, comparing the simulation results with genomic data from colorectal cancer patients. The genomic data was obtained from the DBMutation (http://www.bioinformatics-brazil.org/dbmutation/), a comprehensive database for genomic mutations in cancer. We expect that correlations between driver mutations and the time evolution of tumour process will facilitate the interpretation of genomic information, to make them useful and applicable to clinical oncology.
机译:肿瘤可被认为是一组积累遗传和表观遗传改变的细胞。根据多阶段的击中理论,常规进入肿瘤细胞的转化涉及许多在多个离散阶段(驱动突变)中发生的限制事件。然而,并非细胞中发生的所有发生的突变都直接参与癌症的发展,有些可能不会以任何方式贡献(乘客突变)。此外,通过选择有利的突变和克隆膨胀,肿瘤进化的过程被打断。实际上,尚不知道有多少限制性事件,即,需要多少驾驶员突变或足以促进致癌过程。该猜想应在数学和统计上进行探索和测试,具有关于数据库的基因组数据的可用性。在这项工作中,我们探索了Bozic和合作者(2010)所提出的模型,它根据Galton-Watson工艺描述肿瘤的演变。此外,该模型给出了给出特定数量的驾驶员突变的乘客突变数之间的关系。我们打算探索一些模型参数,并测试一些关于驱动突变数量和选择性优势的场所,并将模拟结果与来自结肠直肠癌患者的基因组数据进行比较。基因组数据是从dbdution(http://www.bioinformatics-brazil.org/dbmmutigation/),是癌症中基因组突变的综合数据库。我们预计驾驶员突变与肿瘤过程的时间演变之间的相关性将有助于解释基因组信息,使其有用和适用于临床肿瘤学。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号