癌症生物样本之间共享变异的分析
Michael B Foote1, James Robert White1,2, Walid K Chatila3
1Division of Solid Tumor Oncology, Memorial Sloan Kettering, New York, New York.
概括
一个新的突变特征相似性 (MPS) 评分有助于确定一个患者的癌症样本是否相关或偶然. 这种工具有助于区分单个与多个癌症,并可以预测诊断变化.
科学领域:
- 基因组学就是基因组学.
- 癌症研究 癌症研究
- 生物信息学是一种生物信息学.
背景情况:
- 整合来自多个患者生物样本的突变数据对于跟踪癌症演变至关重要.
- 缺少一个标准化的框架存在,以区分由于共同的身份与巧合而导致的共享变体.
研究的目的:
- 开发一个计算框架来评估来自同一个体的生物样本之间的分子关系.
- 为了确定两个瘤是否具有独特的相关分子概况,建立信心估计.
主要方法:
- 在33种癌症类型中利用了来自癌症基因组图谱的8000个患者瘤.
- 使用大量突变同时发生率的背景数据库开发了突变特征相似性 (MPS) 评分.
- 应用了MPS算法来分析重复活检,单个患者多种癌症和质固体瘤对的瘤概况.
主要成果:
- 核酸特异性变异在1.3%的癌症类型不可知和10-13%的癌症类型特异性无关瘤中是共同的.
- 通过MPS方法,成功地将共享的变异语境化,以区分单个和多个不同的癌症.
- 在有不一致的临床病理学和分子发现的病例中,MPS预计未来的诊断变化占28%的病例.
结论:
- 一个新的共享变体框架,MPS评分,可以澄清生物样本之间的分子关系.
- 这种方法提供了有价值的见解与最小的输入,帮助癌症诊断和进化跟踪.
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