【佳学基因检测】相互排斥的功能丧失的多组学测量对基因检测结果确定与校对的作用

品牌基因检测在哪里做时机窗口

从开题评估及基因实验室人员知识更新项目中知道《BMC Genomics》在. 2016 Jan 19;17:65.发表了一篇题目为《相互排斥的功能丧失的多组学测量丰富了候选合成致死基因对》肿瘤靶向药物治疗基因检测临床研究文章。该研究由Mark Wappett, Austin Dulak, Zheng Rong Yang, Abdullatif Al-Watban, James R Bradford, Jonathan R Dry等完成。促进了癌细胞基因组突变的结构与组成的了解，进一步强调了基因信息检测与分析对于癌症治疗及基因检测结果分析的重要性。

癌症靶向药物及正确治疗临床研究内容关键词：

癌症,基因检测,多组学,相互排斥,基因突变

肿瘤靶向治疗基因检测临床应用结果

基因解码基因检测的研究介绍：鉴定癌细胞中的合成致死相互作用可以提供有希望的新治疗靶点。大规模的功能基因组筛查为测试大量癌症合成致死假设提供了机会。在分子确定的癌细胞系中富集候选合成致死靶标的基因解码基因检测的研究方法可以指导检测筛选工作的有效设计。合成致死基因对的一个伙伴的丧失会产生对另一个伙伴的依赖，因此合成致死基因对永远不会同时出现功能丧失。基因解码基因检测开发了一种计算基因解码基因检测的研究方法来挖掘大型多组癌症数据集并识别具有互斥功能丧失的基因对。由于功能丧失可能并不总是遗传性的，基因解码基因检测通过使用新算法 BiSEp 定义的双峰来寻找有害突变、基因缺失和/或 mRNA 表达丧失，从而优化基因检测。基因解码基因检测的研究结果：将此工具包应用于肿瘤细胞系和患者数据，基因解码基因检测实现了经过实验验证的肿瘤抑制基因和合成致死基因配对的统计学显着富集。值得注意的是，不依赖遗传损失揭示了许多已知的合成致死关系，否则会被遗漏，从而导致对仅遗传预测的显着改进。基因解码基因检测继续围绕一些新的候选合成致死基因对建立生物学原理，这些基因对在已发表的癌细胞系 shRNA 筛选中具有依赖性。基因解码基因检测的研究结论：这项工作引入了一种多组学基因解码基因检测的研究方法来定义基因功能丧失，并丰富细胞系中的候选合成致死基因对可通过功能筛选进行测试。在此过程中，基因解码基因检测提供了额外的资源来生成新的癌症药物靶点和组合假设。

肿瘤发生与反复转移国际数据库描述：

Background: Identification of synthetic lethal interactions in cancer cells could offer promising new therapeutic targets. Large-scale functional genomic screening presents an opportunity to test large numbers of cancer synthetic lethal hypotheses. Methods enriching for candidate synthetic lethal targets in molecularly defined cancer cell lines can steer effective design of screening efforts. Loss of one partner of a synthetic lethal gene pair creates a dependency on the other, thus synthetic lethal gene pairs should never show simultaneous loss-of-function. We have developed a computational approach to mine large multi-omic cancer data sets and identify gene pairs with mutually exclusive loss-of-function. Since loss-of-function may not always be genetic, we look for deleterious mutations, gene deletion and/or loss of mRNA expression by bimodality defined with a novel algorithm BiSEp.Results: Applying this toolkit to both tumour cell line and patient data, we achieve statistically significant enrichment for experimentally validated tumour suppressor genes and synthetic lethal gene pairings. Notably non-reliance on genetic loss reveals a number of known synthetic lethal relationships otherwise missed, resulting in marked improvement over genetic-only predictions. We go on to establish biological rationale surrounding a number of novel candidate synthetic lethal gene pairs with demonstrated dependencies in published cancer cell line shRNA screens.Conclusions: This work introduces a multi-omic approach to define gene loss-of-function, and enrich for candidate synthetic lethal gene pairs in cell lines testable through functional screens. In doing so, we offer an additional resource to generate new cancer drug target and combination hypotheses.