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Sample type bias in the analysis of cancer genomes.

机译:癌症基因组分析中的样品类型偏倚。

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摘要

There is widespread agreement that cancer gene discovery requires high-quality tumor samples. However, whether primary tumors or cultured samples are superior for cancer genomics has been a longstanding subject of debate. This debate has recently become more important because federally funded cancer genomics has been centralized under The Cancer Genome Atlas, which has chosen to focus exclusively on primary tumors. Here, we provide a data-driven "perspective" on the effect of sample type selection on cancer genomics research. We show that, in the case of glioblastoma multiforme, primary tumors and xenografts are best for the identification of amplifications, whereas xenografts and cell lines are superior for the identification of homozygous deletions. We also note that many of the most important oncogenes and tumor suppressor genes have been discovered through the use of cell lines and xenografts, and highlight the lack of published evidence supporting the dogma that ex vivo culture generates artifactual genetic lesions. Based on this analysis, we suggest that cancer genomics projects such as The Cancer Genome Atlas should include a variety of sample types such as xenografts and cell lines in their integrated genomic analysis of cancer.
机译:人们普遍同意,癌症基因的发现需要高质量的肿瘤样本。然而,对于肿瘤基因组而言,原发肿瘤或培养样品是否优越一直是争论的话题。由于联邦政府资助的癌症基因组学已集中在《癌症基因组图谱》下,该争论已变得更加重要,该癌症基因组图谱已选择仅专注于原发肿瘤。在这里,我们提供了一种数据驱动的“观点”,即样本类型选择对癌症基因组学研究的影响。我们显示,在多形性胶质母细胞瘤的情况下,原发性肿瘤和异种移植最适合鉴定扩增,而异种移植和细胞系则更适合鉴定纯合缺失。我们还注意到,已经通过使用细胞系和异种移植物发现了许多最重要的癌基因和抑癌基因,并突出显示了缺乏支持离体培养产生人为遗传损伤的教条的公开证据。基于此分析,我们建议癌症基因组计划(例如The Cancer Genome Atlas)应在其综合癌症基因组分析中包括各种样本类型(例如异种移植物和细胞系)。

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