Krasnitz Alexander, Kendall Jude, Alexander Joan, Levy Dan, Wigler Michael
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
Trends Mol Med. 2017 Jul;23(7):594-603. doi: 10.1016/j.molmed.2017.05.005. Epub 2017 Jun 3.
Here, we explore the potential of single-cell genomic analysis in blood for early detection of cancer; we consider a method that screens the presence of recurrent patterns of copy number (CN) alterations using sparse single-cell sequencing. We argue for feasibility, based on in silico analysis of existing single-cell data and cancer CN profiles. Sampling procedures from existing diploid single cells can render data for a cell with any given profile. Sampling from multiple published tumor profiles can interrogate cancer clonality via an algorithm that tests the multiplicity of close pairwise similarities among single-cell cancer genomes. The majority of common solid cancers would be detectable in this manner. As any early detection method must be verifiable and actionable, we describe how further analysis of suspect cells can aid in determining risk and anatomic origin. Future affordability rests on currently available procedures for tumor cell enrichment and inexpensive methods for single-cell analysis.
在此,我们探索血液中单细胞基因组分析在癌症早期检测方面的潜力;我们考虑一种使用稀疏单细胞测序来筛查拷贝数(CN)改变复发模式存在情况的方法。基于对现有单细胞数据和癌症CN图谱的计算机模拟分析,我们论证了该方法的可行性。从现有的二倍体单细胞进行采样程序可为具有任何给定图谱的细胞生成数据。从多个已发表的肿瘤图谱中采样可通过一种算法来探究癌症克隆性,该算法测试单细胞癌症基因组之间紧密成对相似性的多重性。大多数常见实体癌都可通过这种方式检测到。由于任何早期检测方法都必须是可验证且可采取行动的,我们描述了对可疑细胞的进一步分析如何有助于确定风险和解剖学起源。未来的可承受性取决于当前可用的肿瘤细胞富集程序和廉价的单细胞分析方法。