Detecting the onset of genome heterogeneity in tumor at single cell resolution

以单细胞分辨率检测肿瘤中基因组异质性的发生

• 批准号: 8754910
• 负责人: Chenghang Zong
• 金额: $ 237.45万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8754910
• 关键词: Basic Science; Cells; Clinical; Complex; Detection; Development; Early Intervention; Evolution; Genome; Genomics; Goals; Heterogeneity; Malignant Neoplasms; Methods; Microscopic; Neoplasms; Nucleotides; Research; Resolution; Sampling; Scheme; Solid; Technology; Tissues; Variant; clinical practice; genome sequencing; method development; public health relevance; success; therapeutic development; tumor

DESCRIPTION (provided by applicant): With the emerging evidence of complex tumor heterogeneity, it is critical for us to profile and understand the complex evolution in tumor development. To do so, we desire to characterize the genome heterogeneity and complex evolution at microscopic resolution. Here we propose an exact linear amplification scheme for single cell whole-genome amplification, which will allow us to detect single nucleotide variations (SNVs) with the high accuracy comparable to the bulk sequencing. With this cutting-edge method development, we will be able to profile tumor heterogeneity at single cell resolution with unprecedented accuracy of SNV detection. Our immediate goal in this proposal is to apply this method to discover the onset of heterogeneity at low-grade of neoplasm and the sequential development of genome heterogeneity at the following higher grades of neoplasm. Overall, our goal is to develop a suite of highly promising single cell analytical technologies to gain an understanding of genomic variations in solid cancers. Success of the project will result in an integrated platform that will serve to overcome prevailing impediments in studying clinical samples. The research is expected to have a broad impact on basic research, clinical practice, and the development of therapeutic treatments for early intervention.

描述（由申请人提供）：随着复杂肿瘤异质性证据的出现，描述和理解肿瘤发展中的复杂演变对我们至关重要。要做到这一点，我们希望在微观分辨率上表征基因组异质性和复杂的进化。在这里，我们提出了一个精确的线性扩增方案的单细胞全基因组扩增，这将使我们能够检测单核苷酸变异（SNV）的高准确度相媲美的批量测序。通过这种尖端的方法开发，我们将能够以单细胞分辨率分析肿瘤异质性，并具有前所未有的SNV检测准确性。我们在这项建议中的直接目标是应用这种方法来发现低级别肿瘤的异质性的发生和以下较高级别肿瘤的基因组异质性的顺序发展。总的来说，我们的目标是开发一套非常有前途的单细胞分析技术，以了解实体癌中的基因组变异。该项目的成功将产生一个综合平台，有助于克服研究临床样本的普遍障碍。该研究预计将对基础研究，临床实践和早期干预治疗方法的发展产生广泛影响。

项目成果

Single-cell Damagenome Profiling by Linear Copying and Splitting based Whole Genome Amplification (LCS-WGA)

基于线性复制和分裂的全基因组扩增 (LCS-WGA) 进行单细胞损伤组分析

• DOI: 10.21769/bioprotoc.4357
• 发表时间: 2022
• 期刊: BIO-PROTOCOL
• 影响因子: 0.8
• 作者: Niu, Yichi;Zhu, Qiangyuan;Zong, Chenghang
• 通讯作者: Zong, Chenghang

Single-cell damagenome profiling unveils vulnerable genes and functional pathways in human genome toward DNA damage

• DOI: 10.1126/sciadv.abf3329
• 发表时间: 2021-07
• 期刊: Science Advances
• 影响因子: 13.6
• 作者: Qiangyuan Zhu;Yichi Niu;Michael C. Gundry;Chenghang Zong