Single cell modeling of cancer mutations

癌症突变的单细胞建模

基本信息

批准号：
10612689
负责人：
Hanlee P Ji
金额：
$ 37.53万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-06-01 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10612689
关键词：
Address Alternative Splicing Amino Acid Substitution Base Sequence Biological Biological Sciences CRISPR/Cas technology Cancer Gene Mutation Cancer Model Categories Cell Line Cell model Cells Cellular Assay Clustered Regularly Interspaced Short Palindromic Repeats Code Colorectal Cancer Complementary DNA DNA Data Data Set Detection Engineering Exons Experimental Models Gene Expression Gene Expression Profile Gene Targeting Genes Genetic Genetic Code Genetic Transcription Genomics Genotype Guide RNA Individual Introns Length Link Malignant Neoplasms Messenger RNA Methods Modeling Mutation Normal Cell Oncogenes Organoids Pattern Point Mutation Process Protein Isoforms RNA Sequences RNA Splicing Reporting Resolution Somatic Mutation Technology Testing Transcript base base editing base editor cancer cell cancer type cellular engineering data integration design experimental study gene function genome editing genomic platform in silico mRNA sequencing malignant stomach neoplasm mutation screening nanopore novel novel strategies nuclease parallelization screening single cell sequencing single molecule single-cell RNA sequencing technological innovation tissue culture tool transcriptome

项目摘要

ABSTRACT Hundreds of thousands of mutations have been identified in cancer. However, the vast majority of cancer mutations lack functional biological characterization. Therefore, very little is known about their impact on gene function beyond in silico predictions. Developing experimental models to study the biological consequences of these mutations is a daunting challenge. We developed a technology called transcript-informed single cell CRISPR sequencing (TISCC-seq) that provides modeling of cancer mutations at single cell resolution. CRISPR engineering introduces cancer gene mutations into cells. Single-cell RNA sequencing (scRNA-seq) is a power tool for evaluating the genomic features of cancer. By combining these two approaches TISCC-seq has the potential for dramatic increases in parallelization and scalability of experimental cancer models. We use DNA base editors to introduce specific cancer mutations into target genes among individual cells. Single molecule nanopore sequencing of the cDNA target directly identifies the mutation in each cell. By integrating single cell long and short read sequence data, each cell’s newly introduced mutation is matched to the same cell’s gene expression data. We will develop TISCC-seq as a new single cell genomic platform for engineering cancer mutations into cell lines and primary tissue cultures. Single base mutations are the most commonly reported type of cancer genetic alteration. For Aim 1, we will develop TISCC-seq for highly multiplexed functional screening of substitution mutations at single cell resolution while matching the mutation genotype to the same single cell’s transcriptome. We will identify reported cancer mutations with known biological effects and others which are not characterized identified in colorectal or gastric cancer. Next, we will determine which of these mutations can be engineered using base editing methods. Then, we will deliver base editors and guide RNAs to engineer up to 500 substitution mutations across different cell lines and organoids. Post-editing, the cells will undergo scRNA-seq with both short and long-read platform. These data sets will be integrated to provide a single readout where the single cell mutation is matched to the corresponding cell’s gene expression. Alternative splicing is increasingly recognized as an important feature of cancer. Some cis-based cancer mutations occur in exon-intron junctions that lead to alternative splicing of mRNAs. For Aim 2, we will develop TISCC-seq as a method to evaluate this category of mutations. First, we will identify a set of 100 cancer genes that have cis-based mutations at exon-intron junctions as reported in colorectal or gastric cancer. We will increase the scalability of this process such that at least 500 of this class of mutations can be studied in parallel using an integrated long and short read sequencing. These mutations will be introduced across different cell lines and organoids. Overall, we will develop a new CRISPR genomic technology for highly multiplexed modeling of cancer mutations at single cell resolution and studying their biological effects.

抽象的癌症中已发现数十万种突变。因此，人们对突变对基因的影响知之甚少。开发实验模型来研究其生物学后果。这些突变是一项艰巨的挑战，我们开发了一种称为转录信息单细胞的技术。 CRISPR 测序 (TISCC-seq) 可提供单细胞 CRISPR 癌症突变建模。工程将癌症基因突变引入细胞中。单细胞 RNA 测序 (scRNA-seq) 是一种力量。通过结合这两种方法，TISCC-seq 具有评估癌症基因组特征的工具。我们使用 DNA 来显着提高实验癌症模型的并行化和可扩展性。碱基编辑器将特定的癌症突变引入单个细胞的靶基因中。 cDNA 靶标的纳米孔测序通过整合单细胞直接识别每个细胞中的突变。长读和短读序列数据，每个细胞新引入的突变与同一细胞的基因相匹配我们将开发 TISCC-seq 作为工程癌症的新单细胞基因组平台。细胞系和原代组织培养物的突变。单碱基突变是最常见的癌症遗传改变类型，对于目标 1，我们将进行介绍。开发 TISCC-seq，用于单细胞分辨率的替代突变的高度多重功能筛选同时将突变基因型与同一单细胞的转录组进行匹配，我们将识别报告的癌症。具有已知生物效应的突变和其他在结直肠或胃中未鉴定的突变接下来，我们将确定哪些突变可以使用碱基编辑方法进行改造。我们将提供碱基编辑器并引导 RNA 在不同细胞中设计多达 500 个替换突变编辑后，细胞将使用短读长和长读长平台进行 scRNA 测序。这些数据集将被整合以提供单个读数，其中单细胞突变与相应细胞的基因表达。选择性剪接越来越被认为是一些顺式癌症的重要特征。突变发生在外显子-内含子连接处，导致 mRNA 的选择性剪接，我们将开发目标 2。 TISCC-seq 作为评估此类突变的方法首先，我们将确定一组 100 个癌症基因。正如在结直肠癌或胃癌中报道的那样，在外显子-内含子连接处具有基于顺式的突变。提高该过程的可扩展性，以便可以并行研究至少 500 个此类突变使用集成的长读和短读测序，这些突变将被引入到不同的细胞中。总体而言，我们将开发一种新的 CRISPR 基因组技术，用于高度多重建模。在单细胞分辨率下研究癌症突变并研究其生物学效应。