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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.

摘要