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Identifying and targeting collateral lethal vulnerabilities in cancers

识别并针对癌症的附带致命弱点

基本信息

批准号：
10563469
负责人：
RONALD ANTHONY DEPINHO
金额：
$ 96.7万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
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：
2023-04-01 至 2028-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10563469
关键词：
1p36 ARID1A gene Adult Alleles Apoptotic Biochemical Biological Biological Assay CDKN2A gene CRISPR/Cas technology Cancer cell line Cell Culture Techniques Cell Line Cell Proliferation Cell Survival Cell division Cell physiology Cells Chromosomes Cleavage Stimulation Factor Clustered Regularly Interspaced Short Palindromic Repeats Common Neoplasm Complement Complex Computer Analysis Computing Methodologies Coupled Cultured Cells Data Defect Dependence Diphosphates Endoplasmic Reticulum Engineering Enzymes Event Extinction Face Gene Deletion Gene Family Genes Genetic Genetic Transcription Genome Genomics Goals Housekeeping Human Individual Knock-out Lactate Dehydrogenase Ligase MADH4 gene Malignant Neoplasms Mammalian Cell Maps Measurement Measures Mediating Metabolism Methods Mitochondria Mitosis Mitotic spindle Modeling Monitor Mus NF1 gene NF1 tumor suppressor Normal Cell Nuclear Envelope Organoids Orthologous Gene PTEN gene Patients Phosphatidylserine Synthase Phosphatidylserines Poly A Polyadenylation Probability Proteins Proteomics Pyruvate RB1 gene Reiterated Genes Ribose-Phosphate Pyrophosphokinase Sample Size Signal Transduction Survival Analysis System Systemic Therapy TP53 gene Toxic effect Tumor Suppressor Genes Tumor Suppressor Proteins U1 small nuclear RNA Validation cancer cell cancer therapy cancer type candidate validation deep learning design drug discovery enzyme activity gain of function genome-wide genomic locus improved outcome in vivo live cell imaging mRNA Precursor malic enzyme member metabolomics model organism mutant new therapeutic target nucleotide metabolism overexpression paralogous gene pharmacologic public database receptor expression research study response screening small hairpin RNA targeted treatment tool transcriptomics tumor validation studies vector whole genome

项目摘要

Identifying and targeting collateral lethal vulnerabilities in cancers Abstract/Summary Genomic deletions targeting major tumor suppressor genes frequently include adjacent passenger genes, encoding cell essential housekeeping functions. These cancer cells survive due to co-expressing functionally redundant paralogs residing in non-deleted regions of the genome. As such, these “collateral deletions” in tumor suppressor loci can confer cancer cell-specific vulnerabilities through targeted extinction of the remaining paralog. Our “collateral lethality” concept was first demonstrated in GBM with deletion of the 1p36 tumor suppressor locus encompassing ENO1, resulting in profound sensitivity to ENO2 depletion or pharmacologic inhibition (Muller et al. 2012). Subsequently, we demonstrated that deletion of mitochondrial malic enzyme 2 (ME2) in the SMAD4 locus engendered lethality upon shRNA-mediated depletion of the remaining mitochondrial malic enzyme activity encoded by the ME3 paralog (Dey et al. 2017). To systematically and comprehensively identify collateral lethal targets in cancer, we first analyzed the Broad Institute’s Cancer Dependency Map (DepMap), a publicly accessible database hosting essentiality scores of 17386 genes from a pooled genome- scale CRISPR knockout study conducted in 1054 cancer cell lines of diverse lineages (Dempster et al. 2019; Ghandi et al. 2019). The computational efforts yielded multiple collateral lethal candidate pairs including REEP3/4, PTDSS1/2, INTS6/INTS6L, PRPS1/2, LDHA/B, and CSTF2/CSTF2T via a two-class comparison method that regressed cell line sensitivity vectors against whole-genome CCLE expression and copy number data to predict paralog-depletion based sensitivity. While computational analysis of DepMap data can identify some candidate collateral lethal pairs, small sample sizes for many collateral deletions have stymied robust conclusions. Building on these computational methods, here we will apply the CRISPR/Cas12a polygenic knockout platform to systematically identify collateral lethal pairs anchored in deletion events targeting common tumor suppressor gene loci such as TP53, CDKN2A/B, ARID1A, PTEN, SMAD4, RB1 and NF1 across cancer types. This conceptual and experimental framework, coupled with a cell/organoid/tumor validation platform, seeks to identify and stringently validate collateral lethal target sets that can then be channeled into a drug discovery pipeline with the goal of expanding precision cancer treatments.

确定和瞄准癌症的附带致命弱点摘要/概要靶向主要肿瘤抑制基因的基因组缺失通常包括邻近的过客基因，编码单元基本的内务管理功能。这些癌细胞由于共表达功能性存在于基因组的非缺失区域中的冗余旁系同源物。因此，肿瘤中的这些“侧支缺失” 抑制基因座可以通过靶向消除癌细胞的剩余基因， paradise.我们的“侧支致死”概念首先在1 p36肿瘤缺失的GBM中得到证实，包含ENO 1的抑制基因座，导致对ENO 2耗尽或药理学的高度敏感性抑制（Muller等人，2012）。随后，我们证明了线粒体苹果酸酶2的缺失， (ME2)在SMAD 4基因座中，在shRNA介导的剩余线粒体消耗后产生致死性，由ME 3蛋白编码的苹果酸酶活性（Dey et al. 2017）。系统全面地为了确定癌症中的附带致死靶点，我们首先分析了布罗德研究所的癌症相关性地图，（DepMap），一个公开访问的数据库，托管来自汇总基因组的17386个基因的必要性评分- 在1054种不同谱系的癌细胞系中进行的大规模CRISPR敲除研究（Dempster et al. 2019; Ghandi等人，2019年）。计算工作产生了多个附带致命的候选对，包括 REEP 3/4、PTDSS 1/2、INTS 6/INTS 6L、PRPS 1/2、LDHA/B和CSTF 2/CSTF 2 T（通过两类比较）针对全基因组CCLE表达和拷贝数回归细胞系敏感性载体的方法数据来预测基于旁系同源物耗尽的灵敏度。虽然DepMap数据的计算分析可以识别一些候选的侧系致死对，许多侧系缺失的小样本量阻碍了鲁棒性结论.在这些计算方法的基础上，在这里我们将应用CRISPR/Cas 12 a多基因敲除平台，以系统地鉴定锚定在缺失事件中的附带致死对，肿瘤抑制基因位点如TP 53、CDKN 2 A/B、ARID 1A、PTEN、SMAD 4、RB 1和NF 1在癌症中的分布类型这个概念和实验框架，加上细胞/类器官/肿瘤验证平台，旨在识别并严格验证可用于药物的附带致死靶点集探索管道，目标是扩大精确的癌症治疗。