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Identification of Synthetic Lethal Partners of Cancer Germline Mutations using Pan-Cancer Human Primary Tumor Data

使用泛癌症人类原发性肿瘤数据鉴定癌症种系突变的合成致死伴侣

基本信息

批准号：
9814587
负责人：
Yihui Shi
金额：
$ 13.36万
依托单位：
SRI INTERNATIONAL
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-11 至 2019-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9814587
关键词：
BRCA1 gene BRCA2 gene Breast Cancer cell line CRISPR screen Cell Culture Techniques Cell Death Cell Line Cells Chemoprevention Chemopreventive Agent Clinic Computing Methodologies DNA DNA sequencing Data Data Analyses Data Set Databases Dependence Disease Gene Expression Gene Mutation Genes Genetic Genomics Genotype Genotype-Tissue Expression Project Germ Cells Germ-Line Mutation Human In Vitro Intercept Lead Malignant Neoplasms Methodology Methods Mining Mus Mutation Normal tissue morphology Oncogenes Operative Surgical Procedures Other Genetics Patients Pharmacology Prevention Prevention strategy Primary Neoplasm RNA interference screen Resistance Sampling Somatic Mutation Susceptibility Gene Testing The Cancer Genome Atlas Therapeutic Tissues Validation Work Xenograft procedure base cancer cell cancer genome cancer risk cancer type clinical practice computerized tools egg gene discovery genome sequencing improved in vivo inhibitor/antagonist knock-down leukemia loss of function mutation malignant breast neoplasm mutant neoplastic cell new therapeutic target novel novel therapeutics offspring overexpression prophylactic response small hairpin RNA sperm cell targeted treatment therapeutic target transcriptomics treatment strategy tumor

项目摘要

PROJECT SUMMARY We propose a novel computational approach to identify therapeutic targets for cancers with germline mutations using integrative analysis of germline mutations and somatic alterations from pan-cancer primary human tumor data. This method will be used to identify new therapeutic targets in breast cancer for germline mutations in BRCA1, BRCA2, and PALB2. Genes in which germline mutations confer increased risks of cancer are called cancer predisposition genes (CPGs). Numerous CPGs are already known, and recent advances in DNA sequencing hold the promise of more CPG discoveries. Given the increased cancer risk in people with germline CPG mutations, there is an urgent need to identify new therapeutic and chemopreventive strategies specific to these mutations. Most of these mutations are loss-of-function alterations and not directly druggable. Synthetic lethality provides the basis for an approach to identify new therapeutic targets for these mutations. Currently, synthetic lethal (SL) partners are identified using large-scale functional screens, which are negatively impacted by the artificiality of the cell culture conditions and limited availability of cell lines with the specific mutations in the right cancer context. We propose to mine patient tumor databases to identify SL partners of germline mutations. Our hypothesis is that SL partners of a germline mutation will be selectively amplified or never deleted and also over-expressed in primary tumor samples harboring the mutation. Previously, we developed a novel computational method (Mining Synthetic Lethals, MiSL) that analyzes primary tumor data to identify SL partners of somatic mutations in specific tumor types. We propose to develop a computational pipeline based on MiSL to identify genetic interactions with germline mutations. In Aim 1, we will develop a MiSL-based computational method to identify SL partners of germline mutations in cancer. This method will be applied to genomic and transcriptomic datasets from multiple large-scale cancer genome sequencing projects and gene expression data for normal tissues from GTEx (Genotype-Tissue Expression) to identify SL partners of germline mutations in three well-known breast cancer CPGs, BRCA1, BRCA2, and PALB2. In Aim 2, we will experimentally validate the SL partners for each germline mutation identified in Aim 1 in two steps. First, in Aim 2a, we will validate the SL partners for each mutation using genetic knockdown of the SL partner with inducible shRNA in isogenic breast cancer cell lines (+/-mutation) in vitro. Next, in Aim 2b, we will validate the top three mutation-SL partner combinations in human breast cancer cell line xenografts in mice using genetic and pharmacologic knockdown. We expect the proposed study will identify novel druggable targets for treatment and chemoprevention in breast cancer. The long-term objective is to develop a new systematic methodology to identify potential targeted therapies for treatment and chemoprevention of patients with germline mutations in cancer. The proposed study responds to PQ3 and will elucidate how tumors with germline mutations respond to targeted therapies based on genetic SL interactions between germline mutations and somatic alterations.

项目总结