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

使用 PanCancer 人类原发性肿瘤数据鉴定癌症种系突变的合成致死伴侣

• 批准号: 10118001
• 负责人: Yihui Shi
• 金额: $ 18.27万
• 依托单位: CALIFORNIA NORTHSTATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-11 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10118001
• 关键词: Identification; Synthetic; Lethal; Partners; Cancer

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. In synthetic lethal interactions, an alteration in one gene leads to dependency on a second gene. Neither alteration by itself is essential for survival, but together these alterations lead to cancer cell death. 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. Two specific aims are proposed: In Aim 1, we will develop a computational method based on mining large-scale genomic and transcriptomic datasets to identify SL partners of germline mutations in cancer. This method will be applied to genomic and transcriptomic datasets from The Cancer Genome Atlas (TCGA), 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.

项目摘要 我们提出了一种新的计算方法来确定生殖系突变癌症的治疗靶点 使用来自泛癌原发性人类肿瘤的种系突变和体细胞改变的综合分析 数据这种方法将用于确定乳腺癌中生殖系突变的新治疗靶点， BRCA 1、BRCA 2和PALB 2。生殖系突变增加癌症风险的基因被称为 癌症易感基因（CPG）。许多CPG是已知的，DNA的最新进展 测序有望发现更多的CPG。考虑到生殖细胞癌患者患癌风险增加， CPG突变，迫切需要确定新的治疗和化学预防策略， 这些突变。大多数这些突变是功能丧失的改变，不能直接用药。合成 致死性为鉴定这些突变的新治疗靶点的方法提供了基础。合成 致命的相互作用，一个基因的改变导致对第二个基因的依赖。也不是改变本身 是生存所必需的，但这些改变共同导致癌细胞死亡。目前，合成致死（SL） 合作伙伴是使用大规模的功能筛选来确定的，这受到人为的负面影响。 细胞培养条件和在正确的癌症背景下具有特定突变的细胞系的有限可用性。 我们建议挖掘患者的肿瘤数据库，以确定生殖系突变的SL合作伙伴。我们的假设是 生殖系突变的SL配偶体将被选择性扩增或从不缺失，并且在细胞中也过表达。 携带突变的原发性肿瘤样本。提出了两个具体目标：在目标1中，我们将制定一个 基于挖掘大规模基因组和转录组数据集以识别SL伙伴的计算方法 癌症的生殖细胞突变。该方法将应用于来自The 癌症基因组图谱（TCGA）和来自GTEx（基因型-组织）的正常组织的基因表达数据 表达）以鉴定三种公知的乳腺癌CPG，BRCA 1， BRCA 2和PALB 2。在目标2中，我们将通过实验验证每个种系突变的SL伴侣 目标1分两步确定。首先，在目标2a中，我们将使用遗传算法验证每个突变的SL伴侣。 在体外用可诱导的shRNA在等基因乳腺癌细胞系（+/-突变）中敲低SL配偶体。接下来， 在目标2b中，我们将在人乳腺癌细胞系中验证前三种突变-SL伴侣组合 使用遗传和药理学敲低在小鼠中进行异种移植。我们预计拟议的研究将确定 用于乳腺癌治疗和化学预防的新型药物靶点。长期目标是 开发新的系统方法，以确定潜在的靶向治疗方法， 癌症生殖细胞突变患者的化学预防。拟议的研究是对方案问题3的回应， 阐明具有生殖系突变的肿瘤如何响应基于遗传SL相互作用的靶向治疗 生殖细胞突变和体细胞改变之间的联系