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 我们提出了一种新型的计算方法，以鉴定具有种系突变的癌症的治疗靶标 利用泛 - 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。此方法将用于鉴定乳腺癌中新的治疗靶标的用于种系突变 BRCA1，BRCA2和PALB2。种系突变会增加癌症风险的基因称为 癌症易感基因（CPGS）。已经知道了许多CPG，并且DNA的最新进展 排序具有更多CPG发现的希望。鉴于种系的癌症风险增加 CPG突变，迫切需要确定特定于 这些突变。这些突变中的大多数是功能丧失的改变，而不是直接吸毒。合成的 致死性为一种方法提供了确定这些突变的新治疗靶标的基础。合成 致命相互作用，一个基因的改变会导致对第二个基因的依赖性。两者都不改变 对于生存至关重要，但是这些改变会导致癌细胞死亡。目前，合成致死（SL） 使用大规模功能屏幕确定合作伙伴，这些屏幕受到人为的人为影响 细胞培养条件和细胞系的可用性有限，在正确的癌症情况下具有特定突变。 我们建议挖掘患者肿瘤数据库，以识别种系突变的SL伴侣。我们的假设是 种系突变的SL伴侣将被选择性地放大或从未删除，并且也过表达 带有突变的原发性肿瘤样品。提出了两个具体目标：在AIM 1中，我们将开发一个 基于挖掘大规模基因组和转录数据集的计算方法来识别SL伴侣 癌症种系突变的。此方法将应用于来自的基因组和转录数据集 癌症基因组地图集（​​TCGA）和GTEX正常组织的基因表达数据（基因型组织 表达），以鉴定三个众所周知的乳腺癌CpG中的种系突变的SL伴侣BRCA1， BRCA2和PALB2。在AIM 2中，我们将通过实验验证每个种系突变的SL伴侣 在AIM 1中以两步确定。首先，在AIM 2A中，我们将使用遗传来验证每个突变的SL伴侣 在体外，在等源性乳腺癌细胞系（+/-突变）中敲低SL伴侣。下一个， 在AIM 2B中，我们将验证人类乳腺癌细胞系中前三名突变SL伴侣组合 使用遗传和药物敲低的小鼠中异种移植物。我们预计拟议的研究将确定 乳腺癌治疗和化学预防的新型可药物目标。长期目标是 开发一种新的系统方法，以识别潜在的靶向治疗疗法和 癌症种系突变患者的化学预防。拟议的研究对PQ3做出了回应，将 阐明基于遗传SL相互作用的种系突变肿瘤如何应对靶向疗法 种系突变和躯体改变之间。