Novel models for functional profiling of germline SDH variants associated with cancer

目的：琥珀酸脱氢酶亚单位(SDHx)基因功能丧失(LOF)突变导致 SDH缺乏并增加患多种癌症的终生风险，包括胃肠道间质瘤， 副神经节瘤、嗜铬细胞瘤和肾癌。已知的LOF/病原性LOF患者 生殖系SDHx突变、遗传咨询(筛查其他家庭成员)和增强的癌症 说明了筛查程序。当SDH缺乏的肿瘤在早期被发现时，它们通常是 是可以治愈的。然而，3.2%的人群携带着意义未知的生殖系SDHx错义变体 (VUS，未知致病或良性)。因此，我们目前没有能力识别许多 由于我们缺乏对功能性疾病的了解，有风险的患者应进行适当的筛查 生殖系SDHx vus的后果。 计划：该提案将使用深度突变扫描(DMS)方法对SDHA VU进行功能性测试 我们培育的新型SDHA缺失细胞系。我们将通过配对DMS来识别所有LOF SDHA变体 用我们实验室开发的负代谢选择方法。以确定此方法是否扩展 为了测试其他SDHx基因(SDHB、C、D)的VU，我们将生成这些个体的敲除模型 基因和评估在每个细胞系中的负代谢选择。人体模型，可以提供强大的 将生成用于临床变异分类的证据，并验证用于测试个体的证据 变种。 方法：为了解决在人群中看到的大量SDHA变体，我们将创建所有 通过饱和突变获得可能的SDHA氨基酸变异，并利用该文库来补充我们的SDHA- 缺乏细胞系。我们将通过在代谢物耗尽的情况下培养文库来筛选SDHA LOF变体 需要全功能SDH(-丙酮酸、-天冬氨酸)的条件。在深度测序之后，耗尽 将进行分析。将对每个变体进行功能解释(功能正常或LOF 通过将计算的效果分数与无意义/同义对照的分数进行比较(目标1)。要填满水流 在没有SDH缺陷细胞系的情况下，我们将使用CRISPR/Cas9产生SDHB-、SDHC-和SDHD-基因敲除 并验证它们的有效性。使用代谢物耗竭介质的阴性选择将被应用于这些 确定其在未来DMS实验中的效用的新模型(目标2)。 临床意义：我们治愈癌症的最好机会在于及早发现SDH缺陷患者 因此，关键的医疗需要在于对SDHx基因变体进行分类，以便能够识别和 随后对高危患者进行筛查。

Objectives: Loss-of-function (LOF) mutations in succinate dehydrogenase subunit (SDHx) genes result in SDH-deficiency and increase the lifetime risk for developing a number of cancers, including GI stromal tumors, paraganglioma, pheochromocytoma, and renal cell carcinoma. In patients with a known LOF/pathogenic germline SDHx mutation, genetic counseling (to screen other family members) and enhanced cancer screening procedures are indicated. When SDH-deficient tumors are detected at early stages, they are often curable. However, 3.2% of the population carry germline SDHx missense variants of unknown significance (VUS, not known to be pathogenic or benign). Therefore, we currently do not have the ability to identify many patients at risk and screen them appropriately because of our lack of knowledge of the functional consequences of germline SDHx VUS. Plan: This proposal will functionally test SDHA VUS utilizing a deep mutational scanning (DMS) approach in a novel SDHA-deficient cell line that we have generated. We will identify all LOF SDHA variants by pairing DMS with a negative metabolic selection method developed in our laboratory. To determine if this approach extends to test VUS of the other SDHx genes (SDHB, C, D), we will generate knockout models of these individual genes and asses negative metabolic selection in each cell line. Human models, which can provide strong evidence to be used for clinical variant classification will be generated and validated for testing individual variants. Methods: To address the large number of SDHA variants seen in the population, we will create libraries of all possible SDHA amino-acid variants by saturation mutagenesis and use this library to complement our SDHA- deficient cell line. We will select against SDHA LOF variants by growing the libraries under metabolite-depleted conditions requiring fully functional SDH (-pyruvate, -aspartic acid). Following deep sequencing, depletion analysis will be performed. Functional interpretations (functionally normal or LOF) will be made for each variant by comparing calculated effect scores with those of nonsense/ synonymous controls (Aim 1). To fill the current void of SDH-deficient cell lines, we will use CRISPR/Cas9 to generate SDHB-, SDHC-, and SDHD-knockout cell lines and validate them. Negative selection using metabolite-depleted medium will be applied to these novel models to determine their utility for future DMS experiments (Aim 2). Clinical Relevance: Our best chance of a cancer cure lies in early detection in patients with SDH-deficient tumors, thus the critical medical need lies in classifying SDHx genetic variants to enable identification and subsequent screening of at-risk patients.