PO.MCB08.02 · 分子与细胞生物学
碱基编辑用于对NF1中意义未明变异进行系统性重新分类
Base editing for systematic reclassification of variants of unknown significance in NF1
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
NF1是一个公认的肿瘤抑制基因，在癌症基因组中频繁突变，并且是癌症易感综合征神经纤维瘤病的致病基因。NF1基因非常大（约350 kb），是人类基因组中突变频率最高的基因之一。由于其编码蛋白的生物学机制尚未完全阐明、序列高度同源、等位基因异质性以及缺乏功能性检测方法，在临床实践中对NF1变异进行解读极具挑战性。根据ClinVar数据库，共列出13460个NF1变异（数据提取截至2024年7月），其中错义变异是最常见的类型，而在错义变异中84.8%为意义未明变异（VUS）。我们近期发现了NF1在微管损伤修复中的一项新功能（Duso等，Biorxiv 2025）。NF1缺陷细胞对微管解聚类美登素类药物（如DM1）变得高度敏感。我们设计了一项高通量碱基编辑筛选，利用这一差异敏感性来鉴定导致NF1功能丧失的变异。我们采用SpliceR来设计对照guide（非靶向、基因内以及靶向剪接必需和非必需区域的guide），而对于靶向NF1的gRNA，则使用BEstimate工具。作为模型，我们构建了HER2+乳腺癌细胞系HCC-1954以及293T细胞，使其稳定表达慢病毒胞嘧啶碱基编辑器（CBE）和腺嘌呤碱基编辑器（ABE）。编辑效率通过BEAR-GFP报告质粒进行评估。
我们获得了一个覆盖8191个变异、共5569条guide的文库。其中大多数为非同义变异。我们分析了已知NF1变异的覆盖情况。根据ClinVar分类，我们覆盖了882个VUS、68个致病性解读存在冲突的变异（CIP）、202个致病/可能致病（P/LP）变异以及25个良性/可能良性（B/LB）变异。根据我们用于VUS重新解读的RENOVO工具，所覆盖的变异中有4968个被判定为低精度致病性或良性。NF1中的关键功能结构域获得了高密度覆盖，尤其是573个变异覆盖了功能性GTPase激活结构域（GAP），2745个变异覆盖了可能介导与微管相互作用的HEAT结构域，267个变异覆盖了对膜定位至关重要的SecPH结构域。此外还覆盖了4257个位于剪接位点的变异以及3'非翻译区（UTR）变异。功能筛选的结果与公共数据相整合，用于基于我们的RENOVO架构开发一种新型NF1预测工具（Favalli V等，Am J Hum Genet. 2021以及Bonetti E等，Hum Genomics 2025）。这些工具对于克服神经纤维瘤病和精准肿瘤学中的关键诊断挑战将至关重要。
查看英文原文 English abstract
NF1 is an established tumor suppressor, frequently mutated in cancer genomes and responsible for the cancer-predisposing syndrome neurofibromatosis. NF1 is very large (~350 kb) and has one of the highest mutation frequency in the human genome. Due to incompletely understood biology of the coded protein, high sequence homology, allelic heterogeneity and lack of functional assays, the interpretation of NF1 variants is highly challenging in clinical practice. According to the ClinVar database, 13460 NF1 variants are listed (data extracted up to July 2024) with missense variants being the most represented type, of which 84.8% are variant of unknown significance - VUS.We recently identified a novel function in microtubular damage repair for NF1 (Duso et al Biorxiv 2025). NF1-deficient cells become highly sensitive to microtubule-depolymerising maytansinoids like DM1. We designed a high-throughput base editing screen that exploits this differential sensitivity to identify NF1 variants that lead to its loss of function.SpliceR was employed to design control guides (non targeting, intragenic and splice essential and non essential targeting regions) while for gRNAs directing to NF1, the BEstimate tool was utilised. As a model, we generated HER2+ breast cancer cell line, HCC-1954 and to 293T cells to stably express lentiviral cytidine-(CBE) and adenosine-base editors (ABE). Editing efficiency is evaluated through the BEAR-GFP reporter plasmid.
We obtained a library covering 8191 variants with 5569 total guides. Of these, the majority are nonsynonymous. We analysed the coverage of known NF1 variants. Based on ClinVar classification, we cover 882 VUS, 68 conflicting interpretation of pathogenicity (CIP), 202 pathogenic/likely pathogenic (P/LP) variants, and 25 benign/likely benign (B/LB) variants. Based on our RENOVO tool for VUS reinterpretation, 4968 covered variants are considered Low-precision Pathogenic or Benign.Key functional domains in NF1 are covered with high density, in particular with 573 variants covering the functional GTPase-activating domain (GAP), 2745 covering the HEAT domain, likely to mediate interactions with microtubules, and 267covering the SecPH domain, essential for membrane localization. 4257 variants in splicing sites and 3 prime untranslated regions (UTR) variants are covered.The results of the functional screen are integrated with public data to develop a novel NF1 predictor based on our RENOVO architecture (Favalli V et al., Am J Hum Genet. 2021 and Bonetti E, et al., Hum Genomics 2025).These tools will be essential to overcome key diagnostic challenges in neurofibromatosis and precision oncology.
利益披露 Disclosure
S. Galavotti, None..
E. Endrizzi, None..
E. Bonetti, None..
G. Frige, None..
P. Pelicci, None..
L. Mazzarella, None.