Genetic Determinants of Tumor Growth and Drug Sensitivity in EGFR Mutant Lung Cancer

项目总结 发现可促进肺癌生长并增加对酪氨酸激酶敏感性的EGFR突变 抑制剂(TKIs)已经改变了肺癌的治疗方式。然而，对TKI的反应是不同的，并且 最终会产生抵抗力。因此，在美国，由EGFR驱动的肺癌每年仍导致约20,000人死亡。 这些肿瘤在不同的肿瘤抑制基因(TSG)上有频繁的变化，然而，这些基因中的哪一个 改变共同推动肿瘤生长，它们如何影响癌细胞状态，以及它们是否是关键 治疗反应的决定因素在很大程度上仍不清楚。当前发现关系的方法 EGFR和TSG之间的关系在很大程度上依赖于相关的人类基因组研究和基于细胞系的模型。 然而，基因组研究在揭示基因相互作用方面往往在统计学上力量不足，而且没有。 提供有关TSG功能的信息。相反，细胞系的研究并不能概括体内环境。 而现存的有限的细胞系只代表了EGFR突变肿瘤的一个子集。要克服这些限制 并更好地了解体内肺癌生长和药物反应的基因组驱动因素，我们最近 用CRISPR/Cas9整合一种新的原生EGFR致癌小鼠肺癌模型 介导体基因组编辑和高通量肿瘤条形码测序。在活体内使用这种多路传输 模型中，我们发现剪接因子RBM10作为一种特性不佳的肿瘤生长抑制因子和 居然发现失活的“肿瘤抑制基因”Lkb1是与致癌基因EGFR合成致死的。 在这里，我们将调查基因如何控制致癌的EGFR驱动的肺癌的生物学。具体来说， 我们将建立Rbm10失活的细胞和分子后果，并阐明其机制 这就是EGFR和Lkb1之间合成致命性的基础。此外，了解肿瘤基因如何 影响治疗反应可能揭示出特定于基因型的治疗脆弱性。因此，我们将利用 我们的多路体内基因编辑平台来确定额外的TSGs对EGFR突变肺的影响 癌症生长和揭示治疗反应的基因组驱动因素。这项工作将增加我们的基础 了解EGFR突变肺癌生长的基因组决定因素并揭示新的和 具有治疗靶向性的促肿瘤途径。这些发现最终可能成为精确治疗的依据。 适用于致癌的EGFR驱动的肺癌患者。

PROJECT SUMMARY The discovery of mutations in EGFR that drive lung cancer growth and confer sensitivity to tyrosine kinase inhibitors (TKIs) has transformed the treatment of lung cancer. However, responses to TKIs are variable and resistance ultimately develops. Thus, EGFR-driven lung cancers still cause ~20,000 deaths annually in the US. These tumors have frequent alterations in diverse tumor suppressor genes (TSGs), however which of these alterations co-operate to drive tumor growth, how they impact cancer cell state, and whether they are key determinants of responses to therapy remains largely unknown. Current methods to uncover relationships between EGFR and TSGs largely rely on correlative human genomic studies and cell line-based models. However, genomic studies are often statistically underpowered to uncover genetic interactions and do not provide information on TSG function. Conversely, cell line studies do not recapitulate the in vivo environment and the limited cell lines that exist represent only a subset of EGFR mutant tumors. To overcome these limitations and better understand the genomic drivers of lung cancer growth and drug responses in vivo, we recently integrated a novel autochthonous mouse model of oncogenic EGFR-driven lung cancer with CRISPR/Cas9- mediated somatic genome editing and high-throughput tumor barcode sequencing. Using this multiplexed in vivo model, we uncovered the splicing factor RBM10 as a poorly characterized suppressor of tumor growth and unexpectedly found that inactivation of the “tumor suppressor” Lkb1 is synthetic lethal with oncogenic EGFR. Here, we will investigate how genotype controls the biology of oncogenic EGFR-driven lung cancer. Specifically, we will establish the cellular and molecular consequences of Rbm10 inactivation and elucidate the mechanism that underlies the synthetic lethality between EGFR and Lkb1. Moreover, understanding how tumor genotype influences treatment responses could reveal genotype-specific therapeutic vulnerabilities. Thus, we will leverage our multiplexed in vivo gene editing platform to determine the impact of additional TSGs on EGFR mutant lung cancer growth and uncover genomic drivers of responses to therapy. This work will increase our fundamental understanding of the genomic determinants of EGFR mutant lung cancer growth and reveal novel and therapeutically targetable pro-tumorigenic pathways. These findings could ultimately inform precision treatments for patients with oncogenic EGFR-driven lung cancer.