Characterizing treatment responses for common lung cancer (LC) subtypes in Latinos and Asians

描述拉丁裔和亚洲人常见肺癌 (LC) 亚型的治疗反应

• 批准号: 10733396
• 负责人: Jonathan W Riess
• 金额: $ 28.83万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10733396
• 关键词: Address; Apoptotic; Asian Americans; Asian ancestry; Asian population; Automobile Driving; BCL1 Oncogene; BCL2 gene; BCL2L1 gene; Biological; Biosensor; Bypass; California; Cancer Model; Cancer Patient; Cancer Therapy Evaluation Program; Cell model; Cells; Clinical; Clinical Trials; Collaborations; Combined Modality Therapy; Comprehensive Cancer Center; Data; Development; Drug Combinations; Epidermal Growth Factor Receptor; Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor; Equity; Ethnic Origin; FDA approved; Family; Frequencies; Gender; Generations; Genes; Genetic; Genomics; Indigenous American; Individual; Latino; Latino Population; Lung Adenocarcinoma; Lung Neoplasms; Malignant neoplasm of lung; Mediating; Minority; Modeling; Mutation; Native Hawaiian; Non-Small-Cell Lung Carcinoma; Oncogenes; Pacific Islander; Patients; Pattern; Pharmaceutical Preparations; Phosphotransferases; Population; Proto-Oncogene Proteins c-akt; Race; Receptor Inhibition; Receptor Protein-Tyrosine Kinases; Receptor Signaling; Research; Resistance; Resolution; Role; Signal Pathway; Signal Transduction; Smoking; Smoking Status; Testing; Texas; The Jackson Laboratory; Translating; Translations; Universities; Variant; Woman; Work; cancer subtypes; drug development; ethnic minority; experience; genomic biomarker; high risk; imaging platform; in vivo; inhibitor; inhibitor therapy; live cell imaging; machine learning method; minority patient; mutant; novel therapeutic intervention; novel therapeutics; patient derived xenograft model; racial minority; repository; research and development; resistance mechanism; response; targeted treatment; treatment optimization; treatment response; tumor; tumor progression

SPECIFIC AIMS The purpose of UCaTS Project 2 is to target clinically important genomic markers of early resistance to EGFR tyrosine kinase inhibitors (EGFR-TKIs) in EGFR-mutant non-small cell lung cancer (NSCLC), to develop quantitative models of Receptor Tyrosine Kinase (RTK)-driven signaling pathways under inhibition, and to explore the role race, ethnicity and genetic ancestry has in predicting baseline EGFR signaling and EGFR-TKI treatment response. EGFR-mutant NSCLC comprises a substantial subset of lung adenocarcinoma (15% in Western/White populations) and occurs with a higher frequency in Asian Americans, Native Hawaiians, Pacific Islanders (AANHPI ~50%), and Latinos (~38%). EGFR mutations show strong associations with smoking status, gender, race/ethnicity, and genetic ancestry. Women of AANHPI and Latino race/ethnicity have, compared to non-Latino Whites (NLW), lower smoking rates and higher frequency of EGFR mutant tumors. Interestingly, a recent study showed that high Indigenous American Ancestry (which is closely associated with Asian ancestry) confers a higher risk of developing EGFR-mutant lung cancer in Latinos. This suggests that somatic EGFR mutations have close associations of biological and non-biological aspects associated with race/ethnicity or ancestry. Through this research, we will develop novel therapeutic strategies with combinations of FDA approved and NCI-CTEP drugs to translate into NCI-sponsored clinical trials overcoming EGFR-TKI resistance mechanisms associated in EGFR-mutant NSCLC. We will also assess whether race/ethnicity and genetic ancestry impacts EGFR signaling and influences responses to EGFR inhibition. Patient-derived xenografts (PDXs) have been broadly used in lung cancer research and drug development. We have extensive experience in establishing PDXs and conducting PDX-based research. Through the Jackson Laboratory (JAX), UCSF and UT Southwestern collaborations, we established and characterized over 200 lung cancer PDXs in which 25 have EGFR-activating mutations and we have identified an additional 10 EGFR-mutant lung cancer models in PDXnet. We anticipate that UCaTS will generate at least 25 additional EGFR-mutant PDXs. We have performed detailed histopathological and genomic characterization on many of these PDXs focused on oncogene driven NSCLC where we identified multiple putative resistance mechanisms that mediate early resistance to current EGFR-targeted therapeutic approaches in these models. We have also shown that EGFR-mutant PDXs can potentially be used to optimize treatment combinations to overcome EGFR-TKI resistance and to identify the most efficacious drugs or drug combinations including FDA approved and NCI- CTEP agents. We will use a high-content live-cell imaging platform to analyze intracellular EGFR signaling, which provides a high-resolution assessment of cellular adaptation to inhibition. The work for this project arises out of our current research, which will be used to address the following specific aims.: Aim 1: Develop targeted treatment combinations with FDA approved drugs and/or NCI-CTEP agents to overcome mechanisms of resistance to EGFR-TKIs that herald early tumor progression. We plan to a) determine the most effective dual MET/EGFR targeting strategy in EGFR-mutant PDX models harboring MET- mediated bypass tract mechanisms of EGFR-TKI resistance; b) determine the most effective dual EGFR- blockade approach in EGFR-mutant PDXs harboring uncommon EGFR-mutations; and c) overcome the limited apoptotic response in RBM10 deficient EGFR-mutant NSCLC with the BCL-2/BCL-xL inhibitor and NCI-CTEP agent pelcitoclax. Aim 2: Modeling EGFR inhibitor effects using signaling dynamics in live cells. The premise is that targeted inhibitor therapy can be optimized by characterizing quantitative variation in RTK-driven intracellular signaling across different EGFR mutants, genetic backgrounds, and inhibitor classes. We will use kinase activity biosensors to track AKT and ERK activity patterns with single-cell resolution in the set of PDX models used in Aim 1. This high-content analysis, in combination with the diverse set of EGFR mutations and genetic backgrounds represented by the PDX panel, will provide the data for a quantitative model with an unprecedented scope. Leveraging machine learning methods, our model will allow us to identify the primary signaling parameters determining response to multiple classes (and combinations) of EGFR inhibitors, MET inhibitors, and Bcl-2/Bcl-xL family inhibitors. Importantly, our model will help to answer a long-standing question of whether EGFR inhibitor resistance involves a shared set of signaling determinants across individuals and backgrounds, or instead depends on patient or genetic background-specific factors. Furthermore, when our results are integrated with Aim 1, we will have the unique opportunity to validate our cellular model against in vivo data. Aim 3: Examining the role of race/ethnicity and genetic ancestry in EGFR signaling and responses to EGFR therapies. As our study will test EGFR therapies in large numbers of EGFR-mutant models from AANHPI, Latinos, and NLW, we will evaluate whether baseline signaling and responses to the third generation EGFR-TKI osimertinib are influenced by race/ethnicity. In Latinos, we will also estimate individual levels of Indigenous American ancestry and will evaluate its associations with baseline signaling and treatment response. IMPACT: This project will advance EGFR therapy and our understanding of EGFR signaling in lung cancer with a focus on minorities, including information that will lead to a more equitable translation into clinical trials.

具体目标 UCaTS 项目 2 的目的是针对 EGFR 早期耐药的临床重要基因组标记物 酪氨酸激酶抑制剂（EGFR-TKI）治疗 EGFR 突变非小细胞肺癌（NSCLC），开发 抑制下受体酪氨酸激酶（RTK）驱动的信号通路的定量模型，并 探索种族、民族和遗传血统在预测基线 EGFR 信号传导和 EGFR-TKI 中的作用 治疗反应。 EGFR 突变 NSCLC 构成了肺腺癌的一个重要子集（15% 西方/白人），并且在亚裔美国人、夏威夷原住民、太平洋岛民中发生频率较高 岛民 (AANHPI ~50%) 和拉丁裔 (~38%)。 EGFR 突变与吸烟状况密切相关， 性别、种族/民族和遗传血统。与 AANHPI 和拉丁裔种族/族裔的女性相比 非拉丁裔白人 (NLW)、吸烟率较低和 EGFR 突变肿瘤发生率较高。有趣的是，一个 最近的研究表明，美国原住民血统较高（与亚洲血统密切相关） 导致拉丁美洲人患 EGFR 突变型肺癌的风险更高。这表明体细胞 EGFR 突变与种族/民族或种族相关的生物学和非生物学方面有密切的关联 祖先。通过这项研究，我们将结合 FDA 批准的药物开发新的治疗策略 和 NCI-CTEP 药物将转化为 NCI 赞助的克服 EGFR-TKI 耐药性的临床试验 EGFR 突变 NSCLC 的相关机制。我们还将评估种族/民族和遗传是否 血统影响 EGFR 信号传导并影响对 EGFR 抑制的反应。 患者来源的异种移植物（PDX）已广泛应用于肺癌研究和药物开发。 我们在建立 PDX 和开展基于 PDX 的研究方面拥有丰富的经验。通过杰克逊 实验室 (JAX)、UCSF 和 UT Southwestern 合作，我们建立并表征了 200 多个肺 癌症 PDX，其中 25 个具有 EGFR 激活突变，我们还鉴定了另外 10 个 EGFR 突变 PDXnet 中的肺癌模型。我们预计 UCaTS 将产生至少 25 个额外的 EGFR 突变体 PDX。我们对许多 PDX 进行了详细的组织病理学和基因组表征 专注于癌基因驱动的非小细胞肺癌，我们发现了多种介导的假定耐药机制 这些模型中对当前 EGFR 靶向治疗方法的早期耐药性。我们还表明 EGFR 突变 PDX 有可能用于优化治疗组合以克服 EGFR-TKI 耐药性并确定最有效的药物或药物组合，包括 FDA 批准的和 NCI- CTEP代理。我们将使用高内涵活细胞成像平台来分析细胞内 EGFR 信号传导，这 提供细胞对抑制的适应的高分辨率评估。该项目的工作源于 我们目前的研究将用于实现以下具体目标： 目标 1：使用 FDA 批准的药物和/或 NCI-CTEP 药物开发有针对性的治疗组合，以 克服预示着早期肿瘤进展的 EGFR-TKI 耐药机制。我们计划a) 确定在携带 MET 的 EGFR 突变 PDX 模型中最有效的双重 MET/EGFR 靶向策略 EGFR-TKI 耐药介导的旁路机制； b) 确定最有效的双重 EGFR- 对携带不常见 EGFR 突变的 EGFR 突变 PDX 进行阻断方法； c) 克服有限的 BCL-2/BCL-xL 抑制剂和 NCI-CTEP 对 RBM10 缺陷 EGFR 突变 NSCLC 的细胞凋亡反应 药剂pelcitoclax。 目标 2：利用活细胞中的信号动力学模拟 EGFR 抑制剂的作用。前提是有针对性 可以通过表征 RTK 驱动的细胞内信号传导的定量变化来优化抑制剂治疗 跨越不同的 EGFR 突变体、遗传背景和抑制剂类别。我们将使用激酶活性 生物传感器在 PDX 模型组中以单细胞分辨率跟踪 AKT 和 ERK 活动模式 目标 1. 这种高内涵分析结合了不同的 EGFR 突变和遗传 以PDX面板为代表的背景，将为定量模型提供前所未有的数据 范围。利用机器学习方法，我们的模型将使我们能够识别主要信号 确定对多种 EGFR 抑制剂、MET 抑制剂、 和 Bcl-2/Bcl-xL 家族抑制剂。重要的是，我们的模型将有助于回答一个长期存在的问题： EGFR 抑制剂耐药性涉及一组跨个体和背景的共同信号决定因素， 或者取决于患者或遗传背景特定因素。此外，当我们的结果是 与 Aim 1 集成后，我们将有独特的机会根据体内数据验证我们的细胞模型。 目标 3：检查种族/民族和遗传血统在 EGFR 信号传导和反应中的作用 EGFR疗法。由于我们的研究将在来自 AANHPI 的大量 EGFR 突变模型中测试 EGFR 疗法， 拉丁裔和 NLW，我们将评估第三代 EGFR-TKI 的基线信号传导和反应是否 奥希替尼受种族/民族的影响。在拉丁裔中，我们还将估计土著人的个人水平 美国血统，并将评估其与基线信号和治疗反应的关联。 影响：该项目将推进 EGFR 治疗以及我们对肺癌中 EGFR 信号传导的理解 关注少数群体，包括能够更公平地转化为临床试验的信息。