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的目的是靶向EGFR早期耐药的临床重要基因组标志物 酪氨酸激酶抑制剂（EGFR-TKI）治疗EGFR突变型非小细胞肺癌（NSCLC）， 抑制下受体酪氨酸激酶（RTK）驱动的信号传导途径的定量模型，以及 探索人种、种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突变型NSCLC包括肺腺癌的实质性亚组（15%， 西方人/白色人群），在亚裔美国人、夏威夷土著人、太平洋 岛民（AANHPI ~50%）和拉丁美洲人（~38%）。EGFR突变显示与吸烟状态密切相关， 性别、种族/民族和遗传祖先。AANHPI和拉丁美洲种族/族裔的妇女， 非拉丁裔白人（NLW），较低的吸烟率和较高的EGFR突变型肿瘤的频率。有趣的是，一 最近的研究表明，高土著美国血统（这是密切相关的亚洲血统） 在拉丁美洲人中发生EGFR突变型肺癌的风险更高。这表明体细胞EGFR 突变与种族/民族相关的生物学和非生物学方面密切相关，或 祖先通过这项研究，我们将开发新的治疗策略， 和NCI-CTEP药物转化为NCI申办的克服EGFR-TKI耐药性的临床试验 EGFR突变型NSCLC的相关机制。我们还将评估种族/民族和遗传 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）已广泛用于肺癌研究和药物开发。 我们在建立PDX和进行基于PDX的研究方面拥有丰富的经验。穿过杰克逊 实验室（JAX），UCSF和UT西南合作，我们建立和表征了200多个肺 癌症PDX，其中25个具有EGFR激活突变，我们已经确定了另外10个EGFR突变体 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我们已经对许多PDX进行了详细的组织病理学和基因组表征 重点关注癌基因驱动的NSCLC，我们确定了多种假定的耐药机制， 在这些模型中对目前EGFR靶向治疗方法的早期抗性。我们还表明， EGFR突变型PDX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批准和NCI- CTEP特工。我们将使用高容量的活细胞成像平台来分析细胞内EGFR信号传导， 提供了细胞对抑制适应的高分辨率评估。这个项目的工作源于 我们目前的研究，将用于解决以下具体目标。 目标1：开发与FDA批准的药物和/或NCI-CTEP药物的靶向治疗组合， 克服对EGFR-TKI的耐药机制，这预示着早期肿瘤进展。我们计划a） 确定携带MET的EGFR突变PDX模型中最有效的双重MET/EGFR靶向策略， 介导的EGFR-TKI抗性旁路途径机制; B）确定最有效的双重EGFR-TKI抗性旁路途径机制。 在携带不常见EGFR突变的EGFR突变型PDX中的阻断方法;以及c）克服限制性的 BCL-2/BCL-xL抑制剂和NCI-CTEP在RBM 10缺陷EGFR突变型NSCLC中的凋亡反应 佩西托克拉斯探员。 目的2：使用活细胞中的信号动力学建模EGFR抑制剂效应。前提是有针对性地 抑制剂治疗可以通过表征RTK驱动的细胞内信号传导中的定量变化来优化 在不同的EGFR突变体、遗传背景和抑制剂类别之间。我们将使用激酶活性 生物传感器，以在用于研究的PDX模型组中以单细胞分辨率跟踪AKT和ERK活性模式。 目标1.这种高含量的分析，结合EGFR突变和遗传学的多样性， PDX面板所代表的背景，将为定量模型提供数据， scope.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 确定对多种类别（和组合）的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享信号传导决定因素， 或者取决于患者或遗传背景特异性因素。此外，当我们的结果 与Aim 1相结合，我们将有独特的机会根据体内数据验证我们的细胞模型。 目的3：检查人种/种族和遗传血统在EGFR信号传导和对EGFR的应答中的作用。 EGFR治疗。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， 我们将评估基线信号和对第三代EGFR-TKI的反应是否与第三代EGFR-TKI的反应有关。 奥希替尼受人种/种族影响。在拉丁美洲人中，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治疗和我们对肺癌EGFR信号传导的理解， 重点关注少数群体，包括将导致更公平地转化为临床试验的信息。