Identifying and Targeting Master Regulators of Drug Resistance in Lung Adenocarcinoma through Network Analysis of Tumor Transcriptomic Data

项目摘要/摘要 肺癌是美国癌症相关死亡的主要原因，其原因超过 每年有10万人死亡。最常见的转移性肺腺癌的治疗 肺癌的组织学亚型，近几十年来通过靶向治疗的出现有了显著的改善 有致癌基因突变的肿瘤的治疗和没有突变的肿瘤的免疫检查点抑制剂。然而， 高达50%的转移性LUAD肿瘤对标准护理抗肿瘤治疗没有反应。上一首 精确肿瘤学努力发现LUAD肿瘤药物的基因组或免疫组织化学生物标志物 敏感度取得的成功有限。为了弥补这些缺陷，我们建议利用翻译后的 通过系统生物学方法识别和靶向LUAD耐药的生物决定因素 肿瘤转录数据的网络分析。由于计算生物学和下一代技术的进步 测序技术，每个患者LUAD肿瘤内基因的动态表达可能是准确的 测量，为鉴定关键的转录调节蛋白提供了一个新的窗口 启动和维持耐药肿瘤表型(即主调节剂)。系统的鉴定 基于非参数分析秩次的富集法可获得主要调节蛋白 (NaRnEA)，一种新开发的统计方法，能够利用上下文特定的转录调控 从LUAD肿瘤转录数据中提取高度机械性信息以提高计算机精度的网络 肿瘤学，从而克服了以前基因组和免疫组织化学方法的局限性。NaRnEA- 推测协调靶向治疗耐药性的主调节蛋白的活性将被利用 用于开发转录型机器学习药物敏感性生物标记物。此外，独一无二的 LUAD中&gt；400 FDA批准和研究化合物的种类扰动基因表达谱 将对NCIH1793细胞进行讯问，以确定能够靶向这些药物主调控子的药物- 使用OncoTreat算法的耐药性，这是一种新的系统生物学精确肿瘤学方法，具有 获得NYS CLIA认证，目前在哥伦比亚大学欧文进行多项临床试验 医疗中心。这一转化性研究项目将与同时进行的科学和临床培训同时进行。 由于申请者学习计算生物学，并与CUIMC的胸部肿瘤学家密切合作， 分别进行了分析。本研究项目完成后，申请人将完成临床培训。 纽约长老会医院通过哥伦比亚大学瓦格洛斯内科和外科医学院。 这一科学和医学相结合的博士前奖学金将为申请人申请内科做好准备 住院医生和血液学/肿瘤学临床研究员，最终成为一名独立的医生- 精准医学肿瘤学领域的科学家。

Project Summary/Abstract Lung cancer, the leading cause of cancer-related mortality in the United States, is responsible for more than 100,000 deaths each year. The treatment of metastatic lung adenocarcinoma (LUAD), the most common histological subtype of lung cancer, has improved substantially in recent decades through the advent of targeted therapy for tumors with oncogenic driver mutations and immune checkpoint inhibitors for those without. However, up to 50% of metastatic LUAD tumors will not respond to standard-of-care antineoplastic therapy. Previous precision oncology efforts to discover genomic or immunohistochemical biomarkers of LUAD tumor drug sensitivity have achieved limited success. To remedy these shortcomings, we propose to leverage a translational systems biology approach to identify and target the biological determinants of drug resistance in LUAD through network analysis of tumor transcriptomic data. Due to advances in computational biology and next-generation sequencing technologies, the dynamic expression of genes within each patient’s LUAD tumor may be accurately measured, providing a novel window for the identification of the key transcriptional regulatory proteins which initiate and maintain drug-resistant tumor phenotypes (i.e. Master Regulators). The systematic identification of Master Regulator proteins can be achieved with Non-parametric analytical Rank-based Enrichment Analysis (NaRnEA), a newly developed statistical method capable of leveraging context-specific transcriptional regulatory networks to extract highly mechanistic information from LUAD tumor transcriptomic data for in silico precision oncology, thus overcoming the limitations of previous genomic and immunohistochemical approaches. NaRnEA- inferred activity of Master Regulator proteins which coordinate resistance to targeted therapy will be leveraged for the development of a transcriptomic machine learning biomarker of drug-sensitivity. Additionally, one-of-a- kind perturbational gene expression profiles for >400 FDA-approved and investigational compounds in the LUAD cell line NCIH1793 will be interrogated to identify drugs capable of targeting these Master Regulators of drug- resistance using the OncoTreat algorithm, a novel systems biology precision oncology method which has received NYS CLIA certification and is currently in use for multiple clinical trials at the Columbia University Irving Medical Center. This translational research project will coincide with simultaneous scientific and clinical training as the applicant studies computational biology and works closely with thoracic oncologists at CUIMC, respectively. Following the completion of this research project the applicant will complete clinical training at the New York Presbyterian Hospital through the Columbia University Vagelos College of Physicians and Surgeons. This combined scientific and medical predoctoral fellowship will prepare the applicant for an Internal Medicine residency and a Hematology/Oncology clinical fellowship culminating in a career as an independent physician- scientist in the field of precision medical oncology.