ARTNet NOSI Supplement

ARTNet NOSI 补充

• 批准号: 10831209
• 负责人: Trever G Bivona
• 金额: $ 8.08万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10831209
• 关键词: Address; CD47 gene; Cancer Etiology; Cancer Patient; Cell Survival; Cells; Chronic; Clinical; Communities; Cues; Data Science Core; Data Set; Development; Disease; Drug resistance; Ecosystem; Ensure; Epidermal Growth Factor Receptor; Event; Extracellular Matrix; Fibroblasts; Foundations; Funding; Future; Geography; Goals; Human; Immune; KRAS2 gene; Link; Lung; Lung Adenocarcinoma; Macrophage; Macrophage Activation; Malignant Neoplasms; Malignant neoplasm of lung; Medicine; Methods; Modeling; Molecular; NF-kappa B; Nature; Non-Small-Cell Lung Carcinoma; Oncogenic; Organoids; PD-1/PD-L1; PDPK1 gene; Paracrine Communication; Pathway interactions; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Pre-Clinical Model; Process; Progress Reports; Proteomics; Public Health; Refractory; Research; Research Project Grants; Resistance; Signal Transduction; Specimen; System; Testing; Therapeutic; acquired drug resistance; cancer cell; cancer therapy; cancer type; clinical translation; cytokine; data sharing; humanized mouse; immunosuppressive checkpoint; improved; improved outcome; innovation; molecular targeted therapies; mortality; mouse model; mutant; neoplastic cell; patient derived xenograft model; precision oncology; prevent; programs; resistance mechanism; response; success; targeted treatment; therapeutic evaluation; therapy resistant; treatment strategy; tumor; tumor microenvironment; tumor progression; tumor xenograft

Project Summary/Abstract: The goal of this BAATAAR-UP renewal program application within the NCI ARTNet is to characterize the mechanisms of, and therapeutically counteract, acquired resistance to molecular therapies in non-small cell lung cancer (NSCLC) by delineating the tumor-tumor microenvironment (TME) ecosystem and its plasticity during treatment. Acquired resistance is defined as tumor progression that occurs during therapy and after an initial tumor response. The overarching hypothesis is that acquired resistance to molecular therapies can be thwarted by defining and exploiting vulnerabilities in the cellular, signaling, and geographic tumor ecosystem networks that allow tumors to survive and grow during therapy. In lung cancer and other cancer types, the use of targeted therapies that inhibit important and common oncogenic driver alterations such as mutant EGFR and KRAS (G12C) and block immunosuppressive checkpoints such as PD1/PDL1 is improving patient outcomes. A major challenge to transforming cancers into chronic or curable diseases is acquired resistance, which enables lethal cancer progression in patients. Understanding the mechanisms underlying acquired resistance is essential to develop counteracting strategies that improve patient survival. During the prior NCI U54 DRSC funding period, our team uncovered several mechanisms of acquired resistance to targeted therapy in human NSCLC by studying clinical specimens and innovative patient-derived models including humanized murine models bearing patient-derived xenografts (PDXs) and patient-derived organoids (PDOs) with an intact TME. Our expert team proposes to investigate these mechanisms, and identify others, synergistically and iteratively via 3 Research Projects and optimal interactions with 2 Cores. A Data Science Core will analyze, harmonize, centralize, and share data obtained across the basic and translational continuum using innovative methods. An Administrative Core will ensure optimal project integration and internal and external interactions with the ARTNet Consortium, and scientific and lay communities. Project 1 (Clinical tumor-TME acquired resistance) is translational and uses clinical specimens and patient-derived models to test the hypothesis that tumor macrophages and tumor fibroblasts promote acquired resistance via paracrine signaling interactions including cytokine, CD47, and extracellular matrix (ECM) cues sensed by cancer cells and converging on survival pathways such as YAP and NF-kB. Project 2 (PDX tumor-TME acquired resistance) is translational and uses humanized mouse models to test the hypothesis that an immune-suppressive TME and activation of macrophage and fibroblast signaling circuits that support tumor cell survival via PDK1, YAP, and NF-kB signaling promote acquired resistance. Project 3 (PDO tumor-TME acquired resistance) is basic and uses synthetic lethal and proteomic profiling in PDOs with a TME to test the hypothesis that signaling interactions involving the ECM, TROP2, and CD47 promote acquired resistance. Synergistic, iterative interactions to study these mechanisms across projects and systems will yield robust, translatable treatment strategies to counteract acquired resistance.

项目摘要/摘要：在NCI Artnet内申请BAATAAR-UP续订计划的目标 是描述获得性分子疗法耐药的机制，并在治疗上加以抵消。 在非小细胞肺癌(NSCLC)通过描绘肿瘤-肿瘤微环境(TME)生态系统和 它在治疗过程中的可塑性。获得性耐药被定义为在治疗过程中发生的肿瘤进展 在最初的肿瘤反应之后。最重要的假设是对分子治疗的获得性抵抗力 可以通过定义和利用细胞、信号和地理肿瘤中的漏洞来阻止 允许肿瘤在治疗期间存活和生长的生态系统网络。在肺癌和其他癌症类型中， 使用靶向疗法抑制重要和常见的致癌基因改变，如突变 EGFR和KRAS(G12C)以及PD1/PDL1等阻断免疫抑制检查点正在改善患者 结果。将癌症转变为慢性病或可治愈疾病的一个主要挑战是获得性耐药性， 这会使患者的癌症发生致命的进展。了解后天获得的潜在机制 耐药性对于制定提高患者存活率的对抗策略至关重要。在之前的NCI期间 在U54 DrSc资助期间，我们的团队发现了几种获得性靶向治疗耐药的机制 在人类非小细胞肺癌中，通过研究临床标本和创新的患者衍生模型，包括人性化 携带患者来源的异种移植物(PDX)和患者来源的有机物(PDO)的小鼠模型 我也是。我们的专家团队建议研究这些机制，并确定其他机制，协同和 迭代地通过3个研究项目和与2个核心的最佳交互。数据科学核心将分析， 使用创新技术协调、集中和共享在基本和翻译过程中获得的数据 方法：研究方法。行政核心将确保最佳项目整合以及内部和外部互动 与Artnet联盟以及科学界和非科学界合作。项目1(临床肿瘤--获得性TME 抗性)是翻译的，并使用临床样本和患者派生的模型来检验假设 肿瘤巨噬细胞和肿瘤成纤维细胞通过旁分泌信号相互作用促进获得性耐药 包括细胞因子、CD47和细胞外基质(ECM)信号，这些信号可被癌细胞感知并集中在生存上 YAP和核因子-kB等通路。项目2(PDX肿瘤-TME获得性耐药)是翻译的，使用 人源化小鼠模型验证免疫抑制TME和巨噬细胞激活的假设 而通过PDK1、YAP和NF-kB信号支持肿瘤细胞存活的成纤维细胞信号通路促进 后天抵抗力。项目3(PDO肿瘤-TME获得性耐药)是基本的，使用合成致命性和 用TME对PDO进行蛋白质组学分析，以检验涉及ECM的信号相互作用， TROP2和CD47促进获得性耐药。协同、迭代的相互作用来研究这些机制 跨项目和系统将产生强大的、可翻译的治疗策略，以抵消获得性耐药性。

项目成果

Circulating tumor DNA analysis in patients with EGFR mutant lung cancer.

• DOI: 10.21037/jtd.2018.09.106
• 发表时间: 2018-09
• 期刊: Journal of thoracic disease
• 影响因子: 2.5
• 作者: S. Nanjo;T. Bivona

Targeting AXL in NSCLC.

• DOI: 10.2147/lctt.s305484
• 发表时间: 2021
• 期刊: Lung Cancer (Auckland, N.Z.)
• 作者: Zaman A;Bivona TG
• 通讯作者: Bivona TG

A CRISPR/Cas9-Engineered ARID1A-Deficient Human Gastric Cancer Organoid Model Reveals Essential and Nonessential Modes of Oncogenic Transformation.

• DOI: 10.1158/2159-8290.cd-20-1109
• 发表时间: 2021-06
• 期刊: Cancer discovery
• 影响因子: 28.2
• 作者: Lo YH;Kolahi KS;Du Y;Chang CY;Krokhotin A;Nair A;Sobba WD;Karlsson K;Jones SJ;Longacre TA;Mah AT;Tercan B;Sockell A;Xu H;Seoane JA;Chen J;Shmulevich I;Weissman JS;Curtis C;Califano A;Fu H;Crabtree GR;Kuo CJ
• 通讯作者: Kuo CJ

Human Intestinal Enteroids Model MHC-II in the Gut Epithelium.

肠上皮中的人肠肠类模型 MHC-II。

• DOI: 10.3389/fimmu.2019.01970
• 发表时间: 2019
• 期刊: Frontiers in immunology
• 影响因子: 7.3
• 作者: Wosen,JonathanE;Ilstad-Minnihan,Alexandra;Co,JuliaY;Jiang,Wei;Mukhopadhyay,Dhriti;Fernandez-Becker,NielsenQ;Kuo,CalvinJ;Amieva,ManuelR;Mellins,ElizabethD
• 通讯作者: Mellins,ElizabethD

Remodeling of the tumor/tumor microenvironment ecosystem during KRAS G12C inhibitor clinical resistance in lung cancer.

• DOI: 10.1172/jci156891
• 发表时间: 2022-02-15
• 期刊: The Journal of clinical investigation
• 作者: Manabe T;Bivona TG
• 通讯作者: Bivona TG