Drug Mechanism of Action-based targeting of tumor subpopulations
Drug Mechanism of Action-based targeting of tumor subpopulations
批准号:
10729387
负责人:
ANDREA CALIFANO
金额:
$47.94万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-19 至 2028-08-31
关键词:
AbateAddressAlgorithmsBehaviorCancer CenterCancer PatientCell LineCell modelCellsClinicalComplement 1qComplexDataDependenceDisease-Free SurvivalDrug TargetingDrug resistanceDuct (organ) structureExcisionFibroblastsFosteringFundingGenetically Engineered MouseGoalsHealthHeterogeneityHumanImmuneImmune checkpoint inhibitorImmune responseImmunotherapyIn VitroIndividualInfiltrationInter-tumoral heterogeneityInterventionIsogenic transplantationKPC modelLogicMAP Kinase GeneMacrophageMalignant - descriptorMalignant NeoplasmsMediatingMetaplasiaMethodologyModelingMolecularNetwork-basedNeurosecretory SystemsOlives - dietaryOrganoidsOutcomePancreatic Ductal AdenocarcinomaParacrine CommunicationPathway interactionsPatientsPharmaceutical PreparationsPre-Clinical ModelPrediction of Response to TherapyPrintingProteinsProteomePublicationsReagentRegulatory T-LymphocyteRelapseSamplingSystemTREM2 geneTherapeuticValidationXenograft Modelactionable mutationcancer cellcastration resistant prostate cancercell behaviorclinically relevantdesigndrug mechanismdrug sensitivitydrug-sensitivegenome databasegenome-widehuman modelimmune checkpoint blockadeimprovedin vivo Modelneoplastic cellnovelpanaceapatient derived xenograft modelpatient responsibilitiespharmacologicprogramsrecruitrelapse patientsresponsesingle cell analysissmall molecule inhibitortargeted treatmenttumortumor heterogeneitytumor microenvironmenttumor-immune system interactionsvirtual
中文摘要
患有侵袭性癌症的患者通常不存在可消除的突变,
对免疫检查点阻断有反应,因此从免疫检查点阻断中仅获得无病生存期的适度改善。
靶向治疗和免疫治疗。肿瘤异质性通过促进肿瘤细胞的生长而使这些挑战进一步复杂化。
旁分泌信号介导的耐药细胞状态的重编程、适应、选择和扩增,
以及免疫抑制性肿瘤微环境(TME)的出现,这是最终负责
治疗复发和预后不良我们建议应对这些挑战,即,物色更多
普遍的,机制的药物干预目标,并评估其潜在的价值,在高度
异质性肿瘤-是严重依赖于准确和全面的细胞的可用性,
网络,它是癌细胞的细胞自主行为及其与其他TME相互作用的基础
亚群在项目3中,我们建议匹配临床上的全蛋白组作用机制(MoA)
相关化合物-从我们的PanACEA全基因组分子扰动数据库中解剖,
人类恶性肿瘤的高保真模型-分子上不同的非癌基因依赖性,
共存的亚群,代表被募集到TME的转化的恶性细胞或健康细胞
以产生促恶性的免疫抑制环境,如通过单细胞分析所解剖的。针对个别
亚群正变得越来越重要,因为这两个转化的异质性和可塑性,
和未转化的TME亚群已经成为,也许,最根本的障碍,
在癌症患者和不同的亚群中实现持久的反应似乎具有潜在的
正交药物敏感性或代表健康的,免疫抑制细胞,这将需要一个完整的
因此,我们必须采取不同的方法,将他们的招募目标锁定在TME,而不是导致他们的死亡。完成
为了实现这些目标,项目3将利用在前一个CSBC资助周期中产生的数据、模型和试剂
用于转移性去势抵抗性前列腺癌(mCRPC)和胰腺导管腺癌的研究
(PDAC),两种侵袭性、高度异质性恶性肿瘤,5年生存率≤ 20%。我们将专注于
探讨mCRPC及其侵袭性神经内分泌亚型(NEPC)的新分子三角定位
设计用于识别高保真模型的方法(OncoLoop)-即,细胞系,类器官,遗传学
工程小鼠模型(GEMM)和患者来源的异种移植物(PDX)-以产生患者相关药物
在体外扰动谱和验证药物预测从患者来源的样品分析在临床前
体内模型。然后,我们将重点关注6个分子上不同的恶性PDAC亚群,包括
谱系、形态发生和腺泡至导管化生样细胞,均在MAPK途径中检测到
活动或非活动状态-探索多种促恶性TME亚群(包括肿瘤浸润性T细胞)
调节细胞、巨噬细胞和成纤维细胞),以鉴定有效地耗尽它们的小分子抑制剂。
英文摘要
Patients with aggressive cancers often present with no pharmacologically actionable mutations and fail to
respond to immune checkpoint blockade, thus deriving only modest improvement in disease-free survival from
targeted therapy and immunotherapy. Tumor heterogeneity further complicates these challenges by fostering
paracrine signal-mediated reprogramming, adaptation, selection, and expansion of drug-resistant cell states, as
well as emergence of an immunosuppressive tumor microenvironment (TME), which are ultimately responsible
for patient relapse and poor outcome . We propose that addressing these challenges—i.e., identifying more
universal, mechanistic targets for pharmacological intervention and assessing their potential value in highly
heterogeneous tumors—is critically dependent on the availability of accurate and comprehensive cellular
networks, which underlie both the cell-autonomous behavior of cancer cells and their interaction with other TME
subpopulations. In Project 3 we propose to match the proteome-wide Mechanism of Action (MoA) of clinically
relevant compounds—as dissected from in our PanACEA database of genome-wide molecular perturbations in
high-fidelity models of human malignancies—to the non-oncogene dependencies of molecularly distinct, yet
coexisting subpopulations, representing either transformed, malignant cells or healthy cells recruited to the TME
to create a pro-malignant, immunosuppressive milieu, as dissected by single cell analyses. Targeting individual
subpopulations is becoming increasingly critical because the heterogeneity and plasticity of both transformed
and non-transformed TME subpopulations have emerged as, perhaps, the most fundamental obstacles to
achieving durable responses in cancer patients and distinct subpopulations appear to either have potentially
orthogonal drug sensitivities or to represent healthy, immunosuppressive cells that will require an entirely
different approach to targeting their recruitment to the TME rather than causing their demise. To accomplish
these goals, Project 3 will leverage data, models and reagents generated during the prior CSBC funding cycle
for the study of metastatic castration resistant prostate cancer (mCRPC) and pancreatic ductal adenocarcinoma
(PDAC), two aggressive, highly heterogeneous malignancies, with ≤ 20% 5-year survival. We will focus on
mCRPC and on its aggressive neuroendocrine subtype (NEPC) to explore a novel molecular triangulation
methodology (OncoLoop) designed to identify high-fidelity models—i.e., cell lines, organoids, genetically
engineered mouse models (GEMMs) and patient derived xenografts (PDXs)—to generate patient-relevant drug
perturbation profiles in vitro and to validate drugs predicted from patient-derived sample analysis in preclinical
models in vivo. We will then focus on 6 molecularly distinct malignant PDAC subpopulations—comprising
Lineage, Morphogenic, and Acinar to Ductal Metaplasia-like cells, each detected in either a MAPK pathway
active or inactive state—exploring multiple pro-malignant TME subpopulations (including tumor infiltrating T
regulatory cells, macrophages and fibroblasts), to identify small molecule inhibitors that effectively deplete them.
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Administrative Core
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批准号:10729384
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项目类别:
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资助金额:$5.4万
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财政年份:2023
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负责人:ANDREA CALIFANO
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依托单位:
Center for Cancer Systems Therapeutics (CaST)
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批准号:10729383
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项目类别:
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资助金额:$50.0万
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财政年份:2017
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Systematic Identification and Pharmacological Targeting of Tumor Dependencies for Precision Cancer Medicine
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依托单位:
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财政年份:2016
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资助金额:$199.19万
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依托单位:
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财政年份:2015
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依托单位:
海外基金