Rational design of drug combinations to target chemotherapy resistance in high-grade serous ovarian cancer via metabolomic profiling of patient-derived organoids
Rational design of drug combinations to target chemotherapy resistance in high-grade serous ovarian cancer via metabolomic profiling of patient-derived organoids
批准号:
10201800
负责人:
Jan Krumsiek
金额:
$8.48万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-07-01 至 2023-06-30
关键词:
AffectAlgorithmsBiochemical PathwayCancer EtiologyCancer ModelCancer PatientCarboplatinCellsCessation of lifeChemoresistanceClinicalClinical TrialsCollaborationsCombined Modality TherapyComputational algorithmComputer ModelsDataDiseaseDisease ResistanceDrug CombinationsDrug DesignDrug resistanceFailureFresh TissueFutureGenesIn VitroInterventionLinkMalignant neoplasm of ovaryMapsMetabolicMetabolic PathwayMetabolismModelingMolecularMutationNatureOrganoidsPaclitaxelPathway interactionsPatientsPharmaceutical PreparationsPharmacotherapyPhasePilot ProjectsPrimary NeoplasmProcessRefractoryRegulator GenesRelapseResistanceResistance profileRunningSamplingSerousSignal PathwaySignaling ProteinStatistical Data InterpretationTechnologyTestingTherapeuticTissue SampleTissuesTranslationsTumor BurdenTumor TissueWomanbasecancer cellcancer subtypescancer therapychemotherapeutic agentchemotherapycohortdesigndrug candidatedrug testingimprovedin silicoin vitro Modelin vivo evaluationmetabolic profilemetabolomicsmultidisciplinaryneoplastic cellnovelpatient responseresistance mechanismresponsetumor
中文摘要
项目
总结/摘要
这
耐
疾病
率
女人,
代谢组
电阻,
的
算法
到
监管
的
类器官
识别
疗法
该项目旨在开发一个新的跨学科框架,用于设计药物的重编程,
肿瘤进入反应状态。该试点将重点关注高级别浆液性卵巢癌,
多达20%的患者对卡铂的初级治疗难治,并且80%复发
最初有反应的病人。我们将从12例难治性和12例反应性患者中获得原发性肿瘤组织
培养患者来源的类器官作为患者肿瘤的个性化体外模型,
对组织样本和类器官进行分析。这将使我们能够识别代谢状态的
这将精确定位耐药肿瘤逃避作用的分子逃逸机制,
化疗剂。在项目的第二阶段,我们将开发一种新的计算
预测哪种药物最有可能将肿瘤重新编程到卡铂敏感状态。
为此,我们将把耐药的代谢谱映射到一个整合的代谢、信号和
然后识别其靶点位于所需效果上游的药物。最后一部分
在该项目中,我们将选择得分最高的预测,并在实验上验证它们。
具体地说,我们希望通过用以下物质预处理它们来使抗性类器官产生反应:
毒品如果成功的话,这个项目将为组合的合理设计建立一个新的范例
在难治性肿瘤中。
F
F
英文摘要
Project
Summary/Abstract
This
resistant
disease
rates
women,
metabolomics
resistance,
of
algorithm
To
regulatory
of
organoids.
identified
therapies
project aims to develop a novel, interdisciplinary framework for the designed reprogramming of drug-
tumors towards a responsive state. This pilot will focus on high-grade serous ovarian cancer, a
with up to 20% o patients being refractory to primary treatment with carboplatin, and 80% relapse
of initially responsive patients. We will obtain primary tumor tissue rom 12 refractory and 12 responsive
grow patient-derived organoids as a personalized in vitro model of the patients' tumors, and perform
profiling on both tissue samples and organoids. This will allow us to identify metabolic states of
which will pinpoint the molecular escape mechanisms resistant tumors employ to evade the action
the chemotherapeutic agent. In the second phase of the project, we wil l develop a novel computational
that predicts which other drug is most likely to reprogram the tumor into a carboplatin-sensitive state.
this end, we will map the metabolic profiles of resistance onto an integrated metabolic, signaling and
pathway map to then identify drugs whose targets are upstream of the desired effect. In the last part
the project, we will choose the highest-scoring predictions and validate them experimentally on the
Specifically, we expect to render resistant organoids responsive by pretreating them with the
drugs. If successful, this project will establish a new paradigm for the rational design of combination
in refractory tumors.
f
f
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Rational design of drug combinations to target chemotherapy resistance in high-grade serous ovarian cancer via metabolomic profiling of patient-derived organoids
-
批准号:10401850
-
项目类别:
-
资助金额:$8.48万
-
财政年份:2021
-
负责人:Jan Krumsiek
-
依托单位:
海外基金