Leveraging Omics-Based Computational Approaches to Identify and Validate Novel Therapeutic Candidates for Endometriosis
利用基于组学的计算方法来识别和验证子宫内膜异位症的新治疗候选药物
基本信息
- 批准号:10308250
- 负责人:
- 金额:$ 44.18万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-08-01 至 2026-07-31
- 项目状态:未结题
- 来源:
- 关键词:AffectAnimal ModelBar CodesBehavioralBioinformaticsBiological AssayCOVID-19CellsClinicalClinical TrialsCombination Drug TherapyCombined Modality TherapyCytometryDataDatabasesDermatomyositisDevelopmentDiseaseDrug CombinationsDrug ScreeningDrug TargetingDysmenorrheaDyspareuniaEndometrialEquipmentEstrogensExcisionFunctional disorderGene AbnormalityGene ExpressionGene Expression ProfileGenomicsGoalsHormonalHormonesHumanImmuneIn VitroInfertilityInflammatoryInflammatory Bowel DiseasesInterleukin-1 betaInterleukin-6LibrariesMalignant neoplasm of lungMapsMediatingMedicalMenstrual cycleModelingMolecularMolecular ProfilingNetwork-basedNon-Steroidal Anti-Inflammatory AgentsOperative Surgical ProceduresPainPathogenesisPelvic PainPelvisPharmaceutical PreparationsPhasePhenotypePre-Clinical ModelPremature BirthProcessPropertyProstaglandinsPublic DomainsQuality of lifeRelapseResearchRodent ModelSignal PathwaySignal TransductionSymptomsTNF geneTechniquesTechnologyTeenagersTestingTherapeuticTissuesTrainingTranslational ResearchValidationWomanbasecell typechronic pelvic paincommunity engagementcytokinedrug developmentdrug repurposingendometriosisimprovedin silicoin vivoinnovationinterestmultidisciplinarynovelnovel strategiesnovel therapeuticspre-clinicalpreclinical developmentreduce symptomsresponsescreeningskillstherapeutic candidatetranscriptomics
项目摘要
ABSTRACT – PROJECT 3
Endometriosis is a common, estrogen-dependent, inflammatory disorder that causes debilitating chronic pelvic
pain including severe dysmenorrhea and dyspareunia, infertility, and a reduced quality of life for 176 million
women and teens worldwide. Treatment of endometriosis-associated pain is mainly surgical and/or medical.
Surgical removal of disease results in 50% relapse of pain within 2-5 years. Medical treatments, largely
unchanged over decades, comprise nonsteroidal anti-inflammatory drugs (NSAIDs) and hormones that lower
estrogen levels or oppose its actions, and result in variable symptom relief. The development and availability of
large-scale genomic, transcriptomic, and other molecular profiling technologies, in combination with the
deployment of the network concept of drug targets and the power of phenotypic screening, provide an
unprecedented opportunity to advance rational drug repurposing and data-driven development of drug
combinations. The goal of Project 3 is to leverage endometriosis transcriptomics data combined with publicly
available drug screening data and apply a computational drug-repurposing pipeline to identify single agent and
combination therapies from existing drugs based on expression reversal perturbing molecular networks away
from disease-associated cellular dysfunction, and validate select drugs in human endometrial cells in vitro and
an animal model of endometriosis pain. In Aim 1, we will use transcriptomic-based computational drug-
repurposing to identify potential new single agent and combination therapeutics based on expression reversal
leveraging public transcriptomics data. Our hypothesis is that the inverse expression profiles between the drug
repositioning candidates and the disease signatures will result in therapeutic predictions. In Aim 2, we will
determine the capacity of compounds of interest (COIs) to inhibit inflammatory signaling responses in primary
human immune and endometrial cells through the use of an ex vivo high-throughput mass-tag barcoding assay.
We hypothesize that the most promising COIs identified in silico (Aim 1) will improve endometriosis symptoms
by inhibiting pro-inflammatory signaling responses in endometrial and/or immune cells. Finally, in Aim 3 we will
determine the efficacy of compounds of interest to alleviate pain in a preclinical endometriosis model. We
hypothesize that the COIs identified for the treatment of endometriosis will alter the endometriotic
microenvironment to alleviate pain. We anticipate this study will serve as the basis for studies on newly
discovered novel targets and drug-repurposing as well as functional validation in endometrial tissue as well as
testing in preclinical models, and if successful, clinical trials for endometriosis-associated pain in women. We
hope that this novel approach will change the paradigm of “one size fits all” hormonal treatment for
endometriosis-associated pelvic pain and expand therapeutic options to new therapies and established therapies
repurposed to improve the lives of millions of affected women and teens and expand the research pipeline in
this space.
摘要-项目3
项目成果
期刊论文数量(0)
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Marina Sirota其他文献
Marina Sirota的其他文献
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{{ truncateString('Marina Sirota', 18)}}的其他基金
Leveraging Omics-Based Computational Approaches to Identify and Validate Novel Therapeutic Candidates for Endometriosis
利用基于组学的计算方法来识别和验证子宫内膜异位症的新治疗候选药物
- 批准号:
10458760 - 财政年份:2021
- 资助金额:
$ 44.18万 - 项目类别:
Leveraging Omics-Based Computational Approaches to Identify and Validate Novel Therapeutic Candidates for Endometriosis
利用基于组学的计算方法来识别和验证子宫内膜异位症的新治疗候选药物
- 批准号:
10699970 - 财政年份:2021
- 资助金额:
$ 44.18万 - 项目类别:
An Integrative Multi-Omics Approach to Elucidate Sex-Specific Differences in Alzheimers Disease
阐明阿尔茨海默病性别特异性差异的综合多组学方法
- 批准号:
10172820 - 财政年份:2018
- 资助金额:
$ 44.18万 - 项目类别:
An Integrative Multi-Omics Approach to Elucidate Sex-Specific Differences in Alzheimers Disease
阐明阿尔茨海默病性别特异性差异的综合多组学方法
- 批准号:
10434004 - 财政年份:2018
- 资助金额:
$ 44.18万 - 项目类别:
Elucidating the Role of the Genetic and Environmental Determinants of Preterm Birth Using Integrative Computational Approaches
使用综合计算方法阐明早产的遗传和环境决定因素的作用
- 批准号:
9324358 - 财政年份:2016
- 资助金额:
$ 44.18万 - 项目类别:
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