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Bioinformatics Core

Bioinformatics Core
生物信息学核心
批准号:
10733394
负责人:
CLIFFORD G TEPPER
金额:
$4.02万
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:
2023-08-01 至 2028-07-31
关键词:
Antineoplastic AgentsAsian AmericansBiochemicalBioinformaticsBiologicalBiometryBiostatistics Shared ResourceCaliforniaCancer ModelCancer PatientCharacteristicsClinicalCollaborationsComprehensive Cancer CenterConduct Clinical TrialsCorrelation StudiesDataData AnalysesData AnalyticsData SetDedicationsDevelopmentDrug CombinationsDrug ModelingsEpidermal Growth Factor ReceptorFrequenciesGene ExpressionGene MutationGenesGeneticGenomicsGoalsHuman ResourcesIn VitroIndividualInfrastructureLatino PopulationLightLinkLungLung AdenocarcinomaLung NeoplasmsMalignant NeoplasmsMalignant neoplasm of lungMethodsMinorityModelingMolecularMutationNative Hawaiian or Other Pacific IslanderNon-Small-Cell Lung CarcinomaPatientsPerformancePharmaceutical PreparationsPilot ProjectsPopulationPropertyRegimenResearch DesignResearch PersonnelResearch Project GrantsResistanceSamplingServicesSmokerStatistical ModelsStomachStomach NeoplasmsTestingTexasTherapeuticTherapeutic AgentsTranscriptTreatment EfficacyTumor SubtypeUniversitiesanalysis pipelinebiobankdata integrationdata repositorydata sharingdesigndrug testingefficacy testingethnic minorityexome sequencinggenetic variantgenomic datahigh throughput analysisimprovedindividual patientmalignant stomach neoplasmminority patientmolecular markermutantnever smokernext generation sequencingnovelnovel therapeuticspatient derived xenograft modelpre-clinicalprecision oncologyracial minorityrelational databaserepositoryresponsetargeted treatmenttherapeutic targettranscriptome sequencingtreatment responsetreatment strategytumortumor heterogeneitytumor xenograft

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PROJECT SUMMARY The overall objective of the proposed Diversity PDX Development and Testing Center (D-PDTC) is directed at improving cancer precision medicine approaches for gastric and lung cancers. This will be achieved through the large-scale development and molecular characterization of over 120 new minority gastric and lung PDX tumor models and to utilize these for in vitro and pre-clinical PDX trials to test the efficacy of molecularly-matched therapeutics administered as single agents or combination. Statistical testing for drug-responsiveness will be performed, as well as the application of data integration strategies that relate treatment responses with molecular characteristics of individual PDXs and patients’ tumors. The goal of Bioinformatics Core (UBC) is to provide extensive data analytic support for the proposed studies at multiple stages including study design, molecular characterization of the PDXs, target selection, and statistical correlation and modeling of drug responses. The UBC will be established, and have considerable capabilities, by bringing together key personnel with strengths in genomics, bioinformatics, and biostatistics, and by leveraging the existing infrastructure at the UCD Comprehensive Cancer Center, specifically the Biorepository, Genomics, and Biostatistics Shared Resources. The UBC will facilitate the seamless integration of our U54 through dynamic interactions with its investigators, and via the implementation of a dedicated UCaTS Bioinformatics Core relational database that will serve as a data repository and interface for linking project design, sample tracking, data analysis, and eventual data sharing. For genetic characterization of the PDX models, and associated patient tumors, we will apply a suite of established bioinformatics analysis pipelines implemented on a high-performance ultra-rapid next-generation sequencing data analysis platform for processing whole-exome sequencing and RNA-sequencing data to generate the fundamental results datasets consisting of fully annotated 1) genomic variants and 2) transcripts with corresponding expression values. Additional tumor properties that can figure prominently in guiding therapeutic decisions, such as mutational burden will also be defined. Subsequently, integrative bioinformatics approaches will be applied for target prioritization and treatment matching, which will be followed by biostatistical analyses to evaluate both drug responses and the accuracy of novel molecular biomarkers. The UBC will also collaborate with the PDXNet, PDMR-FNLCR, and PDTCs for data sharing and participation in PDX trials.
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