Disease Progression Modeling of Bladder Cancer
膀胱癌的疾病进展模型
基本信息
- 批准号:10518025
- 负责人:
- 金额:$ 50.75万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-08-01 至 2027-07-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAffectAneuploidyAnimalsBackBioinformaticsBiologicalBreast Cancer ModelCancer DiagnosticsCancer ModelCause of DeathCessation of lifeCharacteristicsClassificationClinicalClinical ManagementClinical Trials DesignCommunitiesComplexDataData SetDerivation procedureDevelopmentDiagnosticDiseaseDisease ManagementDisease ProgressionDisease modelEpigenetic ProcessEventEvolutionFoundationsFutureGene Expression ProfilingGene MutationGenesGeneticGoalsHeterogeneityHumanIndividualInstitutesInterdisciplinary StudyInvestigationLearningLesionLifeMalignant - descriptorMalignant NeoplasmsMalignant neoplasm of urinary bladderMammary Gland ParenchymaMapsModelingMolecularMolecular ProfilingMutationOperative Surgical ProceduresOutcomePathologicPathway interactionsPatientsPatternPhenotypePrevalenceProcessProgressive DiseaseRecurrenceResearchResearch DesignResourcesSamplingSeriesSpecimenStructureSubgroupSystemSystemic TherapyTherapeuticTherapeutic InterventionTimeTissue SampleTissuesTreesTumor BiologyTumor TissueValidationVisualizationWorkanticancer researchbasebreast cancer progressioncancer diagnosiscarcinogenesiscomputational suitecomputerized toolsdesigndisease natural historyexperimental studygenomic datahigh dimensionalityimprovedinnovationinsightmalignant breast neoplasmmathematical modelmolecular markermolecular subtypesmultidimensional datanovelnovel strategiespressureprognostictargeted treatmenttheoriestooltumortumor progression
项目摘要
PROJECT SUMMARY/ABSTRACT
Carcinogenesis may be viewed as a multistep evolutionary process characterized by accumulation of
genetic and epigenetic alterations, driven by selective pressures imposed by the microenvironment. The
delineation of tumor evolution would provide invaluable insights into tumor biology and lay a foundation for
the development of improved diagnostics, prognostics and targeted therapeutics.
Time-series data are ideal for deriving models of dynamic progression, but this is impossible to collect in
human cancer because of the need for timely surgical intervention and systemic therapy, which alter the
natural history of the disease and exert selection pressures that affect tumor evolution. To overcome the
human serial sampling issue, we have devised a computational strategy to understand cancer evolution by
deriving pseudo time-series data from ‘static’ samples (excised tissue specimens). The design is based on
the rationale that each sample can provide a snapshot of the disease process, and if the number of samples
is sufficiently large we can recover a visualization of disease progression. We demonstrated the utility of the
developed pipeline - referred to as CancerMapp - by applying it to the analysis of gene expression data from
over 9,000 breast tissue samples. Breast cancer progression modeling identified 2 major trajectories to
malignancy – an early split to basal tumors, and a continuum through luminal tumors. The computational
approach and the breast cancer model concept have since been validated in independent studies, and our
findings have provided the impetus for a number of investigations at our institute and by colleagues in the
field.
Built logically on our previous work, we now propose a large-scale interdisciplinary research plan to derive a
progression model for bladder cancer (BLCA). BLCA is among the five most common malignancies
worldwide. In the US alone, new cases for 2018 are estimated at 72,500 with estimated deaths at over
15,000, figures that are anticipated to increase in the near future. Classification of BLCA into multiple
molecular subtypes has recently been proposed and has the potential to impact clinical management.
Nonetheless, significant biologic subgroup heterogeneity remains, and more work is needed before a unified
classification system can gain wide acceptance. More importantly, there is, as yet, no understanding of the
inter-relationships between subtypes. Insights into how subtypes are related and how cancer evolution
influences the observed changes in molecular pathologic phenotype is the next level of analysis required
and is the focus of this proposal.
The proposed work will inform a range of research directions that were previously unattainable. The
derivation of a BLCA roadmap and the identification of pivotal molecular events that drive stepwise cancer
progression will provide new insights into tumor biology and guide the development of improved cancer
diagnostics, prognostics and targeted therapeutics. Annotated progression maps can also guide the design
of clinical trials and animal studies to focus on pivotal points of cancer development, which may yield the
best return with limited resources.
项目总结/文摘
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
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Steve Goodison其他文献
Steve Goodison的其他文献
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{{ truncateString('Steve Goodison', 18)}}的其他基金
Prognostic analysis and progression modeling of basal-like breast cancer using multi-region sequencing
使用多区域测序对基底样乳腺癌进行预后分析和进展建模
- 批准号:
10586445 - 财政年份:2023
- 资助金额:
$ 50.75万 - 项目类别:
Advanced Computational Approaches to Delineating Dynamic Cancer Progression Processes by Using Massive Static Sample Data
使用大量静态样本数据描绘动态癌症进展过程的高级计算方法
- 批准号:
10328873 - 财政年份:2020
- 资助金额:
$ 50.75万 - 项目类别:
Advanced Computational Approaches to Delineating Dynamic Cancer Progression Processes by Using Massive Static Sample Data
使用大量静态样本数据描绘动态癌症进展过程的高级计算方法
- 批准号:
10546466 - 财政年份:2020
- 资助金额:
$ 50.75万 - 项目类别:
Translation of a Clinical Molecular Diagnostic Assay for Bladder Cancer
膀胱癌临床分子诊断检测的转化
- 批准号:
10203860 - 财政年份:2017
- 资助金额:
$ 50.75万 - 项目类别:
Translation of a Clinical Molecular Diagnostic Assay for Bladder Cancer
膀胱癌临床分子诊断检测的转化
- 批准号:
9980305 - 财政年份:2017
- 资助金额:
$ 50.75万 - 项目类别:
Development of molecular assays for non-invasive bladder cancer detection
开发用于非侵入性膀胱癌检测的分子测定方法
- 批准号:
8453158 - 财政年份:2013
- 资助金额:
$ 50.75万 - 项目类别:
Development of molecular assays for non-invasive bladder cancer detection
开发用于非侵入性膀胱癌检测的分子测定方法
- 批准号:
8823877 - 财政年份:2013
- 资助金额:
$ 50.75万 - 项目类别:
Towards a non-invasive molecular test for bladder cancer
膀胱癌的非侵入性分子检测
- 批准号:
8875841 - 财政年份:2007
- 资助金额:
$ 50.75万 - 项目类别:
Towards a non-invasive molecular test for bladder cancer
膀胱癌的非侵入性分子检测
- 批准号:
7305500 - 财政年份:2007
- 资助金额:
$ 50.75万 - 项目类别:
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