Project 1: How tumor ensemble models with two experimental models predict tumor dormancy & reactivation in cancers with gender and/or ethnic disparities

项目1:具有两个实验模型的肿瘤集成模型如何预测肿瘤休眠

基本信息

  • 批准号:
    10250465
  • 负责人:
  • 金额:
    $ 15.11万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2008
  • 资助国家:
    美国
  • 起止时间:
    2008-09-26 至 2024-08-31
  • 项目状态:
    已结题

项目摘要

Cancer is one of the world's major health problems. After chemotherapy or surgery, some cancers, e.g., breast cancer and melanoma, by a still mysterious mechanism persist, apparently dormant, for years before distant metastases appear and tumors reactivate and grow. Latent tumor cells may survive by their microenvi- ronment partially excluding T-cells that would attack them. Transplant studies indicate that, rather than static quiescence, these cells and the immune system are in dynamic equilibrium and periodic bursts of cell division and elimination sometimes transform unobservable micrometastases that accumulate genetic, epigenetic and proteomic changes into macrometastases. Details and a complete mechanism are lacking. There is a paucity of experimental or theoretical models that recapitulate latency or its reactivation. One mouse breast cancer model exhibits short-term latency & recurrence. Mathematical cancer models typically describe single tumor growth and/or metastasis generation or the probability of several mutations, but not dor- mancy. We posit a new mathematical population model for the dynamics of a large ensemble (from one or many patients) of tumors of all sizes subject to mitosis, cell death (immunity, chemo or immunotherapy, necro- sis, etc.) and metastasis. Ensembles naturally incorporate response variations of similar tumors. Predictions are probabilistic, proportional to the expected tumor number of each size and time from any initial size distribu- tion. Smaller tumors often respond better to chemotherapy than larger ones, likely due to the latter's more ac- cumulated mutations; tumor-size-dependent parameters model this most simply. Our model finds a surprising interaction among these size-dependent processes in an ensemble that generates intriguing new unexpected qualitative behavior, e.g., diffusion in tumor size space that for the first time predicts dormancy & recurrence. This proposal intimately integrates this new mathematical model with the BALB/c murine breast cancer and the clear, stripeless zebrafish melanoma systems; both allow live non-invasive monitoring of tumor numbers and sizes vs time without animal sacrifice. Our model fits existing human hepatocellular carcinoma and im- mune-suppressed & competent fish melanoma histograms at many times extremely well with only 3 parame- ters. We plan new fish experiments to control/tune the level of immunity so as to access and test parameters predicted to yield dormancy & recurrence. We shall carry out detailed experiments on the mouse breast cancer system, which may exhibit dormancy & recurrence naturally, and use it to test our model. We shall also attempt to modulate its immunity to access and test parameters predicted to yield dormancy & recurrence. Since both these cancers show both ethnic and gender disparities, we shall use melanoma cell with snps that recapitulate ethnicity-specific genetics and segregate (fish) data by gender so as to see if parameters show ethnic and/or gender specificity; this would carry over to dormancy & recurrence. Time and funds permitting, we shall also begin to look at the effect of tumor shape on its parameters' tumor size dependences.
癌症是世界上主要的健康问题之一。化疗或手术后,一些癌症,例如,

项目成果

期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)

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Richard Mark White其他文献

Richard Mark White的其他文献

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{{ truncateString('Richard Mark White', 18)}}的其他基金

Identification and characterization of cancer cell states by novel computational and experimental technologies - Resubmission - 1
通过新颖的计算和实验技术识别和表征癌细胞状态 - 重新提交 - 1
  • 批准号:
    10650774
  • 财政年份:
    2022
  • 资助金额:
    $ 15.11万
  • 项目类别:
Identification and characterization of cancer cell states by novel computational and experimental technologies - Resubmission - 1
通过新颖的计算和实验技术识别和表征癌细胞状态 - 重新提交 - 1
  • 批准号:
    10448890
  • 财政年份:
    2022
  • 资助金额:
    $ 15.11万
  • 项目类别:
Lipid programs in melanocyte transformation
黑素细胞转化中的脂质程序
  • 批准号:
    10357757
  • 财政年份:
    2020
  • 资助金额:
    $ 15.11万
  • 项目类别:
Lipid programs in melanocyte transformation
黑素细胞转化中的脂质程序
  • 批准号:
    10083205
  • 财政年份:
    2020
  • 资助金额:
    $ 15.11万
  • 项目类别:
Lipid programs in melanocyte transformation
黑素细胞转化中的脂质程序
  • 批准号:
    9886716
  • 财政年份:
    2020
  • 资助金额:
    $ 15.11万
  • 项目类别:
Dissecting the complexity of metastasis with mathematical models and quantitative experiments with in zebrafish
用数学模型和斑马鱼定量实验剖析转移的复杂性
  • 批准号:
    10471185
  • 财政年份:
    2018
  • 资助金额:
    $ 15.11万
  • 项目类别:
Dissecting the complexity of metastasis with mathematical models and quantitative experiments with in zebrafish
用数学模型和斑马鱼定量实验剖析转移的复杂性
  • 批准号:
    10228581
  • 财政年份:
    2018
  • 资助金额:
    $ 15.11万
  • 项目类别:
Evolutionary dynamics of melanoma metastasis
黑色素瘤转移的进化动力学
  • 批准号:
    8568851
  • 财政年份:
    2013
  • 资助金额:
    $ 15.11万
  • 项目类别:
The role of melanocyte precursors in zebrafish pigmentation disorders
黑素细胞前体在斑马鱼色素沉着疾病中的作用
  • 批准号:
    8207200
  • 财政年份:
    2009
  • 资助金额:
    $ 15.11万
  • 项目类别:
The role of melanocyte precursors in zebrafish pigmentation disorders
黑素细胞前体在斑马鱼色素沉着疾病中的作用
  • 批准号:
    8524634
  • 财政年份:
    2009
  • 资助金额:
    $ 15.11万
  • 项目类别:

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