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Building health intelligence with complex data on tumor cell states and therapy resistance

Building health intelligence with complex data on tumor cell states and therapy resistance
利用肿瘤细胞状态和治疗耐药性的复杂数据构建健康情报
批准号:
418179595
负责人:
Dr. Susanne Horn
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Clinical Research Units
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:

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中文摘要
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英文摘要
A comprehensive characterization of the molecular biological background and immunological pathways involved in the immunotherapy of cancer, in our case melanoma, are the basis for developing diagnostics and therapeutics. We perform research in the context of modern immune checkpoint inhibitors and strive to establish and validate predictive markers that can detect long-term survival benefit in a subpopulation of patients. Our biosampling and extensive annotation of clinical data allows us to perform multivariate analyses with additional co-variables such as mutational burden, LDH levels and immune infiltrates. Within the anticipated profiling of molecular tumor heterogeneity of bulk tumors and single cells we are especially interested in site-related molecular differences of melanoma metastases from brain, lung, and skin. We will further expand our data collection by annotating epigenetic and metabolomic information to already annotated datasets, with e.g. methylation, HLA allele status and toxicity profiles. These analyses are empowered by the development of software and easy-to-use webtools extending our PhenoTImE data share (‘translational hub’). Specifically, we aim at extending the Cox proportional hazards model with a bayesian framework to better predict time-to-event data across multiple cohorts as artificial neural networks do not yet perform well to predict survival under immune checkpoint blockade from transcriptomics in various analyzed melanoma cohorts. To this end, the facilitation of exchanging large datasets is crucial. Hence, we support the merging of quantifications from raw ‘omics’ data with phenotypic profiles generated by us and other projects in the research unit. Thereby we aid collaborative, timely analyses with the necessary interconnection of data and metadata. We also administrate and maintain the compute-server cluster that we established in the first funding phase for the analysis of datasets open to all members of the consortium and to collaborators. With these efforts, we extend our research to additional tumor entities beyond melanoma where our pipelines eventually will merge into larger institutional platforms such as multi-omics tumor tissue profiling and inter-disciplinary tumor boards.
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会议论文
The Dark Matter of the Immunopetidome: Cryptic Peptides as Tumor Antigens in Melanoma.
Rapidly rotating Rayleigh-Bénard convection in liquid metals
国内基金
海外基金
基于One Health理念的狂犬病传播风险多源驱动机制与协同防控策略研究
重大传染病防治关键技术研究-重大传染病防治关键技术研究-基于One Health的SFTS防治技术体系构建与应用
  • 批准号:
    2025C02186
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2025
  • 负责人:
    孙继民
  • 依托单位:
人兽共患病One Health防控决策路径研究
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    5.0万元
  • 批准年份:
    2024
  • 负责人:
    张晓溪
  • 依托单位:
基于 One Health 策略的 mcr 阳性多重耐药 ST34 型沙门菌的流行传播机制及溯源研究
  • 批准号:
    Y24H190002
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    罗琦霞
  • 依托单位: