Integrating cancer genomics and spatial architecture of tumor infiltrating lymphocytes

整合癌症基因组学和肿瘤浸润淋巴细胞的空间结构

基本信息

  • 批准号:
    10637960
  • 负责人:
  • 金额:
    $ 44.52万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-04-11 至 2027-03-31
  • 项目状态:
    未结题

项目摘要

ABSTRACT Tumor infiltrating lymphocytes (TILs) are an important component of the immune cells that reside in the tumor microenvironment (TME). The type and number of TILs in the TME have an impact on overall survival and are an indicator of response to immunotherapy. Despite their importance as an indicator of a patient’s immune response to cancer, there are multiple challenges for analyzing TILS from large population data sets involving thousands of samples. There is a lack of methods that can automate an analysis of histopathologic images for different features such as the spatial distribution of TILs, their topological interactions with their neighboring cells in the TME and their association with specific clinical outcomes. Even more challenging is integrating TIL metrics with cancer genomic data. Most other methods provide qualitive metrics of TILs and frequently rely on manual inspection from pathologists – this approach lacks scalability and is subject to observer bias. To address these challenges, we developed a computational framework that uses a deep learning model to identify multiple cell types from histopathology images. The major innovation of our approach is molecular label transferring that annotates tens of thousands of small areas extracted from histopathology images without manual inspections. This approach is highly accurate, efficient, scalable and readily automated for the analysis of millions of images. The objective of this project is to address a key challenge in the application of deep learning to histopathological image: large number of labeled images as training data set. We have three specific aims to 1) identify spatial quantification of TILs from over 10,000 histopathological images from the Cancer Genome Atlas Project; 2) correlate TIL metrics with clonal tumor mutation burden (TMB); 3) determine association of TILs with immune checkpoint blockade responses. This research is significant because our approach enables for a comprehensive characterization of TILs from histopathological images at cellular level, using data that is commonly accessible in clinical settings and can be readily integrated with cancer genomic data.
摘要

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Hanlee P Ji其他文献

Improving bioinformatic pipelines for exome variant calling
  • DOI:
    10.1186/gm306
  • 发表时间:
    2012-01-01
  • 期刊:
  • 影响因子:
    11.200
  • 作者:
    Hanlee P Ji
  • 通讯作者:
    Hanlee P Ji

Hanlee P Ji的其他文献

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{{ truncateString('Hanlee P Ji', 18)}}的其他基金

K-mer indexing for pan-genome reference annotation
用于泛基因组参考注释的 K-mer 索引
  • 批准号:
    10793082
  • 财政年份:
    2023
  • 资助金额:
    $ 44.52万
  • 项目类别:
Determine the mechanisms of acquired brain-tropism
确定获得性脑向性的机制
  • 批准号:
    10813237
  • 财政年份:
    2023
  • 资助金额:
    $ 44.52万
  • 项目类别:
Single cell modeling of cancer mutations
癌症突变的单细胞建模
  • 批准号:
    10612689
  • 财政年份:
    2023
  • 资助金额:
    $ 44.52万
  • 项目类别:
Project 1 - Molecular and Cellular Determinants of High Risk Gastric Precancerous Lesions
项目1——高危胃癌癌前病变的分子和细胞决定因素
  • 批准号:
    10715762
  • 财政年份:
    2023
  • 资助金额:
    $ 44.52万
  • 项目类别:
Core A: Administrative
核心A:行政
  • 批准号:
    10715765
  • 财政年份:
    2023
  • 资助金额:
    $ 44.52万
  • 项目类别:
Determine the mechanisms of acquired brain-tropism
确定获得性脑向性的机制
  • 批准号:
    10706493
  • 财政年份:
    2021
  • 资助金额:
    $ 44.52万
  • 项目类别:
Determine the mechanisms of acquired brain-tropism
确定获得性脑向性的机制
  • 批准号:
    10272359
  • 财政年份:
    2021
  • 资助金额:
    $ 44.52万
  • 项目类别:
Multimodal iterative sequencing of cancer genomes and single tumor cells
癌症基因组和单个肿瘤细胞的多模式迭代测序
  • 批准号:
    10363694
  • 财政年份:
    2021
  • 资助金额:
    $ 44.52万
  • 项目类别:
Multimodal iterative sequencing of cancer genomes and single tumor cells
癌症基因组和单个肿瘤细胞的多模式迭代测序
  • 批准号:
    10112576
  • 财政年份:
    2021
  • 资助金额:
    $ 44.52万
  • 项目类别:
Multimodal iterative sequencing of cancer genomes and single tumor cells
癌症基因组和单个肿瘤细胞的多模式迭代测序
  • 批准号:
    10576304
  • 财政年份:
    2021
  • 资助金额:
    $ 44.52万
  • 项目类别:

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