Computational pathology software for integrative cancer research with three-dimensional digital slides

Information

  • Research Project
  • 10238813
  • ApplicationId
    10238813
  • Core Project Number
    U01CA242936
  • Full Project Number
    5U01CA242936-03
  • Serial Number
    242936
  • FOA Number
    PAR-15-332
  • Sub Project Id
  • Project Start Date
    8/1/2019 - 4 years ago
  • Project End Date
    7/31/2022 - a year ago
  • Program Officer Name
    GANGULY, ANIRUDDHA
  • Budget Start Date
    8/1/2021 - 2 years ago
  • Budget End Date
    7/31/2022 - a year ago
  • Fiscal Year
    2021
  • Support Year
    03
  • Suffix
  • Award Notice Date
    7/9/2021 - 2 years ago
Organizations

Computational pathology software for integrative cancer research with three-dimensional digital slides

PROJECT SUMMARY: Tissue-based investigation remains a cornerstone of cancer research. With the advent of cost-effective digital scanners, large-scale quantitative investigations are now feasible using high throughput analysis of two- dimensional (2D) image datasets. However, 2D image analytics has its limitations, since pathologic diseases occur in three-dimensional (3D) space and 2D representations suffer from significant information loss. There are major gaps for 3D analytical digital pathology, including lack of image analysis tools to quantitatively process 3D data volumes and lack of an effective and scalable data management and analytical infrastructure to model, curate, query and mine large-scale spatial pathology features and biomarkers. We propose to fill these gaps with a new informatics solution directed at better understanding of 3D tumor micro-environments, with driving use cases on immunotherapy study for enhanced immune cell infiltration for pancreatic ductal adenocarcinoma (PDAC) and pathophysiological study of rapid tumor progression in brain tumor glioblastoma (GBM). In line with Human Tumor Atlas program, we propose to create a novel and comprehensive 3D digital pathology analytics framework to quantitatively analyze spatial patterns of pathologic hallmarks and biomarkers related to disease progression in an authentic 3D tissue environment with quantitative digital pathology image volume processing, spatially integrative histology-molecular image analysis, large-scale spatial data analytics, and key cellular compartment tracking for clinical treatment response test and immunotherapy development. To enable a wide use of informatics tools for 3D digital pathology imaging data in cancer research, we will further upgrade a comprehensive, web-based system for multi-modality microscopy image management, dissemination, and visualization. We will leverage a large set of informatics tools and algorithms we have developed for microscopy image analysis, integrative translational cancer research, pathology spatial analytics, and high performance computing in the past 14 years. The developed tools will be tested and used by a suite of well-funded cancer research projects on pancreatic cancer, brain tumor, head and neck, liver, and lung cancers. The proposed informatics tools will enable precise and comprehensive characterizations of the histologic, molecular, cellular and tissue-level interactions at critical transition stages in cancer progression. They will also allow for a precise interrogation of physical and spatial signatures of immune cell infiltration into tumors, and the interactions between the host immune system and tumor cell metastasis within a complex tumor micro-environment architecture, essential for immunotherapy development. The completion of the proposed study will boost our informatics technology capabilities for large scale microscopy image analytics, help cancer researchers accurately understand cancer biology and progression mechanisms, and enable clinicians an easy access to clinically relevant information from large scale microscopy images for computer based diagnosis and therapeutic development.

IC Name
NATIONAL CANCER INSTITUTE
  • Activity
    U01
  • Administering IC
    CA
  • Application Type
    5
  • Direct Cost Amount
    301369
  • Indirect Cost Amount
    69854
  • Total Cost
    308056
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    394
  • Ed Inst. Type
    SCHOOLS OF ARTS AND SCIENCES
  • Funding ICs
    NCI:308056\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    ZCA1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    GEORGIA STATE UNIVERSITY
  • Organization Department
    BIOSTATISTICS & OTHER MATH SCI
  • Organization DUNS
    837322494
  • Organization City
    ATLANTA
  • Organization State
    GA
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    303023999
  • Organization District
    UNITED STATES