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

项目总结:

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.