Funding Agency:
NIH / NCI
Grant No:
UH2 CA263954
Title:
Imaging the native 3D architecture of pancreatic and breast tumor patient tissue at single-cell resolution
Abstract:
Cancer remains the second-leading cause of adult death in the United States, yet the mechanisms by which cancerous growths are initiated and how crucial transitions such as metastasis and therapeutic resistance occur are not well understood. Significant progress has been made in the multiplexed analysis of solid tumors through the use of single-cell sequencing and spatio-molecular mapping techniques. However, despite the unique insights into tumor heterogeneity these methods have afforded, they are limited to two-dimensional (2D) thin analyses which provide little information on the native three-dimensional architecture of the tumor. Serial reconstruction can provide some three-dimensional context, but such approaches are both inefficient in terms of sample throughput and are inherently destructive to the tissue architecture. We propose a cross-disciplinary, approach to quantitatively characterize the native three-dimensional architecture of human solid tumor tissue from triple negative breast cancer (TNBC) and pancreatic ductal adenocarcinoma (PDAC) patients using a combination of the state-of-the art, yet mature technologies of tissue clearing, immunofluorescence and in situ hybridization labeling, and high-resolution lightsheet fluorescence microscopy. Analysis of these tissue volumes will enable the elucidation of the spatial interactome of different tumor, immune and stromal cells that give rise to tumor heterogeneity as well as their interactions with components of the tumor microenvironment. Our Specific Aims are (1) to image the three-dimensional spatial distribution of tumor, immune and stromal cells in relation to vasculature, lymphatics and the extracellular matrix in native solid tumor tissue from human pancreatic and breast malignancies using a combination of tissue clearing, immunofluorescence, in situ hybridization and 3D lightsheet microscopy, and (2) to develop a computational pipeline to build three-dimensional spatial maps of protein expression and RNA transcript localization in intact solid tumor tissue from human pancreatic and breast malignancies. The innovation of the proposed work lies in our cross-disciplinary strategy of combining the cutting- edge tissue clearing, multiplexed labelling and high-resolution lightsheet microscopy to better understand the native three-dimensional architecture of solid tumors. Specifically, by classifying and quantitating previously unknown three-dimensional features of solid tumor tissue we will be able to relate the spatial organization of the tumor to genomic and proteomic data taken from the same specimen. The significance of this proposal is that successful three-dimensional characterization of human tumor tissues will enable key insights to be derived on both intra- and inter-tumor heterogeneity thus facilitating the identification of cell-cell and cell-microenvironment interactions that could serve as potential therapeutic targets thus providing new routes to treatments to decrease patient mortality and improve quality of life.