TY - JOUR
T1 - An integrative platform for three-dimensional quantitative analysis of spatially heterogeneous metastasis landscapes
AU - Guldner, Ian H.
AU - Yang, Lin
AU - Cowdrick, Kyle R.
AU - Wang, Qingfei
AU - Alvarez Barrios, Wendy V.
AU - Zellmer, Victoria R.
AU - Zhang, Yizhe
AU - Host, Misha
AU - Liu, Fang
AU - Chen, Danny Z.
AU - Zhang, Siyuan
N1 - Funding Information:
We would like to thank Dr. Charles Tessier at Indiana University School of Medicine South Bend and Richard Heil-Chapdelaine at Olympus USA for invaluable technical support. We would like to thank Dr. Calli A. Versagli for technical support and Zhang Lab members for insightful discussions of this project. This work was partially supported by NIH Pathway to Independence Award 5R00CA158066-05 (SZ), NIH 1R01CA194697- 01 (SZ), Walther Cancer Foundation Advancing Basic Cancer Research Grant II (SZ), Department of Defense W81XWH-15-1-0021 (SZ), Indiana CTSI core pilot fund (SZ), and NSF Grant CCF-1217906 (DZC). Dr. S. Zhang is the Nancy Dee Assistant Professor in Cancer Research at University of Notre Dame.
PY - 2016/4/12
Y1 - 2016/4/12
N2 - Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ.
AB - Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ.
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U2 - 10.1038/srep24201
DO - 10.1038/srep24201
M3 - Article
C2 - 27068335
AN - SCOPUS:84963801243
SN - 2045-2322
VL - 6
JO - Scientific reports
JF - Scientific reports
M1 - 24201
ER -