Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images

We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between differe...

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Veröffentlicht in:Cancer research (Chicago, Ill.) Jg. 77; H. 21; S. e71
Hauptverfasser: Spagnolo, Daniel M, Al-Kofahi, Yousef, Zhu, Peihong, Lezon, Timothy R, Gough, Albert, Stern, Andrew M, Lee, Adrian V, Ginty, Fiona, Sarachan, Brion, Taylor, D Lansing, Chennubhotla, S Chakra
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 01.11.2017
Schlagworte:
Algorithms
Genetic Heterogeneity
Humans
Image Processing, Computer-Assisted - methods
Neoplasms - genetics
Neoplasms - pathology
Optical Imaging - methods
Optical Imaging - statistics & numerical data
Software
Tissue Array Analysis - statistics & numerical data
ISSN:1538-7445, 1538-7445
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Zusammenfassung:We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between different cell phenotypes and noncellular constituents. Specifically, we foresee applications in phenotyping cells within tumor microenvironments, recognizing tumor boundaries, identifying degrees of immune infiltration and epithelial/stromal separation, and identification of heterotypic signaling networks underlying microdomains. The THRIVE platform provides an integrated workflow for analyzing whole-slide immunofluorescence images and tissue microarrays, including algorithms for segmentation, quantification, and heterogeneity analysis. THRIVE promotes flexible deployment, a maintainable code base using open-source libraries, and an extensible framework for customizing algorithms with ease. THRIVE was designed with highly multiplexed immunofluorescence images in mind, and, by providing a platform to efficiently analyze high-dimensional immunofluorescence signals, we hope to advance these data toward mainstream adoption in cancer research. .
Bibliographie:ObjectType-Article-1
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ISSN:1538-7445
1538-7445
DOI:10.1158/0008-5472.CAN-17-0676