Computational pathology: Exploring the spatial dimension of tumor ecology.
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Date
2016-09-28Author
Nawaz, S
Yuan, Y
Type
Journal Article
Metadata
Show full item recordAbstract
Tumors are evolving ecosystems where cancer subclones and the microenvironment interact. This is analogous to interaction dynamics between species in their natural habitats, which is a prime area of study in ecology. Spatial statistics are frequently used in ecological studies to infer complex relations including predator-prey, resource dependency and co-evolution. Recently, the emerging field of computational pathology has enabled high-throughput spatial analysis by using image processing to identify different cell types and their locations within histological tumor samples. We discuss how these data may be analyzed with spatial statistics used in ecology to reveal patterns and advance our understanding of ecological interactions occurring among cancer cells and their microenvironment.
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Subject
Animals
Humans
Breast Neoplasms
Image Interpretation, Computer-Assisted
Biopsy
Prognosis
Models, Statistical
Predictive Value of Tests
Pathology
Phenotype
Time Factors
Pattern Recognition, Automated
Female
High-Throughput Screening Assays
Tumor Microenvironment
Research team
Computational Pathology & Integrated Genomics
Language
eng
Date accepted
2015-11-10
License start date
2016-09
Citation
Cancer letters, 2016, 380 (1), pp. 296 - 303
Publisher
ELSEVIER IRELAND LTD