title: Computational pathology: Exploring the spatial dimension of tumor ecology.
abstract: 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.
authors.affiliation: Centre for Molecular Pathology, Institute of Cancer Research, London SM2 5NG, UK; Centre for Evolution and Cancer, Institute of Cancer Research, London SM2 5NG, UK; Division of Molecular Pathology, The Institute of Cancer Research, London SM2 5NG, UK.
authors.forename: Sidra
authors.initials: S
authors.lastname: Nawaz
authors.affiliation: Centre for Molecular Pathology, Institute of Cancer Research, London SM2 5NG, UK; Centre for Evolution and Cancer, Institute of Cancer Research, London SM2 5NG, UK; Division of Molecular Pathology, The Institute of Cancer Research, London SM2 5NG, UK. Electronic address: yinyin.yuan@icr.ac.uk.
authors.forename: Yinyin
authors.initials: Y
authors.lastname: Yuan
mesh_terms: D000818:Animals; D001706:Biopsy; D001943:Breast Neoplasms / Q000401:mortality / Q000473:pathology* / Q000628:therapy; D005260:Female; D057166:High-Throughput Screening Assays / Q000706:statistics & numerical data; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D015233:Models, Statistical; D010336:Pathology / Q000379:methods* / Q000706:statistics & numerical data; D010363:Pattern Recognition, Automated; D010641:Phenotype; D011237:Predictive Value of Tests; D011379:Prognosis; D013997:Time Factors; D059016:Tumor Microenvironment
keywords: Geospatial statistics; Histology; Image analysis; Symbiosis; Tumor microenvironment