ArticleScientific reports2020
Combining multiple spatial statistics enhances the description of immune cell localisation within tumours.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 39 citations in OpenAlex.
- scRNA-seq and genomics analyses reveal key mechanisms of inverted papilloma-associated sinonasal squamous cell carcinoma malignant transformation.bioRxiv : the preprint server for biology · 2026Article
- From cells to pixels: A decision tree for designing bioimage analysis pipelines.Journal of microscopy · 2025Article
- Topological classification of tumour-immune interactions and dynamics.Journal of mathematical biology · 2025Article
- Using spatial statistics to infer game-theoretic interactions in an agent-based model of cancer cells.bioRxiv : the preprint server for biology · 2025Article
- Topological data analysis of pattern formation of human induced pluripotent stem cell colonies.Scientific reports · 2025Article
- A new paradigm considering multicellular adhesion, repulsion and attraction represent diverse cellular tile patterns.PLoS computational biology · 2025Article
- Statistical analysis of spatial patterns in tumor microenvironment images.Nature communications · 2025Article
- Peri-tumoural lymphocyte neighbourhoods predict longer survival in pancreatic ductal adenocarcinoma.Frontiers in immunology · 2025Article
- Deciphering cell to cell spatial relationship for pathology images using SpatialQPFs.Scientific reports · 2024Article
- Dissecting the Spatially Restricted Effects of Microenvironment-Mediated Resistance on Targeted Therapy Responses.Cancers · 2024Article
- Using random forests to uncover the predictive power of distance-varying cell interactions in tumor microenvironments.PLoS computational biology · 2024Article
- Hypoxia coordinates the spatial landscape of myeloid cells within glioblastoma to affect survival.Science advances · 2024Article
- Semmaphorin 3 A causes immune suppression by inducing cytoskeletal paralysis in tumour-specific CD8Nature communications · 2024Article
- SpaceANOVA: Spatial Co-occurrence Analysis of Cell Types in Multiplex Imaging Data Using Point Process and Functional ANOVA.Journal of proteome research · 2024Article
- Computational staining of CD3/CD20 positive lymphocytes in human tissues with experimental confirmation in a genetically engineered mouse model.Frontiers in immunology · 2024Article
- Extended correlation functions for spatial analysis of multiplex imaging data.Biological imaging · 2024Article
- Stroma-Mediated Breast Cancer Cell Proliferation Indirectly Drives Chemoresistance by Accelerating Tumor Recovery between Chemotherapy Cycles.Cancer research · 2023Article
- Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer.Nature communications · 2023Article
- Quantification of spatial and phenotypic heterogeneity in an agent-based model of tumour-macrophage interactions.PLoS computational biology · 2023Article
- Multiparameter persistent homology landscapes identify immune cell spatial patterns in tumors.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Digital pathology enables computational analysis algorithms to be applied at scale to histological images. An example is the identification of immune cells within solid tumours. Image analysis algorithms can extract precise cell locations from immunohistochemistry slides, but the resulting spatial coordinates, or point patterns, can be difficult to interpret. Since localisation of immune cells within tumours may reflect their functional status and correlates with patient prognosis, novel descriptors of their spatial distributions are of biological and clinical interest. A range of spatial statistics have been used to analyse such point patterns but, individually, these approaches only partially describe complex immune cell distributions. In this study, we apply three spatial statistics to locations of CD68+ macrophages within human head and neck tumours, and show that images grouped semi-quantitatively by a pathologist share similar statistics. We generate a synthetic dataset which emulates human samples and use it to demonstrate that combining multiple spatial statistics with a maximum likelihood approach better predicts human classifications than any single statistic. We can also estimate the error associated with our classifications. Importantly, this methodology is adaptable and can be extended to other histological investigations or applied to point patterns outside of histology.
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