ArticleJournal of pathology informatics2021
A Comparison of Methods for Studying the Tumor Microenvironment's Spatial Heterogeneity in Digital Pathology Specimens.
Article in Journal of pathology informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- PATHOS: Pathology attention framework for treatment response stratification in ovarian high-grade serous carcinomas following neoadjuvant chemotherapy on H&E images.Journal of pathology informatics · 2026Article
- Caveat Medicus: It's Time to Re-Think Stratification, You May Not Be Helping.Biomarker insights · 2023Article
- Proposal of an automated tumor-stromal ratio assessment algorithm and a nomogram for prognosis in early-stage invasive breast cancer.Cancer medicine · 2023Article
- Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications.Frontiers in immunology · 2023Article
- Simulations of tumor growth and response to immunotherapy by coupling a spatial agent-based model with a whole-patient quantitative systems pharmacology model.PLoS computational biology · 2022Article
- Two Ensemble-CNN Approaches for Colorectal Cancer Tissue Type Classification.Journal of imaging · 2021Article
- Spatial heterogeneity of immune infiltration predicts the prognosis of nasopharyngeal carcinoma patients.Oncoimmunology · 2021Article
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6 authors.
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Abstract
backgroundThe tumor microenvironment is highly heterogeneous, and it is understood to affect tumor progression and patient outcome. A number of studies have reported the prognostic significance of tumor-infiltrating lymphocytes and tumor budding in colorectal cancer (CRC). However, the significance of the intratumoral heterogeneity present in the spatial distribution of these features within the tumor immune microenvironment (TIME) has not been previously reported. Evaluating this intratumoral heterogeneity may aid the understanding of the TIME's effect on patient prognosis as well as identify novel aggressive phenotypes which can be further investigated as potential targets for new treatment.
methodsIn this study, we propose and apply two spatial statistical methodologies for the evaluation of the intratumor heterogeneity present in the distribution of CD3
resultsResultant data from each analysis, characterizing the spatial intratumor heterogeneity of lymphocytes and TBs were used for the development of two new highly prognostic risk models.
conclusionsOur results highlight the value of applying spatial statistics for the assessment of the intratumor heterogeneity. Both Getis-Ord hotspot and our proposed spatial heatmap analysis are broadly applicable across other tissue types as well as other features of interest. AVAILABILITY: The code underpinning this publication can be accessed at https://doi.org/10.17630/c2306fe9-66e2-4442-ad89-f986220053e2.
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