ArticleComputational and systems oncology2022
Inference on spatial heterogeneity in tumor microenvironment using spatial transcriptomics data.
Article in Computational and systems oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 14 citations in OpenAlex.
- Computational Oncology of Chemotaxis-Driven Tumour-Immune Spatial Patterning and Stability.Bioengineering (Basel, Switzerland) · 2026Article
- Article
- Beyond density: mapping the functional landscapes of macrophage-T lymphocyte niches in the tumor microenvironment.Frontiers in immunology · 2026Review
- Article
- Harnessing the tumor microenvironment: targeted cancer therapies through modulation of epithelial-mesenchymal transition.Journal of hematology & oncology · 2025Review
- Pruning-Assisted Modeling of Network Graph Connectivity from Spatial Transcriptomic Data.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Tumor-derived mesenchymal progenitor cell-related genes in the regulation of breast cancer proliferation.Gland surgery · 2024Article
- Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma.Communications biology · 2023Article
- Article
- Important Cells and Factors from Tumor Microenvironment Participated in Perineural Invasion.Cancers · 2023Review
- LOCATOR: feature extraction and spatial analysis of the cancer tissue microenvironment using mass cytometry imaging technologies.Bioinformatics advances · 2023Article
- Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications.Frontiers in immunology · 2023Article
- Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
In the tumor microenvironment (TME), functional interactions among tumor, immune, and stromal cells and the extracellular matrix play key roles in tumor progression, invasion, immune modulation, and response to treatment. Intratumor heterogeneity is ubiquitous not only at the genetic and transcriptomic levels but also in the composition and characteristics of TME. However, quantitative inference on spatial heterogeneity in the TME is still limited. Here, we propose a framework to use network graph-based spatial statistical models on spatially annotated molecular data to gain insights into modularity and spatial heterogeneity in the TME. Applying the framework to spatial transcriptomics data from pancreatic ductal adenocarcinoma samples, we observed significant global and local spatially correlated patterns in the abundance score of tumor cells; in contrast, immune cell types showed dispersed patterns in the TME. Hypoxia, EMT, and inflammation signatures contributed to intra-tumor spatial variations. Spatial patterns in cell type abundance and pathway signatures in the TME potentially impact tumor growth dynamics and cancer hallmarks. Tumor biopsies are integral to the diagnosis and clinical management of cancer patients; our data suggest that owing to intra-tumor non-genetic spatial heterogeneity, individual biopsies may underappreciate the extent of clinically relevant, functional variations across geographic regions within tumors.
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