ArticleCancers2022
Spatial Transcriptomic Analysis Reveals Associations between Genes and Cellular Topology in Breast and Prostate Cancers.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Deep Transfer Learning Links Benign Glands to Prostate Cancer Progression via Transcriptomics.Genomics, proteomics & bioinformatics · 2025Article
- Identification of type 2 diabetes- and obesity-associated human β-cells using deep transfer learning.eLife · 2025Article
- The Expression and Molecular Roles of MAMDC2 in MSS Colorectal Cancer with a High Tumor Stromal Ratio.Biomedicines · 2025Article
- A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging.Topology- and graph-informed imaging informatics : first International Workshop, TGI3 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. International Workshop on Topology- and Graph-Informed ... · 2025Article
- Scoping Review: Methods and Applications of Spatial Transcriptomics in Tumor Research.Cancers · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundCancer is the leading cause of death worldwide with breast and prostate cancer the most common among women and men, respectively. Gene expression and image features are independently prognostic of patient survival; but until the advent of spatial transcriptomics (ST), it was not possible to determine how gene expression of cells was tied to their spatial relationships (i.e., topology).
methodsWe identify topology-associated genes (TAGs) that correlate with 700 image topological features (ITFs) in breast and prostate cancer ST samples. Genes and image topological features are independently clustered and correlated with each other. Themes among genes correlated with ITFs are investigated by functional enrichment analysis.
resultsOverall, topology-associated genes (TAG) corresponding to extracellular matrix (ECM) and Collagen Type I Trimer gene ontology terms are common to both prostate and breast cancer. In breast cancer specifically, we identify the ZAG-PIP Complex as a TAG. In prostate cancer, we identify distinct TAGs that are enriched for GI dysmotility and the IgA immunoglobulin complex. We identified TAGs in every ST slide regardless of cancer type.
conclusionsThese TAGs are enriched for ontology terms, illustrating the biological relevance to our image topology features and their potential utility in diagnostic and prognostic models.
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