Spatial Transcriptomic Analysis Reveals Associations between Genes and Cellular Topology in Breast and Prostate Cancers

dc.contributor.authorAlsaleh, Lujain
dc.contributor.authorLi, Chen
dc.contributor.authorCouetil, Justin L.
dc.contributor.authorYe, Ze
dc.contributor.authorHuang, Kun
dc.contributor.authorZhang, Jie
dc.contributor.authorChen, Chao
dc.contributor.authorJohnson, Travis S.
dc.contributor.departmentBiostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
dc.date.accessioned2024-06-05T11:58:10Z
dc.date.available2024-06-05T11:58:10Z
dc.date.issued2022-10-04
dc.description.abstractBackground: Cancer 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). Methods: We 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. Results: Overall, 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. Conclusions: These TAGs are enriched for ontology terms, illustrating the biological relevance to our image topology features and their potential utility in diagnostic and prognostic models.
dc.eprint.versionFinal published version
dc.identifier.citationAlsaleh L, Li C, Couetil JL, et al. Spatial Transcriptomic Analysis Reveals Associations between Genes and Cellular Topology in Breast and Prostate Cancers. Cancers (Basel). 2022;14(19):4856. Published 2022 Oct 4. doi:10.3390/cancers14194856
dc.identifier.urihttps://hdl.handle.net/1805/41215
dc.language.isoen_US
dc.publisherMDPI
dc.relation.isversionof10.3390/cancers14194856
dc.relation.journalCancers
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePMC
dc.subjectSpatial transcriptomics
dc.subjectHistopathological images
dc.subjectImage analysis
dc.subjectBreast cancer
dc.subjectProstate cancer
dc.subjectGene expression
dc.subjectTopological data analysis
dc.subjectIntegrative analysis
dc.titleSpatial Transcriptomic Analysis Reveals Associations between Genes and Cellular Topology in Breast and Prostate Cancers
dc.typeArticle
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