Molecular Cancer ResearchCancer BiologyPeer-reviewed journal article
Spatial transcriptomic analysis of progressing oral epithelial dysplasia reveals unique differentially expressed genes and microenvironmental changes.
Vincent LavoieiD, Erison Santana dos SantosiD, James JeoniD, Juan Fernandez AndradeiD, Aiman A. AliiD, Graziella R. MolskaiD, Najmeh EsfandiariiD, Hui-Ling YeoiD, Igor JurišicaiD, Deepika ChughiD, Iona LeongiD, Justin BubolaiD, Grace BradleyiD, Marco A. O. MagalhãesiD
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Abstract
Oral squamous cell carcinoma (OSCC) often arises from oral epithelial dysplasia (OED); however, the gene expression changes during OED progression and its microenvironment are not fully understood. This study used spatial transcriptomics to identify differentially expressed genes and microenvironmental alterations associated with OEDs malignant transformation of OED. A ten-year retrospective analysis of paired OSCC and prior OED samples was conducted at the University of Toronto Oral Pathology Laboratory. A total of 24 paired progressing OED cases and 23 matched non-progressing OED cases were examined using spatial transcriptomics in PanCK+ (dysplastic epithelium or OSCC) and PanCK- (stroma) regions. The analysis included differential gene expression, pathway analysis and spatial deconvolution. Three genes (STOM, KIF26A, and CDKN2A) showed increased expression in the epithelial component of progressing OED compared with non-progressing OED, whereas 41 genes were differentially expressed in OSCC versus the precursor samples. Ubiquitination-related pathways were enriched during OED progression. Functional validation identified TNFRSF12A (Fn14) as a potential regulator of OED progression to OSCC. The OSCC microenvironment displayed increased numbers of fibroblasts, neutrophils, monocytes, and mast cells compared with that of the precursor samples. Our findings suggest that spatial profiling of OED can help identify unique gene signatures and microenvironmental changes that occur before the malignant transformation.
- organism: human
- assay: spatial transcriptomics
- research focus: differential expression
- approach: statistical model
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