%0 Journal Article
%T The spatial distribution of intermediate fibroblasts and myeloid-derived cells dictate lymph node metastasis dynamics in oral cancer.
%A Shaikh S
%A Dhar H
%A Moorthy M
%A Bhat V
%A Basu S
%A Banerjee D
%A Mishra DK
%A Datta S
%A Mukherjee G
%J J Transl Med
%V 22
%N 1
%D 2024 Aug 13
%M 39138492
%F 8.44
%R 10.1186/s12967-024-05511-1
%X <B>BACKGROUND: </B>Oral cancer poses a significant health challenge due to limited treatment protocols and therapeutic targets. We aimed to investigate the invasive margins of gingivo-buccal oral squamous cell carcinoma (GB-OSCC) tumors in terms of the localization of genes and cell types within the margins at various distances that could lead to nodal metastasis.<BR><B>METHODS: </B>We collected tumor tissues from 23 resected GB-OSCC samples for gene expression profiling using digital spatial transcriptomics. We monitored differential gene expression at varying distances between the tumor and its microenvironvent (TME), and performed a deconvulation study and immunohistochemistry to identify the cells and genes regulating the TME.<BR><B>RESULTS: </B>We found that the tumor-stromal interface (a distance up to 200 µm between tumor and immune cells) is the most active region for disease progression in GB-OSCC. The most differentially expressed apex genes, such as FN1 and COL5A1, were located at the stromal ends of the margins, and together with enrichment of the extracellular matrix (ECM) and an immune-suppressed microenvironment, were associated with lymph node metastasis. Intermediate fibroblasts, myocytes, and neutrophils were enriched at the tumor ends, while cancer-associated fibroblasts (CAFs) were enriched at the stromal ends. The intermediate fibroblasts transformed into CAFs and relocated to the adjacent stromal ends where they participated in FN1-mediated ECM modulation.<BR><B>CONCLUSIONS: </B>We have generated a functional organization of the tumor-stromal interface in GB-OSCC and identified spatially located genes that contribute to nodal metastasis and disease progression. Our dataset might now be mined to discover suitable molecular targets in oral cancer.