bioRxivCancer BiologyPreprint
Proteogenomic Characterization of Primary Oral Squamous Cell Carcinomas Unveils the Extracellular Matrix Remodeling and Immunosuppressive Microenvironment Linked with Lymph Node Metastasis
Yu LiuiD, Zhenyu YangiD, Jingya Jane PuiD, Jie ZhongiD, U. S. KhooiD, Yu-Xiong SuiD, Gao ZhangiD
Abstract
Oral squamous cell carcinoma (OSCC) is an increasingly prevalent malignancy worldwide. This study aims to understand molecular alterations associated with lymph node metastasis of OSCC in order to improve treatment strategies. We analyzed a cohort of 46 patients with primary OSCC, including 10 with lymph node metastasis and 36 without. Using a comprehensive multi-omics approach--encompassing genomic, transcriptomic, proteomic, epigenetic, single-cell, and spatial analyses--we integrated data to delineate the molecular landscape of OSCC in the context of lymph node metastasis. Our genomic analysis identified significant mutations in key genes within the MAPK, TGF-{beta}, and WNT signaling pathways, which are essential for tumor development. The proteogenomic analysis highlighted pathways critical for lymph node dissemination and factors contributing to an immunosuppressive tumor microenvironment. Elevated levels of POSTN were found to reorganize the extracellular matrix (ECM), interact with TGF-{beta}, disrupt cell cycle regulation, and suppress the immune response by reducing VCAM1 activity. Integrated analyses of single-cell and spatial transcriptome data revealed that cancer-associated fibroblasts (CAFs) secrete TGF-{beta}1/2, promoting cancer cell metastasis through epithelial-mesenchymal transition (EMT). Our integrated multi-omics analysis provides a detailed understanding of molecular mechanisms driving lymph node metastasis of OSCC. These insights could lead to more precise diagnostics and targeted treatments.
- organism: human
- assay: bulk RNA-seq
- assay: proteomics
- assay: DNA methylation
- assay: spatial transcriptomics
- research focus: cancer & tumor microenvironment
- approach: statistical model
- Citations
- 0
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