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Gene & Protein in Disease                                           Pre-metastatic niche oral cancer: Insights



            expression studies. Survival analysis of the TCGA data   and non-metastatic specimens. A  separate analysis was
            was performed using TCGAbiolinks.  Kaplan–Meier    conducted, and DAVID functional analysis showed that
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            plots were constructed to explore the association between   downregulated  DEGs  in  non-metastatic  tissue  were
            clinical outcomes and gene expression, allowing for the   mainly associated with “drug metabolism,” “metabolism
            visualization of survival differences. We further explored   of xenobiotics by cytochrome P450,” “retinol metabolism,”
            protein expression using The Human Protein Atlas.  “calcium signaling pathway,” “dilated cardiomyopathy,”
                                                               “hypertrophic cardiomyopathy, ”and “steroid hormone
            3. Results                                         biosynthesis” pathways. In contrast, the “ECM-receptor
            3.1. Identification of differentially expressed    interaction,” “focal adhesion,” “cytokine-cytokine receptor
            genes, gene ontology enrichment, and functional    interaction,” “neuroactive ligand-receptor interaction,”
            classification                                     “graft-versus-host disease,” “natural killer cell-mediated
                                                               cytotoxicity,” “systemic lupus erythematosus,” and
            To evaluate key factors that contribute to the development   “pathways in cancer” were more active in the same group
            and progression of the pre-metastatic niche in OSCC, we   of specimens (Tables S1 and S2).
            evaluated GEO datasets, including metastatic and non-
            metastatic primary tumor samples (GSE2280), healthy oral   Similarly, in metastatic samples, downregulated DEGs
            tissues  and OSCC samples  (GSE31056), and  metastatic   were linked to the inactivation of “drug metabolism,”
            lymph nodes from patients with OSCC and normal lymph   “metabolism  of  xenobiotics  by  cytochrome  P450,”
            node samples (GSE70604).                           and “retinol metabolism” pathways. On the other
                                                               hand, upregulated DEGs in metastatic samples were
              In the GSE2280 dataset (metastatic and non-metastatic   associated with “ECM-receptor interaction,” “focal
            primary tumor samples), downregulated DEGs indicated   adhesion,”  “cytokine-cytokine  receptor  interaction,”
            the  inactivation  of the “intestinal immune network   “neuroactive ligand-receptor interaction,” “systemic lupus
            for  IgA  production”  and  “cytokine-cytokine  receptor   erythematosus,” “pathways in cancer,” and “cell cycle”
            interaction” pathways. In contrast, upregulation of   pathways. We found similar results in both perineural
            the “calcium signaling pathway,” “neuroactive ligand-  invasion-negative and perineural invasion-positive
            receptor interaction,” “long-term potentiation,” “dilated   analyses (Tables S3 and S4).
            cardiomyopathy,”  “gonadotropin-releasing  hormone
            (GnRH) signaling pathway,” and “gap junction” were   3.3. Differentially expressed genes and pre-
            observed (Table 1).                                metastatic niche-related genes
              In the GSE31056 dataset (healthy oral tissues and   Using Entrez Gene and GeneCards analyses, we identified
            OSCC samples), the top six downregulated pathways were   473 pre-metastatic niche-related genes. A Venn diagram
            “drug metabolism,” “fatty acid metabolism,” “metabolism   was created to illustrate the overlap between the DEGs
            of xenobiotics by cytochrome P450,” “peroxisome    identified in the meta-analysis and those related to the
            proliferator-activated receptor signaling pathway,” “dilated   pre-metastatic niche. The data showed that SERPINE1,
            cardiomyopathy,”  and  “valine,  leucine,  and  isoleucine   SPP1, CALCA, and  MMP13 genes were consistently
            degradation.” We observed that “cell cycle,” “extracellular   upregulated across all GEO and  TCGA  datasets.
            matrix (ECM)-receptor interaction,” “DNA replication,”   According to the list of 473 pre-metastatic niche-related
            “focal adhesion,” “p53 signaling pathway,” and “pathways   genes, the GSE70604 dataset (lymph node samples)
            in cancer” were more active in OSCC samples compared   showed 68 upregulated and 61 downregulated genes.
            with normal tissue (Table 2).                      DAVID analysis showed those the upregulated genes are
              Finally, in the GSE70604 dataset (metastatic lymph   associated  with  several  cancer-related  pathways,  while
            nodes), we observed inactivated immune response    the downregulated genes are mainly associated with
            pathways  and activated “ECM-receptor interaction,”   immune response, axon guidance, and the neurotrophin
            “focal adhesion,” “pathways in cancer,” “circadian rhythm,”   signaling pathway (Table  4). These findings were
            “steroid  hormone  biosynthesis,”  and  “adherens  junction”   validated using immunohistochemical analysis from The
            pathways (Table 3).                                Human Protein Atlas (Figure 1).
                                                                 We found a positive correlation between  CALCA,
            3.2. Overview of The Cancer Genome Atlas cancer    SERPINE1, MMP13, SPP1, and MMP13 in TCGA cancer
            transcriptomic analysis                            samples (Figure  2). Survival analysis showed that the

            To validate the GEO2R results, we evaluated the TCGA   overexpression of  SERPINE1, SPP1, and L1CAM  (axon
            data, obtaining gene expression data from metastatic   guidance) was associated with poor survival, while the low


            Volume 3 Issue 4 (2024)                         3                               doi: 10.36922/gpd.2971
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