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Abstract：
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
摘要：
背景：由于有限的治疗方案和治疗靶标，口腔癌构成了重大的健康挑战。我们旨在研究牙龈-口腔鳞状细胞癌（GB-OSCC）肿瘤的浸润性边缘，这些边缘在不同距离的基因和细胞类型的定位可能导致淋巴结转移。
方法：我们从23个切除的GB-OSCC样本中收集了肿瘤组织，用于使用数字空间转录组学进行基因表达谱分析。我们监测了肿瘤与其微环境（TME）之间不同距离的差异基因表达，并进行了去克隆研究和免疫组织化学以鉴定调节TME的细胞和基因。
结果：我们发现肿瘤-基质界面（肿瘤和免疫细胞之间的距离高达200µm）是GB-OSCC中疾病进展最活跃的区域。差异表达最多的顶点基因，如FN1和COL5A1，位于边缘的基质末端，以及细胞外基质（ECM）的富集和免疫抑制的微环境，与淋巴结转移有关。中间成纤维细胞，肌细胞,和嗜中性粒细胞在肿瘤末端富集，而癌症相关成纤维细胞（CAF）在基质末端富集。中间成纤维细胞转化为CAF并重新定位到相邻的基质末端,在那里它们参与FN1介导的ECM调节。
结论：我们已经在GB-OSCC中产生了肿瘤-基质界面的功能性组织，并鉴定了有助于淋巴结转移和疾病进展的空间定位基因。现在可以挖掘我们的数据集以发现口腔癌中合适的分子靶标。
方法：我们从23个切除的GB-OSCC样本中收集了肿瘤组织，用于使用数字空间转录组学进行基因表达谱分析。我们监测了肿瘤与其微环境（TME）之间不同距离的差异基因表达，并进行了去克隆研究和免疫组织化学以鉴定调节TME的细胞和基因。
结果：我们发现肿瘤-基质界面（肿瘤和免疫细胞之间的距离高达200µm）是GB-OSCC中疾病进展最活跃的区域。差异表达最多的顶点基因，如FN1和COL5A1，位于边缘的基质末端，以及细胞外基质（ECM）的富集和免疫抑制的微环境，与淋巴结转移有关。中间成纤维细胞，肌细胞,和嗜中性粒细胞在肿瘤末端富集，而癌症相关成纤维细胞（CAF）在基质末端富集。中间成纤维细胞转化为CAF并重新定位到相邻的基质末端,在那里它们参与FN1介导的ECM调节。
结论：我们已经在GB-OSCC中产生了肿瘤-基质界面的功能性组织，并鉴定了有助于淋巴结转移和疾病进展的空间定位基因。现在可以挖掘我们的数据集以发现口腔癌中合适的分子靶标。
