The scRNA-sequencing landscape of pancreatic ductal adenocarcinoma revealed distinct cell populations associated with tumor initiation and progression

Genes & Diseases(2024)

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摘要
Pancreatic ductal adenocarcinoma (PDAC) stands as a formidable malignancy characterized by its profound lethality. The comprehensive analysis of the transcriptional landscape holds immense significance in understanding PDAC development and exploring novel treatment strategies. However, due to the firm consistency of pancreatic cancer samples, the dissociation of single cells and subsequent sequencing can be challenging. Here, we performed single-cell RNA sequencing (scRNA-seq) on 8 PDAC patients with different lymph node metastasis status. We first identified the crucial role of MMP1 in the transition from normal pancreatic cells to cancer cells. The knockdown of MMP1 in pancreatic cancer cell lines decreased the expression of ductal markers such as SOX9 while the overexpression of MMP1 in hTERT-HPNE increased the expression of ductal markers, suggesting its function of maintaining ductal identity. Secondly, we found a S100A2+ tumor subset which fueled lymph node metastasis in PDAC. The knockdown of S100A2 significantly reduced the motility of pancreatic cancer cell lines in both wound healing and transwell migration assays. While overexpression of S100A2 led to increased migratory capability. Moreover, overexpression of S100A2 in KPC1199, a mouse pancreatic cancer cell line, caused a larger tumor burden in a hemi-spleen injection model of liver metastasis. In addition, epithelial-mesenchymal transition-related genes were decreased by S100A2 knockdown revealed by bulk RNA sequencing. We also identified several pivotal contributors to the pro-tumor microenvironment, notably OMD+ fibroblast and CCL2+ macrophage. As a result, our study provides valuable insights for early detection of PDAC and promising therapeutic targets for combatting lymph node metastasis.
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关键词
Acinar-to-ductal metaplasia,Lymph node metastasis,Pancreatic ductal adenocarcinoma,Single-cell RNA sequencing,Tumor microenvironment
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