Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Esophageal Squamous Cell Carcinoma.
Yongxu JiaBai-Feng ZhangChunyang ZhangDora Lai-Wan KwongZhiwei ChangShanshan LiZehua WangHuiqiong HanJing LiYali ZhongXin SuiLi FuXin-Yuan GuanYanru QinPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2023)
Lymph node metastasis, the leading cause of mortality in esophageal squamous carcinoma (ESCC) with a highly complex tumor microenvironment, remains underexplored. Here, the transcriptomes of 85 263 single cells are analyzed from four ESCC patients with lymph node metastases. Strikingly, it is observed that the metastatic microenvironment undergoes the emergence or expansion of interferon induced IFIT3 + T, B cells, and immunosuppressive cells such as APOC1 + APOE + macrophages and myofibroblasts with highly expression of immunoglobulin genes (IGKC) and extracellular matrix component and matrix metallopeptidase genes. A poor-prognostic epithelial-immune dual expression program regulating immune effector processes, whose activity is significantly enhanced in metastatic malignant epithelial cells and enriched in CD74 + CXCR4 + and major histocompatibility complex (MHC) class II genes upregulated malignant epithelia cells is discovered. Comparing with primary tumor, differential intercellular communications of metastatic ESCC microenvironment are revealed and furtherly validated via multiplexed immunofluorescence and immunohistochemistry staining, which mainly rely on the crosstalk of APOC1 + APOE + macrophages with tumor and stromal cell. The data highlight potential molecular mechanisms that shape the lymph-node metastatic microenvironment and may inform drug discovery and the development of new strategies to target these prometastatic nontumor components for inhibiting tumor growth and overcoming metastasis to improve clinical outcomes.
Keyphrases
- single cell
- squamous cell carcinoma
- lymph node
- induced apoptosis
- small cell lung cancer
- lymph node metastasis
- cell cycle arrest
- extracellular matrix
- stem cells
- drug discovery
- poor prognosis
- genome wide
- rna seq
- endoplasmic reticulum stress
- oxidative stress
- cell death
- cardiovascular disease
- regulatory t cells
- cell therapy
- coronary artery disease
- immune response
- risk factors
- binding protein
- insulin resistance
- big data
- high fat diet
- machine learning
- risk assessment
- dna methylation
- gene expression
- papillary thyroid
- electronic health record
- cardiovascular events
- sentinel lymph node
- cell proliferation
- genome wide identification