Identification and characterization of metastasis-initiating cells in esophageal squamous cell carcinoma in a pulmonary metastasis mouse model [scRNA-Seq]

Background and aims: Cancer metastasis is the biggest obstacle to esophageal squamous cell carcinoma (ESCC) treatment. At present, understanding of its mechanism remains insufficient. Therefore, an in-depth exploration of the mechanisms of metastasis is crucial for early detection and intervention to reduce metastasis-related mortality. Methods: This study applied single-cell RNA sequencing analysis to investigate lung metastatic ESCC cells isolated from a pulmonary metastasis mouse model at multiple timepoints to characterize early metastatic microenvironment. Results: We identified a small population of parental ESCC KYSE30 cell line (Cluster S) resembled metastasis-initiating cells (MICs) because they could survive and colonize at lung metastatic sites. By comparing differential expression profiles between Cluster S and other subpopulations, we identified a panel of 7 metastasis-initiating signature genes (MIS), including CD44 and TACSTD2, to represent MICs of ESCC. Functional studies demonstrated that Cluster S cells (CD44high) exhibited significantly enhanced cell survival (resistances to oxidative stress and apoptosis), cell migration, invasion, stemness, and in vivo lung metastasis capabilities. Multiplex immunohistochemistry (mIHC) staining of 4 MISs (CD44, S100A14, RHOD, and TACSTD2) in ESCC cell lines and clinical samples found that differential MIS expression scores (dMISs) could predict lymph node metastasis, overall survival and risk of carcinothrombosis. GO and KEGG analyses revealed that CD44high cells were enriched in cell migration, organ development, stress responses, and neuron development, which might be related to the establishment of early metastatic microenvironment. Conclusion: This study identified CD44, S100A14, RHOD, and TACSTD2 as MISs to represent the MICs in ESCC populations and predict patient outcomes. Keywords: ESCC, metastasis-initiating cells, metastasis-initiating signatures, biomarker, scRNA-seq.