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Series GSE249057 Query DataSets for GSE249057
Status Public on Aug 21, 2024
Title Identification and characterization of metastasis-initiating cells in esophageal squamous cell carcinoma in a pulmonary metastasis mouse model [scRNA-Seq]
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary 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.
 
Overall design Human origin ESCC cell line labelled with luciferase and GFP (KYSE30-Luc-GFP) at in vitro state and retrieved from metastatic lungs of pulmonary metastasis mouse models at four timepoints (6 hours, 48 hours, 2 months, and 4 months) were collected via flow cytometry cell sorting (FACS), and undergone 10X Genomics single-cell transcriptome sequencing.
 
Contributor(s) WONG C, ZHANG Y, RU B, WANG S, ZHOU H, LIN J, Lyu Y, QIN Y, JIANG P, LEE V, GUAN X
Citation(s) 38864342
Submission date Nov 30, 2023
Last update date Aug 22, 2024
Contact name Ching Ngar Wong
E-mail(s) cynngar@connect.hku.hk
Organization name The University of Hong Kong
Department Clinical Oncology
Lab L10-56
Street address Lab Block, 21 Sassoon Road,
City Hong Kong
State/province Hong Kong
ZIP/Postal code 000000
Country Hong Kong
 
Platforms (1)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
Samples (5)
GSM7925719 ESCC_KYSE30-Luc-GFP, in vitro, rep1
GSM7925720 ESCC_KYSE30-Luc-GFP, in vivo metastasis 6 hours, rep1
GSM7925721 ESCC_KYSE30-Luc-GFP, in vivo metastasis 48 hours, rep1
This SubSeries is part of SuperSeries:
GSE249058 Identification and characterization of metastasis-initiating cells in esophageal squamous cell carcinoma in a pulmonary metastasis mouse model
Relations
BioProject PRJNA1047099

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Supplementary file Size Download File type/resource
GSE249057_RAW.tar 329.4 Mb (http)(custom) TAR (of MTX, TSV)
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Raw data are available in SRA

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