Dataset Information

Immune characteristics and genetic markers of esophageal cancer by single-cell analysis: implications for immunotherapy.

ABSTRACT:

Background

Esophageal cancer (EC) is one of the most common cancers worldwide. The prognoses for patients with the same stage of EC can vary substantially. The progress of single-cell analysis technology has furthered the understanding of tumor heterogeneity. This paper aimed to apply single-cell analysis to explore the characteristics of the tumor environment of EC and provide a basis for personalized treatment.

Methods

The latest gene expression data and clinical follow-up information of single-cell sequencing results of EC samples were downloaded from The Cancer Genome Atlas (TCGA) Genomic Data Commons (GDC) Application Programming Interface (API). A differential gene function analysis of the immune infiltration signature agents in the tumor microenvironment (TME) was performed using bioinformatics analytical methods, and potential molecular targets were sought.

Results

We identified specific cell subsets in the EC and paracancerous samples, including panel cells, natural killer (NK) cells, exhausted cluster of differentiation (CD)8⁺ T cells, CD8⁺ memory T (Tcm) cells, and effector memory T (Tem) cells, including B cell enrichment in the cancer samples. Differences were detected between B cells and monocytes in stage II and III tumors, which may be related to RNA transcription and degradation. The CXCL8 protein was identified as a valid potential prognostic marker.

Conclusions

Cell groups with homogenous cell surface markers exhibit intercellular variations that exert a considerable effect on cell function. Our study will contribute to the understanding of the TME and cellular heterogeneity in EC patients and serve as a valuable resource for in-depth exploration of the pathogenesis of EC and the identification of potential therapeutic targets in the future.

SUBMITTER: Xu B

PROVIDER: S-EPMC10183529 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Publications

Immune characteristics and genetic markers of esophageal cancer by single-cell analysis: implications for immunotherapy.

Xu Bing B Tseng Ihsuan I Zhang Xiaofei X Chen Hui H Rivin Del Campo Eleonor E Deng Jiaying J Ai Dashan D Fang Xumeng X Sun Xinchen X Zhao Kuaile K Su Fengtao F Ge Xiaolin X Zhu Hongcheng H

Journal of thoracic disease 20230427 4

<h4>Background</h4>Esophageal cancer (EC) is one of the most common cancers worldwide. The prognoses for patients with the same stage of EC can vary substantially. The progress of single-cell analysis technology has furthered the understanding of tumor heterogeneity. This paper aimed to apply single-cell analysis to explore the characteristics of the tumor environment of EC and provide a basis for personalized treatment.<h4>Methods</h4>The latest gene expression data and clinical follow-up infor ...[more]

PMID: 37197539

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Project description:BackgroundGastric cancer (GC) is the fifth most common cancer and the second leading cause of cancer-related deaths worldwide. Due to the lack of specific markers, the early diagnosis of gastric cancer is very low, and most patients with gastric cancer are diagnosed at advanced stages. The aim of this study was to identify key biomarkers of GC and to elucidate GC-associated immune cell infiltration and related pathways.MethodsGene microarray data associated with GC were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were analyzed using Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia, Gene Set Enrichment Analysis (GSEA) and Protein-Protein Interaction (PPI) networks. Weighted gene coexpression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to identify pivotal genes for GC and to assess the diagnostic accuracy of GC hub markers using the subjects' working characteristic curves. In addition, the infiltration levels of 28 immune cells in GC and their interrelationship with hub markers were analyzed using ssGSEA. And further validated by RT-qPCR.ResultsA total of 133 DEGs were identified. The biological functions and signaling pathways closely associated with GC were inflammatory and immune processes. Nine expression modules were obtained by WGCNA, with the pink module having the highest correlation with GC; 13 crossover genes were obtained by combining DEGs. Subsequently, the LASSO algorithm and validation set verification analysis were used to finally identify three hub genes as potential biomarkers of GC. In the immune cell infiltration analysis, infiltration of activated CD4 T cell, macrophages, regulatory T cells and plasmacytoid dendritic cells was more significant in GC. The validation part demonstrated that three hub genes were expressed at lower levels in the gastric cancer cells.ConclusionThe use of WGCNA combined with the LASSO algorithm to identify hub biomarkers closely related to GC can help to elucidate the molecular mechanism of GC development and is important for finding new immunotherapeutic targets and disease prevention.

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Dataset Information

Immune characteristics and genetic markers of esophageal cancer by single-cell analysis: implications for immunotherapy.

Background

Methods

Results

Conclusions

Publications

Immune characteristics and genetic markers of esophageal cancer by single-cell analysis: implications for immunotherapy.

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