Abstract
Esophageal squamous cell carcinoma (ESCC) is one of the deadliest solid malignancies and has a poor survival rate worldwide. In this study, we aimed to establish a tumor-infiltrating immune cell-based prognosis signature (IPS) to predict patients’ survival times and aid in the development of targeted therapies or immunotherapies. The abundances of 22 types of immune cells were determined by the CIBERSORT algorithm from ESCC patient gene expression data in the Gene Expression Omnibus (GEO) training set (n = 179) and The Cancer Genome Atlas (TCGA) validation set (n = 95). Then, the IPS was established by using the least absolute shrinkage and selection operator (LASSO) regression method. Kaplan-Meier analysis showed that patients with high IPS scores had significantly worse overall survival times than patients with low IPS scores in both the training set and the validation set (log-rank p = 0.001, and p = 0.050, respectively). Univariate and multivariate Cox regression analyses proved that the IPS was a robust prognostic factor for ESCC, independent of age, sex, tumor node metastasis (TNM) stage, pathology grade, and tumor location. In the mechanistic study, the epithelial-mesenchymal transition (EMT) process was identified by both gene set enrichment analysis (GSEA) and weighted correlation network analysis (WGCNA) as the underlying mechanism by which the IPS affects the prognosis of ESCC. After systematic correlation analyses, we found that M2 macrophages were the only cell type in the IPS significantly correlated with the EMT process. This relationship between M2 macrophage infiltration and the EMT phenotype was also confirmed by our preliminary immunochemistry (IHC) and multiplexed immunofluorescence study. In conclusion, we constructed an IPS that predicts the postoperative prognosis of ESCC patients and uncovered the critical role of M2 macrophages in the interplay between immune status and the EMT phenotype in ESCC.
Highlights
Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies posing a severe threat to human health worldwide especially in East Asia
We found that M2 macrophages were the only cell type significantly correlated with the immune cell-based prognosis signature (IPS) score and epithelialmesenchymal transition (EMT) score in both the training and validation sets
We applied the median point as the cutoff value, and Kaplan-Meier analysis showed that patients with high IPS scores had a significantly worse overall survival than patients with low IPS scores in both the training and validation sets
Summary
Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies posing a severe threat to human health worldwide especially in East Asia. Prior immunohistochemistry (IHC)-based cell biomarker studies have a common limitation: only a few routine immune cell biomarkers, most frequently CD3, CD4, CD8, CD45RO, and FoxP3, were investigated [3]. These studies provide only a limited understanding of the vast immune microenvironment scenarios of ESCC. The specificity and sensitivity with which a given cell biomarker can identify certain immune cell subtypes are still under debate [4] In addressing these questions, bioinformatics has long played a critical role [5]. Ongoing progress in computational methods has enabled higher accuracy in the quantification of the immune cells, greatly aiding in immune-related research of tumors [10,11,12]
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