AUTHOR=Yuan Wei , Yan Jiaqin , Liu Hongtao , Li Ling , Wu BoWen , Guo Can , Zhang Mingzhi
TITLE=Identification of Prognostic Related Genes of Tumor Microenvironment Derived From Esophageal Cancer Patients
JOURNAL=Pathology and Oncology Research
VOLUME=27
YEAR=2021
URL=https://www.por-journal.com/journals/pathology-and-oncology-research/articles/10.3389/pore.2021.589662
DOI=10.3389/pore.2021.589662
ISSN=1532-2807
ABSTRACT=Background and Objective: Esophageal cancer (ESCA) is a commonly occurring cancer worldwide with poor survival and limited therapeutic options. Due to the lack of biomarkers that facilitate early detection, its treatment remains a great challenge. This study aims at identifying the tumor microenvironment (TME)-related genes, which might affect prognosis and accelerate clinical treatment for ESCA patients.
Methods: We integrated the expression profiles from ESCA patients in The Cancer Genome Atlas. Then, we determined the stromal and immune scores of each sample using the R package. The Gene Expression Omnibus database was used to validate the expression profile of the key genes.
Results: Tumor mutational burden showed a significant difference between the groups of ESCA patients with high and low ESTIMATE scores. We identified 859 intersection genes among patients with different immune and stromal scores. Moreover, gene ontology analysis demonstrated that these 859 intersection genes were closely related to adaptive immune response and regulation of lymphocyte activation. Kyoto Encyclopedia of Genes and Genomes showed the enrichment of cytokine-cytokine receptor interaction and chemokine signaling pathway in the TME. Furthermore, the protein–protein interaction network consisted of 175 nodes. We selected 35 hub genes, including ITGAM, CXCL10, CCR2, CCR5, and CCR1. Of these, 23 intersection genes predicted the overall survival rate. C1QA and FCER1G correlated with overall survival of the ESCA patients in the two databases.
Conclusion: We identified a set of stromal and immune score-related prognostic differentially expressed genes that could influence the complexity of the TME. C1QA and FCER1G were identified and validated with respect to their role in the progression of ESCA.