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Establishment of a Novel Risk Score System of Immune Genes Associated With Prognosis in Esophageal Carcinoma.

AbstractBACKGROUND:
Few studies have addressed the role of immune-related genes in the survival and prognosis of different esophageal cancer (EC) sub-types. We established two new prognostic model indexes by bioinformatics analysis to select patients with esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) who may benefit from immunotherapy.
METHODS:
Based on TCGA and ImmPort data sets, we screened immune genes differentially expressed between tumor and normal tissues in ESCC and EAC and analyzed the relationship between these genes and patient survival outcomes. We established the risk score models of immune-related genes in ESCC and EAC by multivariate COX regression analysis.
RESULTS:
We identified 12 and 11 immune-related differentially expressed genes associated with the clinical prognosis of ESCC and EAC respectively, based on which two prognostic risk score models of the two EC sub-types were constructed. It was found that the survival probability of patients with high scores was significantly lower than that of patients with low scores (p < 0.001). BMP1, EGFR, S100A12, HLA-B, TNFSF18, IL1B, MAPT and OXTR were significantly related to sex, TNM stage or survival outcomes of ESCC or EAC patients (p < 0.05). In addition, the risk score of ESCC was significantly correlated with the level of B cell infiltration in immune cells (p < 0.05).
CONCLUSIONS:
The prognosis-related immune gene model indexes described herein prove to be useful prognostic biomarkers of the two EC sub-types in that they may provide a reference direction for looking for the beneficiaries of immunotherapy for EC patients.
AuthorsZhenghua Fei, Rongrong Xie, Zhi Chen, Junhui Xie, Yuyang Gu, Yue Zhou, Tongpeng Xu
JournalFrontiers in oncology (Front Oncol) Vol. 11 Pg. 625271 ( 2021) ISSN: 2234-943X [Print] Switzerland
PMID33859939 (Publication Type: Journal Article)
CopyrightCopyright © 2021 Fei, Xie, Chen, Xie, Gu, Zhou and Xu.

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