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. 2023 Jul 10;24(1):385.
doi: 10.1186/s12864-023-09496-x.

A robust immune-related gene pairs signature for predicting the overall survival of esophageal cancer

Wei Zheng  1 , Gaofeng Fang  2 , Qiao Huang  3 , Dan Shi  4 , Biao Xie  5
Affiliations

A robust immune-related gene pairs signature for predicting the overall survival of esophageal cancer

Wei Zheng et al. BMC Genomics. .

Abstract

Background: Identifying reliable biomarkers could effectively predict esophagus carcinoma (EC) patients with poor prognosis. In this work, we constructed an immune-related gene pairs (IRGP) signature to evaluate the prognosis of EC.

Results: The IRGP signature was trained by the TCGA cohort and validated by three GEO datasets, respectively. Cox regression model together with LASSO was applied to construct the overall survival (OS) associated IRGP. 21 IRGPs consisting of 38 immune-related genes were included in our signature, according to which patients were stratified into high- and low-risk groups. The results of Kaplan-Meier survival analyses indicated that high-risk EC patients had worse OS than low-risk group in the training set, meta-validation set and all independent validation datasets. After adjustment in multivariate Cox analyses, our signature continued to be an independent prognostic factor of EC and the signature-based nomogram could effectively predict the prognosis of EC sufferers. Besides, Gene Ontology analysis revealed this signature is related to immunity. 'CIBERSORT' analysis revealed the infiltration levels of plasma cells and activated CD4 memory T cells in two risk groups were significantly different. Ultimately, we validated the expression levels of six selected genes from IRGP index in KYSE-150 and KYSE-450.

Conclusions: This IRGP signature could be applied to select EC patients with high mortality risk, thereby improving prospects for the treatment of EC.

Keywords: Bioinformatic analysis; Cells lines; Esophageal cancer; Immune-related gene pairs; Prognosis.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The overview design in this study
Fig. 2
Fig. 2
The Kaplan-Meier curves and time-dependent ROC curves in patients of training cohort. (a) OS in patients of training dataset classified by the signature. (b) RFS in patients of training dataset classified by the signature. (c) The time-dependent ROC curves of the IRGPI for 1-, 2- and 3-year OS of patients in training cohort
Fig. 3
Fig. 3
Kaplan-Meier curves in patients of validation sets classified by the signature. (a) OS of patients in meta-validation set. (b) OS of patients in GSE13898. (c) OS of patients in GSE19417. (d) OS of patients in GSE53625.
Fig. 4
Fig. 4
GO enrichment analysis on IRGs of the signature. The GO terms which were the top 15 ranked by FDR were listed. (a) The GO terms and their genes. (b) FDR and count of each GO term
Fig. 5
Fig. 5
Infiltrating immune cell of the signature. (a) 22 immune cells abundance. (b) The percentage in 22 immune cells of different samples. (c) The immune cells abundance of different risk groups
Fig. 6
Fig. 6
The Nomogram of OS. (a) training cohort. (b) meta-validation cohort
Fig. 7
Fig. 7
The Correlation analysis between the signature and TIDE score
Fig. 8
Fig. 8
Validation of mRNA expression of genes generated from genes pairs. (a-f) Real-time PCR analysis of selected six genes in Het-1 A, KYSE-150 and KYSE-450 cells. Data were presented as the mean ± SE.
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References

    1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. doi: 10.3322/caac.21492. - DOI - PubMed
    1. Smyth EC, Lagergren J, Fitzgerald RC, Lordick F, Shah MA, Lagergren P, Cunningham D. Oesophageal cancer. Nat Rev Dis Primers. 2017;3:17048. doi: 10.1038/nrdp.2017.48. - DOI - PMC - PubMed
    1. Lagergren J, Smyth E, Cunningham D, Lagergren P. Oesophageal cancer. Lancet. 2017;390(10110):2383–96. doi: 10.1016/S0140-6736(17)31462-9. - DOI - PubMed
    1. Bruni D, Angell HK, Galon J. The immune contexture and immunoscore in cancer prognosis and therapeutic efficacy. Nat Rev Cancer. 2020;20(11):662–80. doi: 10.1038/s41568-020-0285-7. - DOI - PubMed
    1. Gentles AJ, Newman AM, Liu CL, Bratman SV, Feng W, Kim D, Nair VS, Xu Y, Khuong A, Hoang CD, et al. The prognostic landscape of genes and infiltrating immune cells across human cancers. Nat Med. 2015;21(8):938–45. doi: 10.1038/nm.3909. - DOI - PMC - PubMed