Identifying changes in immune cells and constructing prognostic models using immune-related genes in post-burn immunosuppression

Peng Wang; Zexin Zhang; Bin Yin; Jiayuan Li; Cheng Xialin; Wenqin Lian; Yingjun Su; Chiyu Jia

doi:10.7717/peerj.12680

Identifying changes in immune cells and constructing prognostic models using immune-related genes in post-burn immunosuppression

PeerJ. 2022 Jan 13:10:e12680. doi: 10.7717/peerj.12680. eCollection 2022.

Authors

Peng Wang^#¹, Zexin Zhang^#¹, Bin Yin¹, Jiayuan Li², Cheng Xialin¹, Wenqin Lian¹, Yingjun Su³, Chiyu Jia¹

Affiliations

¹ Department of Burns and Plastic & Wound Repair Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
² Department of Anesthesia Operation, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China.
³ Department of Burns and Plastic Surgery, Plastic Surgery Hospital, Xi'an International Medical Center, Xi'an, Shaanxi, China.

^# Contributed equally.

Abstract

Background: Burn patients are prone to infection as well as immunosuppression, which is a significant cause of death. Currently, there is a lack of prognostic biomarkers for immunosuppression in burn patients. This study was conducted to identify immune-related genes that are prognosis biomarkers in post-burn immunosuppression and potential targets for immunotherapy.

Methods: We downloaded the gene expression profiles and clinical data of 213 burn patients and 79 healthy samples from the Gene Expression Omnibus (GEO) database. Immune infiltration analysis was used to identify the proportion of circulating immune cells. Functional enrichment analyses were carried out to identify immune-related genes that were used to build miRNA-mRNA networks to screen key genes. Next, we carried out correlation analysis between immune cells and key genes that were then used to construct logistic regression models in GSE77791 and were validated in GSE19743. Finally, we determined the expression of key genes in burn patients using quantitative reverse transcription polymerase chain reaction (qRT-PCR).

Results: A total of 745 differently expressed genes were screened out: 299 were up-regulated and 446 were down-regulated. The number of Th-cells (CD4+) decreased while neutrophils increased in burn patients. The enrichment analysis showed that down-regulated genes were enriched in the T-cell activation pathway, while up-regulated genes were enriched in neutrophil activation response in burn patients. We screened out key genes (NFATC2, RORA, and CAMK4) that could be regulated by miRNA. The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945. Finally, we determined that NFATC2, RORA, and CAMK4 were down-regulated in burn patients.

Conclusion: We found that NFATC2, RORA, and CAMK4 were likely prognostic biomarkers in post-burn immunosuppression and potential immunotherapeutic targets to convert Th-cell dysfunction.

Keywords: Immune-related cell; Post-burn immunosuppression; Prognostic biomarkers; Targets of immunotherapy; miRNA.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers
Humans
Immunosuppression Therapy*
Immunotherapy
MicroRNAs* / genetics
Prognosis

Substances

MicroRNAs
Biomarkers

Grants and funding

The project was supported by the Natural Science Foundation of Fujian Province of China (No. 2019J01011); Opening Project of Fujian Key Laboratory (No. XHZDSYS202004, No. XHZDSYS202005); Starting Package of Xiang’an Hospital of Xiamen University (No. PM201809170010). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.