Construction of a prognostic model of acute myeloid leukemia associated with immunogenic cell death

ABSTRACT

Background

Immunogenic cell death (ICD)is a kind of regulatory cell death, which causes a series of antigen-specific adaptive immune responses by generating and emitting some danger signals or damage-associated molecular patterns (DAMPs). At present, little is known about the prognostic value of ICD and its related processes in acute myeloid leukemia (AML). The aim of the study was to explore the relationship between ICD and tumor immune microenvironment changes in AML.

Research Design & Methods

In the study, AML samples were divided into two groups by consensus clustering analysis, and then gene enrichment analysis and GSEA analysis were performed on the ICD high expression group. Furthermore, CIBERSORT was used to analyze the tumor microenvironment and immune characteristics of AML. Finally, a prognostic model related to ICD was constructed by using univariate and multivariate regression analysis.

Results

ICD was divided into two groups according to the level of ICD gene expression. The ICD high expression group was associated with good clinical results and high levels of immune cell infiltration.

Conclusions

The study constructed and verified the prognostic characteristics of AML related to ICD, which has important value in predicting the overall survival time of AML patients.

KEYWORDS:

• Immunogenic cell death
• AML
• immunotherapy
• prognosis
• tumor immune microenvironment

Acknowledgments

All authors would like to thank the TCGA database.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

X Sheng, J Lu: Conceptualization, Methodology, Data curation, Formal analysis and Writing manuscript. M Huang: Data curation. K Fan: Methodology. J Wang: Formal analysis. Q Lu: Revising manuscript critically for intellectual content.

All authors have read and agreed to the published version of the manuscript.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors https://doi.org/10.6084/m9.figshare.21200566.v3.

Additional information

Funding

This paper was funded by Xiamen science and technology guidance project (Grant Code: 3502Z20199174) and Natural Science Foundation of Fujian Province (Grant Code: 2019D009).