Evidence map›Paper›PMID 36211454›Full record

ArticleFrontiers in cell and developmental biology2022

Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis.

Jie Lu, Guowei Zheng, Ani Dong, Xinyu Chang, Xiting Cao, Mengying Liu, Xuezhong Shi, Chunmei Wang, Yongli Yang, Xiaocan Jia

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Article in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Jie LuDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Guowei ZhengDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Ani DongDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Xinyu ChangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Xiting CaoDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Mengying LiuDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Xuezhong ShiDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Chunmei WangChildren's Hospital, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yongli YangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Xiaocan JiaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune genes play an important role in the development and progression of acute myeloid leukemia (AML). However, the role of immune genes in the prognosis and microenvironment of AML remains unclear. In this study, we analyzed 151 AML patients in the TCGA database for relevant immune cell infiltration. AML patients were divided into high and low immune cell infiltration clusters based on ssGSEA results. Immune-related pathways, AML pathways and glucose metabolism pathways were enriched in the high immune cell infiltration cluster. Then we screened the differential immune genes between the two immune cell infiltration clusters. Nine prognostic immune genes were finally identified in the train set by LASSO-Cox regression. We constructed a model in the train set based on the nine prognostic immune genes and validated the predictive capability in the test set. The areas under the ROC curve of the train set and the test set for ROC at 1, 3, 5 years were 0.807, 0.813, 0.815, and 0.731, 0.745, 0.830, respectively. The areas under ROC curve of external validation set in 1, 3, and 5 years were 0.564, 0.619, and 0.614, respectively. People with high risk scores accompanied by high TMB had been detected with the worst prognosis. Single-cell sequencing analysis revealed the expression of prognostic genes in AML cell subsets and pseudo-time analysis described the differentiation trajectory of cell subsets. In conclusion, our results reveal the characteristics of immune microenvironment and cell subsets of AML, while it still needs to be confirmed in larger samples studies. The prognosis model constructed with nine key immune genes can provide a new method to assess the prognosis of AML patients.

Indexed as

acute myelogenous leukemiaprognostic modelsingle-cell RNA-seqSsGSEAtumor immune microenvironment

Identifiers

PMID36211454
PMCPMC9540204

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