Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis
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 infiltrati...
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Cell and Developmental Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2022.990034/full |
| _version_ | 1818058153600745472 |
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| author | Jie Lu Guowei Zheng Ani Dong Xinyu Chang Xiting Cao Mengying Liu Xuezhong Shi Chunmei Wang Yongli Yang Xiaocan Jia |
| author_facet | Jie Lu Guowei Zheng Ani Dong Xinyu Chang Xiting Cao Mengying Liu Xuezhong Shi Chunmei Wang Yongli Yang Xiaocan Jia |
| author_sort | Jie Lu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T12:56:06Z |
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| issn | 2296-634X |
| language | English |
| last_indexed | 2024-12-10T12:56:06Z |
| publishDate | 2022-09-01 |
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| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj.art-d895fd9f788e4d7a8a377bb140f9a22a2022-12-22T01:48:06ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2022-09-011010.3389/fcell.2022.990034990034Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysisJie Lu0Guowei Zheng1Ani Dong2Xinyu Chang3Xiting Cao4Mengying Liu5Xuezhong Shi6Chunmei Wang7Yongli Yang8Xiaocan Jia9Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaChildren’s Hospital, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, ChinaImmune 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.https://www.frontiersin.org/articles/10.3389/fcell.2022.990034/fullacute myelogenous leukemiasingle-cell RNA-seqprognostic modelSsGSEAtumor immune microenvironment |
| spellingShingle | Jie Lu Guowei Zheng Ani Dong Xinyu Chang Xiting Cao Mengying Liu Xuezhong Shi Chunmei Wang Yongli Yang Xiaocan Jia Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis Frontiers in Cell and Developmental Biology acute myelogenous leukemia single-cell RNA-seq prognostic model SsGSEA tumor immune microenvironment |
| title | Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis |
| title_full | Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis |
| title_fullStr | Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis |
| title_full_unstemmed | Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis |
| title_short | Prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single-cell sequencing analysis |
| title_sort | prognostic characteristics of immune subtypes associated with acute myeloid leukemia and their identification in cell subsets based on single cell sequencing analysis |
| topic | acute myelogenous leukemia single-cell RNA-seq prognostic model SsGSEA tumor immune microenvironment |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2022.990034/full |
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