A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia
ABSTRACTObjectives Acute myeloid leukemia (AML) is one of the common hematological diseases with low survival rates. Studies have highlighted the dysregulated expression of immune-related and exosome-related genes (ERGs) in cancers. Nevertheless, it remains to be determined whether combining these g...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Hematology |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/16078454.2023.2300855 |
| _version_ | 1797362183499153408 |
|---|---|
| author | Zenghui Fang Jiali Fu Xin Chen |
| author_facet | Zenghui Fang Jiali Fu Xin Chen |
| author_sort | Zenghui Fang |
| collection | DOAJ |
| description | ABSTRACTObjectives Acute myeloid leukemia (AML) is one of the common hematological diseases with low survival rates. Studies have highlighted the dysregulated expression of immune-related and exosome-related genes (ERGs) in cancers. Nevertheless, it remains to be determined whether combining these genes have a prognostic significance in AML.Methods Immune-ERG profiles for 151 AML patients from TCGA were analyzed. A risk model was constructed and optimized through the combination of univariate Cox regression and LASSO regression analysis. GEO datasets were utilized as the external validation for the robustness of the risk model. In addition, we performed KEGG and GO enrichment analyses to investigate the role played by these genes in AML. The variations in immune cell infiltrations among risk groups were assessed through four algorithms. Expression of hub gene in specific cell was analyzed by single-cell RNA seq.Results A total of 85 immune-ERGs associated with prognosis were identified, enabling the construction of a risk model for AML. The risk model based on five immune-ERGs (CD37, NUCB2, LSP1, MGST1, and PLXNB1) demonstrated a correlation with the clinical outcomes. Additionally, age, FAB classification, cytogenetics risk, and risk score were identified as independent prognostic factors. The five immune-ERGs exhibited correlations with cytokine-cytokine receptor interaction, and antigen processing and presentation. Notably, the risk model demonstrated significant associations with immune responses and the expression of immune checkpoints.Conclusions An immune-ERG-based risk model was developed to effectively predict prognostic outcomes for AML patients. There is potential for immune therapy in AML targeting the five hub genes. |
| first_indexed | 2024-03-08T16:04:44Z |
| format | Article |
| id | doaj.art-abda9ac6532b490fb64b825da13b403d |
| institution | Directory Open Access Journal |
| issn | 1607-8454 |
| language | English |
| last_indexed | 2024-03-08T16:04:44Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Hematology |
| spelling | doaj.art-abda9ac6532b490fb64b825da13b403d2024-01-08T07:46:14ZengTaylor & Francis GroupHematology1607-84542024-12-0129110.1080/16078454.2023.2300855A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemiaZenghui Fang0Jiali Fu1Xin Chen2Department of Clinical Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of ChinaDepartment of Clinical Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of ChinaDepartment of Clinical Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of ChinaABSTRACTObjectives Acute myeloid leukemia (AML) is one of the common hematological diseases with low survival rates. Studies have highlighted the dysregulated expression of immune-related and exosome-related genes (ERGs) in cancers. Nevertheless, it remains to be determined whether combining these genes have a prognostic significance in AML.Methods Immune-ERG profiles for 151 AML patients from TCGA were analyzed. A risk model was constructed and optimized through the combination of univariate Cox regression and LASSO regression analysis. GEO datasets were utilized as the external validation for the robustness of the risk model. In addition, we performed KEGG and GO enrichment analyses to investigate the role played by these genes in AML. The variations in immune cell infiltrations among risk groups were assessed through four algorithms. Expression of hub gene in specific cell was analyzed by single-cell RNA seq.Results A total of 85 immune-ERGs associated with prognosis were identified, enabling the construction of a risk model for AML. The risk model based on five immune-ERGs (CD37, NUCB2, LSP1, MGST1, and PLXNB1) demonstrated a correlation with the clinical outcomes. Additionally, age, FAB classification, cytogenetics risk, and risk score were identified as independent prognostic factors. The five immune-ERGs exhibited correlations with cytokine-cytokine receptor interaction, and antigen processing and presentation. Notably, the risk model demonstrated significant associations with immune responses and the expression of immune checkpoints.Conclusions An immune-ERG-based risk model was developed to effectively predict prognostic outcomes for AML patients. There is potential for immune therapy in AML targeting the five hub genes.https://www.tandfonline.com/doi/10.1080/16078454.2023.2300855Immuneexosomerisk scoreacute myeloid leukemiatumor environmentprognosis |
| spellingShingle | Zenghui Fang Jiali Fu Xin Chen A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia Hematology Immune exosome risk score acute myeloid leukemia tumor environment prognosis |
| title | A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia |
| title_full | A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia |
| title_fullStr | A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia |
| title_full_unstemmed | A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia |
| title_short | A combined immune and exosome-related risk signature as prognostic biomakers in acute myeloid leukemia |
| title_sort | combined immune and exosome related risk signature as prognostic biomakers in acute myeloid leukemia |
| topic | Immune exosome risk score acute myeloid leukemia tumor environment prognosis |
| url | https://www.tandfonline.com/doi/10.1080/16078454.2023.2300855 |
| work_keys_str_mv | AT zenghuifang acombinedimmuneandexosomerelatedrisksignatureasprognosticbiomakersinacutemyeloidleukemia AT jialifu acombinedimmuneandexosomerelatedrisksignatureasprognosticbiomakersinacutemyeloidleukemia AT xinchen acombinedimmuneandexosomerelatedrisksignatureasprognosticbiomakersinacutemyeloidleukemia AT zenghuifang combinedimmuneandexosomerelatedrisksignatureasprognosticbiomakersinacutemyeloidleukemia AT jialifu combinedimmuneandexosomerelatedrisksignatureasprognosticbiomakersinacutemyeloidleukemia AT xinchen combinedimmuneandexosomerelatedrisksignatureasprognosticbiomakersinacutemyeloidleukemia |