Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes
BackgroundOne of the most prevalent hematological system cancers is acute myeloid leukemia (AML). Efferocytosis-related genes (ERGs) and N6-methyladenosine (m6A) have an important significance in the progression of cancer, and the metastasis of tumors.MethodsThe AML-related data were collected from...
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Frontiers Media S.A.
2023-11-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1268090/full |
| _version_ | 1827661560836784128 |
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| author | Ying Wang Ting Bin Jing Tang Xiao-Jun Xu Chao Lin Bo Lu Tian-Tian Sun |
| author_facet | Ying Wang Ting Bin Jing Tang Xiao-Jun Xu Chao Lin Bo Lu Tian-Tian Sun |
| author_sort | Ying Wang |
| collection | DOAJ |
| description | BackgroundOne of the most prevalent hematological system cancers is acute myeloid leukemia (AML). Efferocytosis-related genes (ERGs) and N6-methyladenosine (m6A) have an important significance in the progression of cancer, and the metastasis of tumors.MethodsThe AML-related data were collected from The Cancer Genome Atlas (TCGA; TCGA-AML) database and Gene Expression Omnibus (GEO; GSE9476, GSE71014, and GSE13159) database. The “limma” R package and Venn diagram were adopted to identify differentially expressed ERGs (DE-ERGs). The m6A related-DE-ERGs were obtained by Spearman analysis. Subsequently, univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) were used to construct an m6A related-ERGs risk signature for AML patients. The possibility of immunotherapy for AML was explored. The pRRophetic package was adopted to calculate the IC50 of drugs for the treatment of AML. Finally, the expression of characterized genes was validated by quantitative reverse transcription-PCR (qRT-PCR).ResultsBased on m6A related-DE-ERGs, a prognostic model with four characteristic genes (UCP2, DOCK1, SLC14A1, and SLC25A1) was constructed. The risk score of model was significantly associated with the immune microenvironment of AML, with four immune cell types, 14 immune checkpoints, 20 HLA family genes and, immunophenoscore (IPS) all showing differences between the high- and low-risk groups. A total of 56 drugs were predicted to differ between the two groups, of which Erlotinib, Dasatinib, BI.2536, and bortezomib have been reported to be associated with AML treatment. The qRT-PCR results showed that the expression trends of DOCK1, SLC14A1 and SLC25A1 were consistent with the bioinformatics analysis.ConclusionIn summary, 4 m6A related- ERGs were identified and the corresponding prognostic model was constructed for AML patients. This prognostic model effectively stratified the risk of AML patients. |
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| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-03-10T00:13:01Z |
| publishDate | 2023-11-01 |
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| series | Frontiers in Immunology |
| spelling | doaj.art-5894c25d906f4230b8be91cf5c1f13052023-11-23T15:56:46ZengFrontiers Media S.A.Frontiers in Immunology1664-32242023-11-011410.3389/fimmu.2023.12680901268090Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genesYing Wang0Ting Bin1Jing Tang2Xiao-Jun Xu3Chao Lin4Bo Lu5Tian-Tian Sun6Department of Haematology. The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, ChinaDepartment of Haematology. The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, ChinaDepartment of Haematology. The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, ChinaDepartment of Haematology. The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, ChinaPediatric Hematology Laboratory, Division of Hematology/Oncology, Department of Pediatrics. The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, ChinaDepartment of Haematology. The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, ChinaDepartment of Haematology. The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, ChinaBackgroundOne of the most prevalent hematological system cancers is acute myeloid leukemia (AML). Efferocytosis-related genes (ERGs) and N6-methyladenosine (m6A) have an important significance in the progression of cancer, and the metastasis of tumors.MethodsThe AML-related data were collected from The Cancer Genome Atlas (TCGA; TCGA-AML) database and Gene Expression Omnibus (GEO; GSE9476, GSE71014, and GSE13159) database. The “limma” R package and Venn diagram were adopted to identify differentially expressed ERGs (DE-ERGs). The m6A related-DE-ERGs were obtained by Spearman analysis. Subsequently, univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) were used to construct an m6A related-ERGs risk signature for AML patients. The possibility of immunotherapy for AML was explored. The pRRophetic package was adopted to calculate the IC50 of drugs for the treatment of AML. Finally, the expression of characterized genes was validated by quantitative reverse transcription-PCR (qRT-PCR).ResultsBased on m6A related-DE-ERGs, a prognostic model with four characteristic genes (UCP2, DOCK1, SLC14A1, and SLC25A1) was constructed. The risk score of model was significantly associated with the immune microenvironment of AML, with four immune cell types, 14 immune checkpoints, 20 HLA family genes and, immunophenoscore (IPS) all showing differences between the high- and low-risk groups. A total of 56 drugs were predicted to differ between the two groups, of which Erlotinib, Dasatinib, BI.2536, and bortezomib have been reported to be associated with AML treatment. The qRT-PCR results showed that the expression trends of DOCK1, SLC14A1 and SLC25A1 were consistent with the bioinformatics analysis.ConclusionIn summary, 4 m6A related- ERGs were identified and the corresponding prognostic model was constructed for AML patients. This prognostic model effectively stratified the risk of AML patients.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1268090/fullacute myeloid leukemiaN6-methyladenosineefferocytosisprognostic risk modelbioinformaticsdrug prediction |
| spellingShingle | Ying Wang Ting Bin Jing Tang Xiao-Jun Xu Chao Lin Bo Lu Tian-Tian Sun Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes Frontiers in Immunology acute myeloid leukemia N6-methyladenosine efferocytosis prognostic risk model bioinformatics drug prediction |
| title | Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes |
| title_full | Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes |
| title_fullStr | Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes |
| title_full_unstemmed | Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes |
| title_short | Construction of an acute myeloid leukemia prognostic model based on m6A-related efferocytosis-related genes |
| title_sort | construction of an acute myeloid leukemia prognostic model based on m6a related efferocytosis related genes |
| topic | acute myeloid leukemia N6-methyladenosine efferocytosis prognostic risk model bioinformatics drug prediction |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1268090/full |
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