Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysis
Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy. The bone marrow (BM) microenvironment in AML plays an important role in leukemogenesis, drug resistance and leukemia relapse. In this study, we aimed to identify reliable immune-related biomarkers for AML prognosis by m...
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| Format: | Article |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.925615/full |
| _version_ | 1818498669459013632 |
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| author | Fu Li Jiao Cai Jiao Cai Jia Liu Shi-cang Yu Xi Zhang Yi Su Lei Gao |
| author_facet | Fu Li Jiao Cai Jiao Cai Jia Liu Shi-cang Yu Xi Zhang Yi Su Lei Gao |
| author_sort | Fu Li |
| collection | DOAJ |
| description | Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy. The bone marrow (BM) microenvironment in AML plays an important role in leukemogenesis, drug resistance and leukemia relapse. In this study, we aimed to identify reliable immune-related biomarkers for AML prognosis by multiomics analysis. We obtained expression profiles from The Cancer Genome Atlas (TCGA) database and constructed a LASSO-Cox regression model to predict the prognosis of AML using multiomics bioinformatic analysis data. This was followed by independent validation of the model in the GSE106291 (n=251) data set and mutated genes in clinical samples for predicting overall survival (OS). Molecular docking was performed to predict the most optimal ligands to the genes in prognostic model. The single-cell RNA sequence dataset GSE116256 was used to clarify the expression of the hub genes in different immune cell types. According to their significant differences in immune gene signatures and survival trends, we concluded that the immune infiltration-lacking subtype (IL type) is associated with better prognosis than the immune infiltration-rich subtype (IR type). Using the LASSO model, we built a classifier based on 5 hub genes to predict the prognosis of AML (risk score = -0.086×ADAMTS3 + 0.180×CD52 + 0.472×CLCN5 - 0.356×HAL + 0.368×ICAM3). In summary, we constructed a prognostic model of AML using integrated multiomics bioinformatic analysis that could serve as a therapeutic classifier. |
| first_indexed | 2024-12-10T20:18:43Z |
| format | Article |
| id | doaj.art-ba22484ed7674f79b43d5ebfa5a7a41f |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-10T20:18:43Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-ba22484ed7674f79b43d5ebfa5a7a41f2022-12-22T01:35:07ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-08-011210.3389/fonc.2022.925615925615Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysisFu Li0Jiao Cai1Jiao Cai2Jia Liu3Shi-cang Yu4Xi Zhang5Yi Su6Lei Gao7Medical Center of Hematology, Xinqiao Hospital, Army Medical University, Chongqing, ChinaDepartment of Hematology and Hematopoietic Stem Cell Transplantation Centre, The General Hospital of Western Theater Command, Chengdu, ChinaDepartment of Stem Cell and Regenerative Medicine, Southwest Hospital, Army Medical University, Chongqing, ChinaMedical Center of Hematology, Xinqiao Hospital, Army Medical University, Chongqing, ChinaDepartment of Stem Cell and Regenerative Medicine, Southwest Hospital, Army Medical University, Chongqing, ChinaMedical Center of Hematology, Xinqiao Hospital, Army Medical University, Chongqing, ChinaDepartment of Hematology and Hematopoietic Stem Cell Transplantation Centre, The General Hospital of Western Theater Command, Chengdu, ChinaMedical Center of Hematology, Xinqiao Hospital, Army Medical University, Chongqing, ChinaAcute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy. The bone marrow (BM) microenvironment in AML plays an important role in leukemogenesis, drug resistance and leukemia relapse. In this study, we aimed to identify reliable immune-related biomarkers for AML prognosis by multiomics analysis. We obtained expression profiles from The Cancer Genome Atlas (TCGA) database and constructed a LASSO-Cox regression model to predict the prognosis of AML using multiomics bioinformatic analysis data. This was followed by independent validation of the model in the GSE106291 (n=251) data set and mutated genes in clinical samples for predicting overall survival (OS). Molecular docking was performed to predict the most optimal ligands to the genes in prognostic model. The single-cell RNA sequence dataset GSE116256 was used to clarify the expression of the hub genes in different immune cell types. According to their significant differences in immune gene signatures and survival trends, we concluded that the immune infiltration-lacking subtype (IL type) is associated with better prognosis than the immune infiltration-rich subtype (IR type). Using the LASSO model, we built a classifier based on 5 hub genes to predict the prognosis of AML (risk score = -0.086×ADAMTS3 + 0.180×CD52 + 0.472×CLCN5 - 0.356×HAL + 0.368×ICAM3). In summary, we constructed a prognostic model of AML using integrated multiomics bioinformatic analysis that could serve as a therapeutic classifier.https://www.frontiersin.org/articles/10.3389/fonc.2022.925615/fullbioinformaticAML – acute myeloid leukaemiaprognostic modelLASSOcox regression model |
| spellingShingle | Fu Li Jiao Cai Jiao Cai Jia Liu Shi-cang Yu Xi Zhang Yi Su Lei Gao Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysis Frontiers in Oncology bioinformatic AML – acute myeloid leukaemia prognostic model LASSO cox regression model |
| title | Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysis |
| title_full | Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysis |
| title_fullStr | Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysis |
| title_full_unstemmed | Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysis |
| title_short | Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysis |
| title_sort | construction of a solid cox model for aml patients based on multiomics bioinformatic analysis |
| topic | bioinformatic AML – acute myeloid leukaemia prognostic model LASSO cox regression model |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.925615/full |
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