Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutation
Objectives The TP53 mutation, a prevalent tumor suppressor gene alteration, is linked to chemotherapy resistance, increased relapse rates and diminished overall survival (OS) in acute myeloid leukemia (AML) patients.Methods In this study, we characterize the TP53 mutation phenotypes across various A...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Hematology |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/16078454.2024.2400620 |
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| author | Gelan Zhu Jiayi Cai Wanbin Fu Yue Sun Ting Wang Hua Zhong |
| author_facet | Gelan Zhu Jiayi Cai Wanbin Fu Yue Sun Ting Wang Hua Zhong |
| author_sort | Gelan Zhu |
| collection | DOAJ |
| description | Objectives The TP53 mutation, a prevalent tumor suppressor gene alteration, is linked to chemotherapy resistance, increased relapse rates and diminished overall survival (OS) in acute myeloid leukemia (AML) patients.Methods In this study, we characterize the TP53 mutation phenotypes across various AML cohorts utilizing The Cancer Genome Atlas (TCGA) data. We devised a TP53-related prognostic signature derived from differentially expressed genes between mutated and wild-type TP53 AML specimens. In-depth analyses were conducted, encompassing genetic variation, immune cell infiltration and prognostic stratification.Results A six-gene TP53-related signature was established using least absolute shrinkage and selection operator (LASSO)–Cox regression, demonstrating robust prognostic predictability. This signature exhibited strong performance in both the OHSU validation cohorts, an independent Gene Expression Omnibus (GEO) validation cohort (GSE71014) and proved by results of the in vivo experiment. Finally, we used single cell database (GSE198681) to observe the characteristics of these six genes.Discussion Our study may facilitate the development of efficacious therapeutic approaches and provide a novel idea for future research. Conclusion: The TP53-related signature and pattern hold the potential to refine prognostic stratification and underscore emerging targeted therapies. |
| format | Article |
| id | doaj-art-c21c1b2a07df4ed8a0ca3e1b1a9cdf34 |
| institution | OA Journals |
| issn | 1607-8454 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Hematology |
| spelling | doaj-art-c21c1b2a07df4ed8a0ca3e1b1a9cdf342025-08-20T01:59:09ZengTaylor & Francis GroupHematology1607-84542024-12-0129110.1080/16078454.2024.2400620Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutationGelan Zhu0Jiayi Cai1Wanbin Fu2Yue Sun3Ting Wang4Hua Zhong5Department of Hematology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaDepartment of Hematology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaDepartment of Hematology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaDepartment of Hematology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaDepartment of Hematology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaDepartment of Hematology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, People’s Republic of ChinaObjectives The TP53 mutation, a prevalent tumor suppressor gene alteration, is linked to chemotherapy resistance, increased relapse rates and diminished overall survival (OS) in acute myeloid leukemia (AML) patients.Methods In this study, we characterize the TP53 mutation phenotypes across various AML cohorts utilizing The Cancer Genome Atlas (TCGA) data. We devised a TP53-related prognostic signature derived from differentially expressed genes between mutated and wild-type TP53 AML specimens. In-depth analyses were conducted, encompassing genetic variation, immune cell infiltration and prognostic stratification.Results A six-gene TP53-related signature was established using least absolute shrinkage and selection operator (LASSO)–Cox regression, demonstrating robust prognostic predictability. This signature exhibited strong performance in both the OHSU validation cohorts, an independent Gene Expression Omnibus (GEO) validation cohort (GSE71014) and proved by results of the in vivo experiment. Finally, we used single cell database (GSE198681) to observe the characteristics of these six genes.Discussion Our study may facilitate the development of efficacious therapeutic approaches and provide a novel idea for future research. Conclusion: The TP53-related signature and pattern hold the potential to refine prognostic stratification and underscore emerging targeted therapies.https://www.tandfonline.com/doi/10.1080/16078454.2024.2400620Prognostic modelacute myeloid leukemiaimmune landscapeTP53 mutation |
| spellingShingle | Gelan Zhu Jiayi Cai Wanbin Fu Yue Sun Ting Wang Hua Zhong Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutation Hematology Prognostic model acute myeloid leukemia immune landscape TP53 mutation |
| title | Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutation |
| title_full | Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutation |
| title_fullStr | Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutation |
| title_full_unstemmed | Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutation |
| title_short | Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutation |
| title_sort | elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with tp53 mutation |
| topic | Prognostic model acute myeloid leukemia immune landscape TP53 mutation |
| url | https://www.tandfonline.com/doi/10.1080/16078454.2024.2400620 |
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