A novel 5-gene prognostic signature to improve risk stratification of cytogenetically normal acute myeloid leukemia
- 01.06.2023
- Research
Erschienen in:
- Verfasst von
- Cong Deng
- Tiansheng Zeng
- Pei Zhu
- Sijie Zhao
- Zeyong Huang
- Wenhui Huang
- Wenjuan Zhang
- Xiaojuan Huang
- Lin Fu
- Erschienen in
- Journal of Cancer Research and Clinical Oncology | Ausgabe 12/2023
Abstract
Purpose
Prognostic prediction is a challenging task in cytogenetically normal acute myeloid leukemia (CN-AML) patients. In this study, we aimed at developing a novel prognostic signature to predict and stratify the survival of CN-AML patients.
Methods
Using a training dataset (GSE12417), 5-gene prognostic signature was established to predict survival of CN-AML patients. The prognostic performance of this prognostic signature was further validated in testing dataset (TCGA CN-AML cohort) and validation dataset (GSE6891 CN-AML cohort).
Results
In training, testing and validation datasets, the increased 5-gene risk score was significantly related with inferior overall survival (OS) of patients, and the area under the receiver operating characteristic curve (AUC) demonstrated that our prognostic signature had overall prediction accuracy. The excellent prognostic value of the 5-gene prognostic signature was also supported by the comparison with three previously proposed prognostic models. For the intermediate-risk CN-AML patients and the CN-AML patients with FLT3 or NPM1 mutation, our model could also well dichotomize them into two subgroups with distinct prognosis. Multivariate analysis demonstrated that 5-gene risk score was the only independent risk factor in TCGA CN-AML cohort. Nomogram including the 5-gene risk score performed well in predicting 1-year, 2-year and 3-year OS.
Conclusion
In summary, our novel 5-gene prognostic signature facilitated the improvement in risk stratification of CN-AML patients.
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- Titel
- A novel 5-gene prognostic signature to improve risk stratification of cytogenetically normal acute myeloid leukemia
- Verfasst von
-
Cong Deng
Tiansheng Zeng
Pei Zhu
Sijie Zhao
Zeyong Huang
Wenhui Huang
Wenjuan Zhang
Xiaojuan Huang
Lin Fu
- Publikationsdatum
- 01.06.2023
- Verlag
- Springer Berlin Heidelberg
- Erschienen in
-
Journal of Cancer Research and Clinical Oncology / Ausgabe 12/2023
Print ISSN: 0171-5216
Elektronische ISSN: 1432-1335 - DOI
- https://doi.org/10.1007/s00432-023-04884-y
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