4.6

CiteScore

2.2

Impact Factor
  • ISSN 1674-8301
  • CN 32-1810/R
Jiaqi Tang, Lin Luo, Bakwatanisa Bosco, Ning Li, Bin Huang, Rongrong Wu, Zihan Lin, Ming Hong, Wenjie Liu, Lingxiang Wu, Wei Wu, Mengyan Zhu, Quanzhong Liu, Peng Xia, Miao Yu, Diru Yao, Sali Lv, Ruohan Zhang, Wentao Liu, Qianghu Wang, Kening Li. Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis[J]. The Journal of Biomedical Research. DOI: 10.7555/JBR.38.20240065
Citation: Jiaqi Tang, Lin Luo, Bakwatanisa Bosco, Ning Li, Bin Huang, Rongrong Wu, Zihan Lin, Ming Hong, Wenjie Liu, Lingxiang Wu, Wei Wu, Mengyan Zhu, Quanzhong Liu, Peng Xia, Miao Yu, Diru Yao, Sali Lv, Ruohan Zhang, Wentao Liu, Qianghu Wang, Kening Li. Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis[J]. The Journal of Biomedical Research. DOI: 10.7555/JBR.38.20240065

Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

  • Given the extremely high inter-patient heterogeneity of acute myeloid leukemia (AML), the identification of biomarkers for prognostic assessment and therapeutic guidance is critical. Cell surface markers (CSMs) have been shown to play an important role in AML leukemogenesis and progression. In this study, we evaluated the prognostic potential of all human CSMs in AML patients based on differential gene expression analysis and univariable Cox regression analysis. By using multi-model analysis, including Adaptive LASSO regression, LASSO regression, and Elastic Net, we constructed a 9-CSMs prognostic model for risk stratification of AML patients. The predictive value of the 9-CSMs risk score was further validated in three independent datasets. Multivariate Cox regression analysis showed that the risk score was an independent prognostic factor for AML patients. AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with lower scores. Notably, single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance. Furthermore, PI3K inhibitors were identified as potential treatments for these high-risk patients. In conclusion, we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.
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