Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis
Jiaqi Tang1
Lin Luo1
Bakwatanisa Bosco2
Ning Li2
Bin Huang2
Rongrong Wu2
Zihan Lin2
Ming Hong3
Wenjie Liu3
Lingxiang Wu2
Wei Wu2
Mengyan Zhu2
Quanzhong Liu2
Peng Xia2
Miao Yu2
Diru Yao2
Sali Lv2
Ruohan Zhang2
Wentao Liu4
Qianghu Wang5
Kening Li6
1.Department of Bioinformatics,School of Biomedical Engineering and Informatics,Nanjing Medical University,Nanjing,Jiangsu 211166,China;Department of Hematology of the Affiliated Huai'an No.1 People's Hospital of Nanjing Medical University,Northern Jiangsu Institute of Clinical Medicine,Huai'an,Jiangsu 223300,China;Collaborative Innovation Center for Personalized Cancer Medicine,Jiangsu Key Lab of Cancer Biomarkers,Prevention and Treatment,Nanjing Medical University,Nanjing,Jiangsu 211166,China2.Department of Bioinformatics,School of Biomedical Engineering and Informatics,Nanjing Medical University,Nanjing,Jiangsu 211166,China;Collaborative Innovation Center for Personalized Cancer Medicine,Jiangsu Key Lab of Cancer Biomarkers,Prevention and Treatment,Nanjing Medical University,Nanjing,Jiangsu 211166,China3.Department of Hematology,the First Affiliated Hospital of Nanjing Medical University,Jiangsu Province Hospital,Nanjing,Jiangsu 210029,China;Key Laboratory of Hematology of Nanjing Medical University,Nanjing,Jiangsu 210029,China4.Department of Pharmacology,School of Basic Medical Sciences,Nanjing Medical University,Nanjing,Jiangsu 211166,China5.Department of Bioinformatics,School of Biomedical Engineering and Informatics,Nanjing Medical University,Nanjing,Jiangsu 211166,China;Collaborative Innovation Center for Personalized Cancer Medicine,Jiangsu Key Lab of Cancer Biomarkers,Prevention and Treatment,Nanjing Medical University,Nanjing,Jiangsu 211166,China;The Affiliated Cancer Hospital of Nanjing Medical University,Jiangsu Cancer Hospital,Jiangsu Institute of Cancer Research,Nanjing,Jiangsu 210002,China6.Department of Bioinformatics,School of Biomedical Engineering and Informatics,Nanjing Medical University,Nanjing,Jiangsu 211166,China;Department of Hematology of the Affiliated Huai'an No.1 People's Hospital of Nanjing Medical University,Northern Jiangsu Institute of Clinical Medicine,Huai'an,Jiangsu 223300,China
摘要：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 the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards 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 the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low 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.
机标关键词：identificationleukemiaprognosisanalysissurfacecellacutebased
分类号：R733.71(造血器及淋巴系肿瘤)
论文发表日期：2024-07-30
在线出版日期：2026-03-31（本平台首次上网日期，不代表文献的发表时间）
页数：17( 中插9,397-412 )
英文信息