机构:[1]Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics (Capital Medical University), Key Laboratory of Major Diseases in Children, Ministry of Education, Hematology Oncology Center, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, 56 Nanlishi Road, Beijing 100045, China.医技科室职能科室临床流行病与循证医学中心血液中心首都医科大学附属北京儿童医院[2]School of Computer Science and Technology, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin 150001, Heilongjiang, China.[3]Center for Clinical Epidemiology & Evidence?based Medicine, Beijing Children’s Hospital Medical, Capital Medical University, National Center for Children’s Health, 56 Nanlishi Road, Beijing 100045, China.职能科室临床流行病与循证医学中心首都医科大学附属北京儿童医院[4]Ningbo Health Gene Technologies Ltd., Ningbo 315800, Zhejiang, China.[5]Institute of Medical Biology, Chinese Academy of Medicine Sciences and Peking Union Medical College, 935 Jiaoling Road, Kunming 650031, Yunnan, China.
BackgroundAcute lymphoblastic leukemia (ALL) contains cytogenetically distinct subtypes that respond differently to cytotoxic drugs. Therefore, subtype classification is important and indispensable in ALL diagnosis. In our previous study, we identified some marker genes in childhood ALL by means of microarray technology and, furthermore, detected the relative expression levels of 57 marker genes and built a comparatively convenient and cost-effective classifier with a prediction accuracy as high as 94% based on the advanced fragment analysis (AFA) technique.MethodsA more convenient improved AFA (iAFA) technique with one-step multiplex RT-PCR and an anti-contamination system was developed to detect 57 marker genes for ALL.ResultsThe iAFA assay is much easier and more convenient to perform than the previous AFA assay and has a prediction accuracy of 95.29% in ALL subtypes. The anti-contamination system could effectively prevent the occurrence of lab DNA contamination. We also showed that marker gene expression profiles in pediatric ALL revealed 2 subgroups with different outcomes. Most ALL patients (95.8%) had a good-risk genetic profile, and only 4.2% of ALL patients had a poor-risk genetic profile, which predicted an event-free survival (EFS) of 93.61.3% vs 18.8 +/- 9.8% at 5years, respectively (P<0.001).Conclusions p id=Par4 Compared to the previous AFA assay, the iAFA technique is more functional, time-saving and labor-saving. It could be a valuable clinical tool for the classification and risk stratification of pediatric ALL patients.
基金:
Beijing Municipal Administration of Hospitals Clinical Medicine Development Special Grant [ZY201404]; Beijing Municipal Administration of Hospitals DengFeng Program [DFL20151101]; Capital Health and Development Special Grant [2016-1-2091]; Natural Science Foundation of ChinaNational Natural Science Foundation of China [61471147]; Natural Science Foundation of Heilongjiang ProvinceNatural Science Foundation of Heilongjiang Province [F2016016]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities; NSRIF [2017037]; National Key Research and Development Program of China [2016YFC0901905]
第一作者机构:[1]Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics (Capital Medical University), Key Laboratory of Major Diseases in Children, Ministry of Education, Hematology Oncology Center, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, 56 Nanlishi Road, Beijing 100045, China.
通讯作者:
通讯机构:[1]Beijing Key Laboratory of Pediatric Hematology Oncology, National Key Discipline of Pediatrics (Capital Medical University), Key Laboratory of Major Diseases in Children, Ministry of Education, Hematology Oncology Center, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, 56 Nanlishi Road, Beijing 100045, China.[2]School of Computer Science and Technology, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin 150001, Heilongjiang, China.
推荐引用方式(GB/T 7714):
Sun Yanran,Zhang Qiaosheng,Feng Guoshuang,et al.An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia[J].CANCER CELL INTERNATIONAL.2019,19(1):-.doi:10.1186/s12935-019-0825-y.
APA:
Sun, Yanran,Zhang, Qiaosheng,Feng, Guoshuang,Chen, Zhen,Gao, Chao...&Zheng, Huyong.(2019).An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia.CANCER CELL INTERNATIONAL,19,(1)
MLA:
Sun, Yanran,et al."An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia".CANCER CELL INTERNATIONAL 19..1(2019):-