2. Academic Validation
  3. An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia

An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia

  • Cancer Cell Int. 2019 Apr 25:19:110. doi: 10.1186/s12935-019-0825-y.
Yanran Sun 1,  Qiaosheng Zhang 2,  Guoshuang Feng 3,  Zhen Chen 4,  Chao Gao 1,  Shuguang Liu 1,  Ruidong Zhang 1,  Han Zhang 1 5,  Xueling Zheng 1,  Wenyu Gong 1,  Yadong Wang 2,  Yong Wu 4,  Jie Li 2,  Huyong Zheng 1
Affiliations

Affiliations

  • 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 2School 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.
  • 4 4Ningbo Health Gene Technologies Ltd., Ningbo, 315800 Zhejiang China.
  • 5 Present Address: Institute of Medical Biology, Chinese Academy of Medicine Sciences and Peking Union Medical College, 935 Jiaoling Road, Kunming, 650031 Yunnan China.
PMID: 31049032 DOI: 10.1186/s12935-019-0825-y
Abstract

Background: Acute 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.

Methods: A 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.

Results: The 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 93.6 ± 1.3% vs 18.8 ± 9.8% at 5 years, respectively (P < 0.001).

Conclusions: 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.

Keywords

Acute lymphoblastic leukemia; Classification; Pediatric; Prognosis; Risk stratification.

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