ArticleScientific reports2015
An advanced fragment analysis-based individualized subtype classification of pediatric acute lymphoblastic leukemia.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Examining treatment responses of diagnostic marrow in murine xenografts to predict relapse in children with acute lymphoblastic leukaemia.British journal of cancer · 2020Article
- [Clinical characteristics and gene expression profiles in children with ETV6-RUNX1 acute lymphoblastic leukemia].Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi · 2020Article
- Evaluation of a multiplex PCR assay for detection of respiratory viruses and Mycoplasma pneumoniae in oropharyngeal swab samples from outpatients.Journal of clinical laboratory analysis · 2020Article
- Clinical characteristics of the lower respiratory tract infection caused by a single infection or coinfection of the human parainfluenza virus in children.Journal of medical virology · 2019Article
- Detection of varicella-zoster virus from cerebrospinal fluid using advanced fragment analysis in a child with encephalitis: a case report.BMC infectious diseases · 2019Article
- Development and validation of an advanced fragment analysis-based assay for the detection of 22 pathogens in the cerebrospinal fluid of patients with meningitis and encephalitis.Journal of clinical laboratory analysis · 2019Article
- An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia.Cancer cell international · 2019Article
- The prognostic potential of coilin in association with p27 expression in pediatric acute lymphoblastic leukemia for disease relapse.Cancer cell international · 2018Article
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Authors and funding
18 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pediatric acute lymphoblastic leukemia (ALL) is the most common neoplasm and one of the primary causes of death in children. Its treatment is highly dependent on the correct classification of subtype. Previously, we developed a microarray-based subtype classifier based on the relative expression levels of 62 marker genes, which can predict 7 different ALL subtypes with an accuracy as high as 97% in completely independent samples. Because the classifier is based on gene expression rank values rather than actual values, the classifier enables an individualized diagnosis, without the need to reference the background distribution of the marker genes in a large number of other samples, and also enables cross platform application. Here, we demonstrate that the classifier can be extended from a microarray-based technology to a multiplex qPCR-based technology using the same set of marker genes as the advanced fragment analysis (AFA). Compared to microarray assays, the new assay system makes the convenient, low cost and individualized subtype diagnosis of pediatric ALL a reality and is clinically applicable, particularly in developing countries.
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