Ontology highlight
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?ConclusionsCompared 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.
SUBMITTER: Sun Y
PROVIDER: S-EPMC6482565 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Cancer cell international 20190425
<h4>Background</h4>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 accurac ...[more]