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An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia
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 o...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482565/ https://www.ncbi.nlm.nih.gov/pubmed/31049032 http://dx.doi.org/10.1186/s12935-019-0825-y |
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author | Sun, Yanran Zhang, Qiaosheng Feng, Guoshuang Chen, Zhen Gao, Chao Liu, Shuguang Zhang, Ruidong Zhang, Han Zheng, Xueling Gong, Wenyu Wang, Yadong Wu, Yong Li, Jie Zheng, Huyong |
author_facet | Sun, Yanran Zhang, Qiaosheng Feng, Guoshuang Chen, Zhen Gao, Chao Liu, Shuguang Zhang, Ruidong Zhang, Han Zheng, Xueling Gong, Wenyu Wang, Yadong Wu, Yong Li, Jie Zheng, Huyong |
author_sort | Sun, Yanran |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-019-0825-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6482565 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64825652019-05-02 An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia Sun, Yanran Zhang, Qiaosheng Feng, Guoshuang Chen, Zhen Gao, Chao Liu, Shuguang Zhang, Ruidong Zhang, Han Zheng, Xueling Gong, Wenyu Wang, Yadong Wu, Yong Li, Jie Zheng, Huyong Cancer Cell Int Primary Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12935-019-0825-y) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-25 /pmc/articles/PMC6482565/ /pubmed/31049032 http://dx.doi.org/10.1186/s12935-019-0825-y Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Primary Research Sun, Yanran Zhang, Qiaosheng Feng, Guoshuang Chen, Zhen Gao, Chao Liu, Shuguang Zhang, Ruidong Zhang, Han Zheng, Xueling Gong, Wenyu Wang, Yadong Wu, Yong Li, Jie Zheng, Huyong An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia |
title | An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia |
title_full | An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia |
title_fullStr | An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia |
title_full_unstemmed | An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia |
title_short | An improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia |
title_sort | improved advanced fragment analysis-based classification and risk stratification of pediatric acute lymphoblastic leukemia |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482565/ https://www.ncbi.nlm.nih.gov/pubmed/31049032 http://dx.doi.org/10.1186/s12935-019-0825-y |
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