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Title: Gene expression overlap affects karyotype prediction in pediatric acute lymphoblastic leukemia

Abstract

Leukemia is the most common childhood malignancy in the United States. Acute lymphoblastic leukemia (ALL) accounts for 75% of new leukemia cases in children. Although the outcome for children with ALL has improved dramatically over the past three decades, 25% of children with ALL still develop recurrent disease. Current risk classification schemes in pediatric ALL use clinical and laboratory parameters such as age and initial white blood cell count, as well as the presence of specific ALL-associated cytogenetic or molecular genetic abnormalities. Stratification based on cytogenetic analysis and molecular genetic detection consider B precursor ALL translocations such as t(12;21)(TEL-AML1), t(1;19)(E2A-PBX1) and t(9;22)(BCR-ABL), as well as numerical imbalances such as hyperdiploidy, specific chromosome trisomies or hypodiploidy. Despite such efforts, current diagnosis and risk classification schemes in pediatric ALL remain imprecise. In particular, it is likely that a significant number of higher-risk children are currently overtreated and could be cured with less intensive regimens, resulting in fewer toxicities and long-term side effects. Finally and conversely, a significant number of children in lower-risk categories still relapse and precise means to prospectively identify them have remained elusive.

Authors:
 [1];  [2];  [2];  [1];  [3];  [3];  [4];  [4];  [4];  [4];  [4];  [2];  [2];  [2];  [2];  [2];  [2];  [4];  [5];  [6] more »;  [7];  [2] « less
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Biology
  2. Univ. of New Mexico, Albuquerque, NM (United States). School of Medicine. Dept. of Pathology. Cancer Research and Treatment Center
  3. Univ. of New Mexico, Albuquerque, NM (United States). School of Medicine. Dept. of Pathology. Cancer Research and Treatment Center. Dept. of Computer Science, Mathematics and Statistics, Physics and Astronomy. Center for High Performance Computing
  4. Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Computer Science, Mathematics and Statistics, Physics and Astronomy. Center for High Performance Computing
  5. Univ. of Florida, Gainesville, FL (United States). General Clinical Research Center
  6. Univ. of Alabama, Birmingham, AL (United States). Dept. of Genetics
  7. Medical College of Wisconsin, Milwaukee, WI (United States). Dept. of Pediatrics. Midwest Children’s Cancer Center
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of New Mexico, Albuquerque, NM (United States)
Sponsoring Org.:
USDOE; SNL Laboratory Directed Research and Development (LDRD) Program; National Inst. of Health (NIH) (United States); The Leukemia and Lymphoma Society (United States)
OSTI Identifier:
1426985
Report Number(s):
SAND2007-0699J
Journal ID: ISSN 0887-6924; 524123
Grant/Contract Number:  
AC04-94AL85000; NCI CA88361; NCI CA114762
Resource Type:
Accepted Manuscript
Journal Name:
Leukemia
Additional Journal Information:
Journal Volume: 21; Journal Issue: 6; Journal ID: ISSN 0887-6924
Publisher:
Nature Publishing Group (NPG)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Martin, S. B., Mosquera-Caro, M. P., Potter, J. W., Davidson, G. S., Andries, E., Kang, H., Helman, P., Veroff, R. L., Atlas, S. R., Murphy, M., Wang, X., Ar, K., Xu, Y., Chen, I.-M., Schultz, F. A., Wilson, C. S., Harvey, R., Bedrick, E., Shuster, J., Carroll, A. J., Camitta, B., and Willman, C. L. Gene expression overlap affects karyotype prediction in pediatric acute lymphoblastic leukemia. United States: N. p., 2007. Web. doi:10.1038/sj.leu.2404640.
Martin, S. B., Mosquera-Caro, M. P., Potter, J. W., Davidson, G. S., Andries, E., Kang, H., Helman, P., Veroff, R. L., Atlas, S. R., Murphy, M., Wang, X., Ar, K., Xu, Y., Chen, I.-M., Schultz, F. A., Wilson, C. S., Harvey, R., Bedrick, E., Shuster, J., Carroll, A. J., Camitta, B., & Willman, C. L. Gene expression overlap affects karyotype prediction in pediatric acute lymphoblastic leukemia. United States. https://doi.org/10.1038/sj.leu.2404640
Martin, S. B., Mosquera-Caro, M. P., Potter, J. W., Davidson, G. S., Andries, E., Kang, H., Helman, P., Veroff, R. L., Atlas, S. R., Murphy, M., Wang, X., Ar, K., Xu, Y., Chen, I.-M., Schultz, F. A., Wilson, C. S., Harvey, R., Bedrick, E., Shuster, J., Carroll, A. J., Camitta, B., and Willman, C. L. Thu . "Gene expression overlap affects karyotype prediction in pediatric acute lymphoblastic leukemia". United States. https://doi.org/10.1038/sj.leu.2404640. https://www.osti.gov/servlets/purl/1426985.
@article{osti_1426985,
title = {Gene expression overlap affects karyotype prediction in pediatric acute lymphoblastic leukemia},
author = {Martin, S. B. and Mosquera-Caro, M. P. and Potter, J. W. and Davidson, G. S. and Andries, E. and Kang, H. and Helman, P. and Veroff, R. L. and Atlas, S. R. and Murphy, M. and Wang, X. and Ar, K. and Xu, Y. and Chen, I.-M. and Schultz, F. A. and Wilson, C. S. and Harvey, R. and Bedrick, E. and Shuster, J. and Carroll, A. J. and Camitta, B. and Willman, C. L.},
abstractNote = {Leukemia is the most common childhood malignancy in the United States. Acute lymphoblastic leukemia (ALL) accounts for 75% of new leukemia cases in children. Although the outcome for children with ALL has improved dramatically over the past three decades, 25% of children with ALL still develop recurrent disease. Current risk classification schemes in pediatric ALL use clinical and laboratory parameters such as age and initial white blood cell count, as well as the presence of specific ALL-associated cytogenetic or molecular genetic abnormalities. Stratification based on cytogenetic analysis and molecular genetic detection consider B precursor ALL translocations such as t(12;21)(TEL-AML1), t(1;19)(E2A-PBX1) and t(9;22)(BCR-ABL), as well as numerical imbalances such as hyperdiploidy, specific chromosome trisomies or hypodiploidy. Despite such efforts, current diagnosis and risk classification schemes in pediatric ALL remain imprecise. In particular, it is likely that a significant number of higher-risk children are currently overtreated and could be cured with less intensive regimens, resulting in fewer toxicities and long-term side effects. Finally and conversely, a significant number of children in lower-risk categories still relapse and precise means to prospectively identify them have remained elusive.},
doi = {10.1038/sj.leu.2404640},
journal = {Leukemia},
number = 6,
volume = 21,
place = {United States},
year = {Thu Apr 05 00:00:00 EDT 2007},
month = {Thu Apr 05 00:00:00 EDT 2007}
}

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Works referenced in this record:

Classification of pediatric acute lymphoblastic leukemia by gene expression profiling
journal, October 2003


Acute Lymphoblastic Leukemia
journal, April 2004

  • Pui, Ching-Hon; Relling, Mary V.; Downing, James R.
  • New England Journal of Medicine, Vol. 350, Issue 15
  • DOI: 10.1056/NEJMra023001

A Bayesian Network Classification Methodology for Gene Expression Data
journal, August 2004

  • Helman, Paul; Veroff, Robert; Atlas, Susan R.
  • Journal of Computational Biology, Vol. 11, Issue 4
  • DOI: 10.1089/cmb.2004.11.581

Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling
journal, March 2002