Childhood acute lymphoblastic leukemia in the age of genomics.
The recent sequencing of the human genome and technical breakthroughs now make it possible to simultaneously determine mRNA expression levels of almost all of the identified genes in the human genome. DNA "chip" or microarray technology holds great promise for the development of more refined, biologically-based classification systems for childhood ALL, as well as the identification of new targets for novel therapy. To date gene expression profiles have been described that correlate with subtypes of ALL defined by morphology, immunophenotype, cytogenetic alterations, and response to therapy. Mechanistic insights into treatment failure have come from the definition of mRNA signatures that predict in vitro chemoresistance, as well as differences between blasts at relapse and new diagnosis. New bioinformatics tools optimize data mining, but validation of findings is essential since "over-fitting" the data is a common danger. In the future, genomic analysis will be complemented by evaluation of the cancer proteome.
Carroll
William L
WL
Division of Pediatric Hematology/Oncology, New York University Cancer Institute, New York University School of Medicine, New York City, New York, USA. william.carroll@nyumc.org
Bhojwani
Deepa
D
Min
Dong-Joon
DJ
Moskowitz
Naomi
N
Raetz
Elizabeth A
EA
D002648:Child; D019295:Computational Biology; D020869:Gene Expression Profiling; D015973:Gene Expression Regulation, Leukemic; D023281:Genomics; D006801:Humans; D046228:Microarray Analysis; D009363:Neoplasm Proteins / Q000235:genetics / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D015398:Signal Transduction
D009363:Neoplasm Proteins