PMID- 20459861
OWN - NLM
STAT- MEDLINE
DCOM- 20100730
LR  - 20211020
IS  - 1476-4598 (Electronic)
IS  - 1476-4598 (Linking)
VI  - 9
DP  - 2010 May 12
TI  - Gene-based outcome prediction in multiple cohorts of pediatric T-cell acute 
      lymphoblastic leukemia: a Children's Oncology Group study.
PG  - 105
LID - 10.1186/1476-4598-9-105 [doi]
AB  - BACKGROUND: Continuous complete clinical remission in T-cell acute lymphoblastic 
      leukemia (T-ALL) is now approaching 80% due to the implementation of aggressive 
      chemotherapy protocols but patients that relapse continue to have a poor 
      prognosis. Such patients could benefit from augmented therapy if their clinical 
      outcome could be more accurately predicted at the time of diagnosis. Gene 
      expression profiling offers the potential to identify additional prognostic 
      markers but has had limited success in generating robust signatures that predict 
      outcome across multiple patient cohorts. This study aimed to identify robust gene 
      classifiers that could be used for the accurate prediction of relapse in 
      independent cohorts and across different experimental platforms. RESULTS: Using 
      HG-U133Plus2 microarrays we modeled a five-gene classifier (5-GC) that accurately 
      predicted clinical outcome in a cohort of 50 T-ALL patients. The 5-GC was further 
      tested against three independent cohorts of T-ALL patients, using either qRT-PCR 
      or microarray gene expression, and could predict patients with significantly 
      adverse clinical outcome in each. The 5-GC featured the interleukin-7 receptor 
      (IL-7R), low-expression of which was independently predictive of relapse in T-ALL 
      patients. In T-ALL cell lines, low IL-7R expression was correlated with 
      diminished growth response to IL-7 and enhanced glucocorticoid resistance. 
      Analysis of biological pathways identified the NF-kappaB and Wnt pathways, and 
      the cell adhesion receptor family (particularly integrins) as being predictive of 
      relapse. Outcome modeling using genes from these pathways identified patients 
      with significantly worse relapse-free survival in each T-ALL cohort. CONCLUSIONS: 
      We have used two different approaches to identify, for the first time, robust 
      gene signatures that can successfully discriminate relapse and CCR patients at 
      the time of diagnosis across multiple patient cohorts and platforms. Such genes 
      and pathways represent markers for improved patient risk stratification and 
      potential targets for novel T-ALL therapies.
FAU - Cleaver, Amanda L
AU  - Cleaver AL
AD  - Division of Children's Leukaemia and Cancer Research, Telethon Institute for 
      Child Health Research, Perth, Australia.
FAU - Beesley, Alex H
AU  - Beesley AH
FAU - Firth, Martin J
AU  - Firth MJ
FAU - Sturges, Nina C
AU  - Sturges NC
FAU - O'Leary, Rebecca A
AU  - O'Leary RA
FAU - Hunger, Stephen P
AU  - Hunger SP
FAU - Baker, David L
AU  - Baker DL
FAU - Kees, Ursula R
AU  - Kees UR
LA  - eng
GR  - CA114766/CA/NCI NIH HHS/United States
GR  - CA95475/CA/NCI NIH HHS/United States
GR  - CA98543/CA/NCI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20100512
PL  - England
TA  - Mol Cancer
JT  - Molecular cancer
JID - 101147698
RN  - 0 (Biomarkers, Tumor)
RN  - 0 (NF-kappa B)
RN  - 0 (Receptors, Interleukin-7)
RN  - 0 (Wnt Proteins)
SB  - IM
MH  - Adolescent
MH  - Algorithms
MH  - Biomarkers, Tumor/analysis/*genetics
MH  - Child
MH  - Child, Preschool
MH  - Decision Trees
MH  - Female
MH  - Gene Expression
MH  - Gene Expression Profiling/*methods
MH  - Humans
MH  - Kaplan-Meier Estimate
MH  - Male
MH  - NF-kappa B/genetics
MH  - Oligonucleotide Array Sequence Analysis
MH  - Precursor T-Cell Lymphoblastic Leukemia-Lymphoma/*genetics/mortality
MH  - Prognosis
MH  - Receptors, Interleukin-7/genetics
MH  - Reverse Transcriptase Polymerase Chain Reaction
MH  - Treatment Outcome
MH  - Wnt Proteins/genetics
PMC - PMC2879253
EDAT- 2010/05/13 06:00
MHDA- 2010/07/31 06:00
PMCR- 2010/05/12
CRDT- 2010/05/13 06:00
PHST- 2009/12/04 00:00 [received]
PHST- 2010/05/12 00:00 [accepted]
PHST- 2010/05/13 06:00 [entrez]
PHST- 2010/05/13 06:00 [pubmed]
PHST- 2010/07/31 06:00 [medline]
PHST- 2010/05/12 00:00 [pmc-release]
AID - 1476-4598-9-105 [pii]
AID - 10.1186/1476-4598-9-105 [doi]
PST - epublish
SO  - Mol Cancer. 2010 May 12;9:105. doi: 10.1186/1476-4598-9-105.