Gene expression signatures predictive of early response and outcome in high-risk childhood acute lymphoblastic leukemia: A Children's Oncology Group Study [corrected].
OBJECTIVE
To identify children with acute lymphoblastic leukemia (ALL) at initial diagnosis who are at risk for inferior response to therapy by using molecular signatures.


METHODS
Gene expression profiles were generated from bone marrow blasts at initial diagnosis from a cohort of 99 children with National Cancer Institute-defined high-risk ALL who were treated uniformly on the Children's Oncology Group (COG) 1961 study. For prediction of early response, genes that correlated to marrow status on day 7 were identified on a training set and were validated on a test set. An additional signature was correlated with long-term outcome, and the predictive models were validated on three large, independent patient cohorts. Results We identified a 24-probe set signature that was highly predictive of day 7 marrow status on the test set (P = .0061). Pathways were identified that may play a role in early blast regression. We have also identified a 47-probe set signature (which represents 41 unique genes) that was predictive of long-term outcome in our data set as well as three large independent data sets of patients with childhood ALL who were treated on different protocols. However, we did not find sufficient evidence for the added significance of these genes and the derived predictive models when other known prognostic features, such as age, WBC, and karyotype, were included in a multivariate analysis.


CONCLUSIONS
Genes and pathways that play a role in early blast regression may identify patients who may be at risk for inferior responses to treatment. A fully validated predictive gene expression signature was defined for high-risk ALL that provided insight into the biologic mechanisms of treatment failure.
Bhojwani
Deepa
D
Division of Pediatric Hematology/Oncology, New York University Cancer Institute, New York University School of Medicine, New York, NY 10016, USA.
Kang
Huining
H
Menezes
Renee X
RX
Yang
Wenjian
W
Sather
Harland
H
Moskowitz
Naomi P
NP
Min
Dong-Joon
DJ
Potter
Jeffrey W
JW
Harvey
Richard
R
Hunger
Stephen P
SP
Seibel
Nita
N
Raetz
Elizabeth A
EA
Pieters
Rob
R
Horstmann
Martin A
MA
Relling
Mary V
MV
den Boer
Monique L
ML
Willman
Cheryl L
CL
Carroll
William L
WL
D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics; D005819:Genetic Markers; D006801:Humans; D007223:Infant; D008297:Male; D015233:Models, Statistical; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000175:diagnosis* / Q000235:genetics* / Q000628:therapy; D011237:Predictive Value of Tests; D012372:ROC Curve; D018570:Risk Assessment; D016896:Treatment Outcome
D005819:Genetic Markers
Nature. 2000 Feb 3;403(6769):503-11
10676951
Nat Genet. 2000 May;25(1):25-9
10802651
Blood. 2008 Mar 1;111(5):2548-55
18039957
Cancer Res. 2000 Sep 15;60(18):5092-6
11016634
Proc Natl Acad Sci U S A. 2002 May 14;99(10):6567-72
12011421
Leukemia. 2002 Jun;16(6):1099-111
12040440
Cancer Cell. 2002 Mar;1(2):133-43
12086872
Leukemia. 2003 Aug;17(8):1566-72
12886244
N Engl J Med. 2004 Aug 5;351(6):533-42
15295046
N Engl J Med. 1998 Jun 4;338(23):1663-71
9614257
Science. 1999 Oct 15;286(5439):531-7
10521349
J Comput Biol. 2004;11(4):581-615
15579233
Cancer Cell. 2005 Apr;7(4):375-86
15837626
Genome Biol. 2005;6(9):R81
16168088
Br J Haematol. 2005 Dec;131(5):579-87
16351633
N Engl J Med. 2006 Jan 12;354(2):166-78
16407512
Leukemia. 2006 Aug;20(8):1385-92
16761018
Blood. 2006 Aug 1;108(3):1050-7
16627760
N Engl J Med. 2006 Aug 10;355(6):560-9
16899776
Blood. 2006 Sep 15;108(6):1984-90
16709928
J Clin Oncol. 2006 Nov 1;24(31):5079-90
17075127
Blood. 2007 Feb 1;109(3):926-35
17003380
Leukemia. 2007 Jun;21(6):1341-4
17410195
Blood. 2007 Aug 15;110(4):1271-7
17456722