Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma.
Currently, patients with neuroblastoma are classified into risk groups (e.g., according to the Children's Oncology Group risk-stratification) to guide physicians in the choice of the most appropriate therapy. Despite this careful stratification, the survival rate for patients with high-risk neuroblastoma remains <30%, and it is not possible to predict which of these high-risk patients will survive or succumb to the disease. Therefore, we have performed gene expression profiling using cDNA microarrays containing 42,578 clones and used artificial neural networks to develop an accurate predictor of survival for each individual patient with neuroblastoma. Using principal component analysis we found that neuroblastoma tumors exhibited inherent prognostic specific gene expression profiles. Subsequent artificial neural network-based prognosis prediction using expression levels of all 37,920 good-quality clones achieved 88% accuracy. Moreover, using an artificial neural network-based gene minimization strategy in a separate analysis we identified 19 genes, including 2 prognostic markers reported previously, MYCN and CD44, which correctly predicted outcome for 98% of these patients. In addition, these 19 predictor genes were able to additionally partition Children's Oncology Group-stratified high-risk patients into two subgroups according to their survival status (P = 0.0005). Our findings provide evidence of a gene expression signature that can predict prognosis independent of currently known risk factors and could assist physicians in the individual management of patients with high-risk neuroblastoma.
Advanced Technology Center, Oncogenomics Section, Pediatric Oncology Branch, National Cancer Institute, NIH, Gaithersburg, Maryland 20877, USA.
Jun S
JS
Wei
Braden T
BT
Greer
Frank
F
Westermann
Seth M
SM
Steinberg
Chang-Gue
CG
Son
Qing-Rong
QR
Chen
Craig C
CC
Whiteford
Sven
S
Bilke
Alexei L
AL
Krasnoselsky
Nicola
N
Cenacchi
Daniel
D
Catchpoole
Frank
F
Berthold
Manfred
M
Schwab
Javed
J
Khan
D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D002648:Child; D002675:Child, Preschool; D003131:Combined Modality Therapy; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D007223:Infant; D016571:Neural Networks, Computer; D009447:Neuroblastoma / Q000188:drug therapy / Q000235:genetics* / Q000378:metabolism / Q000601:surgery; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D011379:Prognosis; D012189:Retrospective Studies; D012307:Risk Factors; D016019:Survival Analysis; D016896:Treatment Outcome