Neuroblastomas are cancers of neural crest origin with variable prognoses depending on age at presentation, stage, histology, presence of MYCN amplification, chromosomal ploidy, and deletion status of 1p36. Very little is known of the molecular mechanisms that confer good or poor prognosis in this and other malignancies. We have recently demonstrated that cancers can be diagnosed on the basis of gene expression profiling using cDNA microarrays and sophisticated pattern recognition algorithms such as Artificial Neural Networks. The Oncogenomics Section has expanded this concept further by profiling a series on neuroblastomas of different stages and prognosis. With these methods we are identifying tumor-specific expression patterns, or fingerprints, that uniquely identify a poor prognostic group, as well as those associated with specific genetic aberrations including MYCN amplification. By these techniques, we hope to classify expression profiles that correlate with prognosis and hence identified the genes that confer these biological properties. Once we have narrowed down the list of genes that defines a particular cancer or diagnostic or prognostic group cluster to a minimum number, we will use this to make smaller microarrays or other multiplex PCR-based assays for diagnostic purposes in the clinic. Isotope-coded affinity tags (ICAT), allows the quantitative measurement of protein expression levels in different cell types and tissues. In this method proteins from two samples can be compared by chemically labeling both samples with the light and heavy isotopic forms of a reagent respectively. With this method we plan to sequence and identify up to 3000-4000 differentially expressed proteins between tumors with poor (death) and good (event free survival > 3yrs) outcome. These proteins represent potential targets for therapy, diagnostic and prognostic markers for high-risk patients as well as provide important clues on the biology of these tumors that fail to respond to conventional therapy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Intramural Research (Z01)
Project #
1Z01SC010366-07
Application #
7594820
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
7
Fiscal Year
2007
Total Cost
$459,160
Indirect Cost
Name
National Cancer Institute Division of Clinical Sciences
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Ambros, P F; Ambros, I M; Brodeur, G M et al. (2009) International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee. Br J Cancer 100:1471-82
Wei, Jun S; Johansson, Peter; Chen, Qing-Rong et al. (2009) microRNA profiling identifies cancer-specific and prognostic signatures in pediatric malignancies. Clin Cancer Res 15:5560-8
Westermann, Frank; Henrich, Kai-Oliver; Wei, Jun S et al. (2007) High Skp2 expression characterizes high-risk neuroblastomas independent of MYCN status. Clin Cancer Res 13:4695-703
Catchpoole, Daniel; Lail, Andy; Guo, Dachuan et al. (2007) Gene expression profiles that segregate patients with childhood acute lymphoblastic leukaemia: an independent validation study identifies that endoglin associates with patient outcome. Leuk Res 31:1741-7
Chen, Qing-Rong; Bilke, Sven; Wei, Jun S et al. (2006) Increased WSB1 copy number correlates with its over-expression which associates with increased survival in neuroblastoma. Genes Chromosomes Cancer 45:856-62
Henrich, Kai-Oliver; Fischer, Matthias; Mertens, Daniel et al. (2006) Reduced expression of CAMTA1 correlates with adverse outcome in neuroblastoma patients. Clin Cancer Res 12:131-8
Krasnoselsky, Alexei L; Whiteford, Craig C; Wei, Jun S et al. (2005) Altered expression of cell cycle genes distinguishes aggressive neuroblastoma. Oncogene 24:1533-41
Wei, Jun S; Greer, Braden T; Westermann, Frank et al. (2004) Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma. Cancer Res 64:6883-91
Yu, Yanlin; Khan, Javed; Khanna, Chand et al. (2004) Expression profiling identifies the cytoskeletal organizer ezrin and the developmental homeoprotein Six-1 as key metastatic regulators. Nat Med 10:175-81
Williams, Richard D; Hing, Sandra N; Greer, Braden T et al. (2004) Prognostic classification of relapsing favorable histology Wilms tumor using cDNA microarray expression profiling and support vector machines. Genes Chromosomes Cancer 41:65-79

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