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 neuroblastoma 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. We are now applying next generation sequencing strategies to comprehensively interrogate the cancer genome. By these techniques, we hope to classify genomic profiles that correlate with prognosis and hence identify 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 translate our findings to the patient for example develop 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 and other proteomic 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.

National Institute of Health (NIH)
National Cancer Institute (NCI)
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National Cancer Institute Division of Clinical Sciences
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Tenente, InĂªs M; Hayes, Madeline N; Ignatius, Myron S et al. (2017) Myogenic regulatory transcription factors regulate growth in rhabdomyosarcoma. Elife 6:
Ignatius, Myron S; Hayes, Madeline N; Lobbardi, Riadh et al. (2017) The NOTCH1/SNAIL1/MEF2C Pathway Regulates Growth and Self-Renewal in Embryonal Rhabdomyosarcoma. Cell Rep 19:2304-2318
Pugh, Trevor J; Morozova, Olena; Attiyeh, Edward F et al. (2013) The genetic landscape of high-risk neuroblastoma. Nat Genet 45:279-84
Wan, Xiaolin; Yeung, Choh; Kim, Su Young et al. (2012) Identification of FoxM1/Bub1b signaling pathway as a required component for growth and survival of rhabdomyosarcoma. Cancer Res 72:5889-99
Stauffer, Jimmy K; Orentas, Rimas J; Lincoln, Erin et al. (2012) High-throughput molecular and histopathologic profiling of tumor tissue in a novel transplantable model of murine neuroblastoma: new tools for pediatric drug discovery. Cancer Invest 30:343-63
Schleiermacher, G; Mosseri, V; London, W B et al. (2012) Segmental chromosomal alterations have prognostic impact in neuroblastoma: a report from the INRG project. Br J Cancer 107:1418-22
Chen, Qing-Rong; Yu, Li-Rong; Tsang, Patricia et al. (2011) Systematic proteome analysis identifies transcription factor YY1 as a direct target of miR-34a. J Proteome Res 10:479-87
Meadors, Joanna L; Cui, Yonghzi; Chen, Qing-Rong et al. (2011) Murine rhabdomyosarcoma is immunogenic and responsive to T-cell-based immunotherapy. Pediatr Blood Cancer 57:921-9
Liu, Z; Yang, X; Li, Z et al. (2011) CASZ1, a candidate tumor-suppressor gene, suppresses neuroblastoma tumor growth through reprogramming gene expression. Cell Death Differ 18:1174-83
Gonzalez-Bosquet, Jesus; Calcei, Jacob; Wei, Jun S et al. (2011) Detection of somatic mutations by high-resolution DNA melting (HRM) analysis in multiple cancers. PLoS One 6:e14522

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