Development of personalized medicine and therapeutic strategies for pediatric solid tumors

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We have aimed to establish new diagnostic systems to predict prognosis of neuroblastoma and hepatoblastoma, which are typical childhood solid tumors, by using comprehensive methodology including genomics and proteomics. The childhood cancers-proper cDNA libraries we generated previously and the BAC clones-based array-CGH methods were introduced. We could successfully generate a practically usable mini-chip carrying top ranked 200 genes to predict the prognosis of neuroblastoma. In addition, our array-CGH analysis made it possible to generate a genome-based risk classification of neuroblastoma which is now applicable to the clinical study. The novel serum prognostic factors have also been identified. Furthermore, we found new neuroblastoma genes including KIF1Bbeta, RUNX3 and ALK which is often amplified and mutated in primary neuroblastomas.