Heterogeneous subgroups in human neuroblastoma for clinically relevant risk stratification

Hiyama, Eiso; Yamaoka, Hiroaki; Kondo, Satoshi; Yoneda, Akihiro; Tajiri, Tatsuro; Fukuzawa, Masahiro; Sugiyama, Masahiko; Hayashi, Yutaka; Sasaki, Fumiaki; Ohtaki, Megu
November 2007
Pediatric Surgery International;Nov2007, Vol. 23 Issue 11, p1051
Academic Journal
journal article
Neuroblastoma is a heterogeneous tumor and that may have a favorable or unfavorable prognosis. In Japan, a nation-wide neuroblastoma mass-screening (MS) project assessed 6-month-old infants between 1985 and 2003, and almost all neuroblastomas, including regressing or maturing tumors were thought to be detected in this period. To evaluate the heterogeneity of neuroblastoma subgroups, we analyzed patients with neuroblastoma who had been diagnosed during this period. The clinical courses of 4,209 patients with neuroblastoma, including 1,560 MS detected patients, whose tumors had been diagnosed between 1971 and 1995 were registered. The 2,520 cases registered between 1985 and 1995 were compared to 1,050 cases registered between 1971 and 1980 and analyzed by a multi-gene target model to determine the age distribution of neuroblastoma incidence. We hypothesized that three target genes were responsible for the progression of neuroblastoma: one pair of tumor suppressor gene alleles, one oncogene, and one gene controlling regression/differentiation. This simulation study revealed that the age distribution at initial diagnosis of neuroblastoma was divided into four groups based on post-fertilization age: 20-40, 40-50, 60-90, and 160-200 weeks. Since neuroblatoma in the first group occurred prenatal, post-natal clinical neuroblastoma can be classified into three age groups: 0-6 months, 1-2 years, and 3-4 years. The 0- to 6-month group consisted of mostly benign tumors, and the two older groups had predominantly malignant phenotypes. Our proposed model could explain qualitatively the distribution of neuroblastoma consisting of one subgroup with a favorable prognosis and two subgroups with unfavorable prognosis. For clinically relevant risk stratification, an age cutoff should be considered by the age distribution of these heterogeneous subgroups.


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