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Retrospective Analysis of INRG Clinical and Genomic Factors for 605 Neuroblastomas in Japan: A Report from the Japan Children's Cancer Group Neuroblastoma Committee (JCCG-JNBSG).

Miki OhiraYohko NakamuraTetsuya TakimotoAtsuko NakazawaTomoro HishikiKimikazu MatsumotoHiroyuki ShichinoTomoko IeharaHiroki NagaseTakashi FukushimaAkihiro YonedaTatsuro TajiriAkira NakagawaraTakehiko Kamijo
Published in: Biomolecules (2021)
Neuroblastomas (NBs) exhibit broad and divergent clinical behaviors and tumor risk classification at diagnosis is crucial for the selection of an appropriate therapeutic strategy for each patient. The present study aimed to validate the clinical relevance of International Neuroblastoma Risk Group (INRG) prognostic and genomic markers in a Japanese NB cohort using a retrospective analysis. Follow-up data based on 30 common INRG queries in 605 NB cases diagnosed in Japan between 1990 and 2014 were collected and the genome signature of each tumor sample was integrated. As previously indicated, age, tumor stage, MYCN , DNA ploidy, the adrenals as the primary tumor site, serum ferritin and lactate dehydrogenase (LDH) levels, segmental chromosome aberrations, and the number of chromosome breakpoints (BP) correlated with lower survival rates, while the thorax as the primary tumor site and numerical chromosome aberrations correlated with a favorable prognosis. In the patient group with stage 4, MYCN non-amplified tumors (n = 225), one of the challenging subsets for risk stratification, age ≥ 18 months, LDH ≥ 1400 U/L, and BP ≥ 7 correlated with lower overall and event-free survival rates ( p < 0.05). The genome subgroup GG-P2s (partial chromosome gain/loss type with 1p/11q losses and 17q gain, n = 30) was strongly associated with a lower overall survival rate (5-year survival rate: 34%, p < 0.05). Therefore, the combination of the tumor genomic pattern (GG-P2s and BP ≥ 7) with age at diagnosis and LDH will be a promising predictor for MYCN -non-amplified high-risk NBs in patient subsets, in accordance with previous findings from the INRG project.
Keyphrases
  • copy number
  • free survival
  • case report
  • gene expression
  • young adults
  • squamous cell carcinoma
  • machine learning
  • quality improvement
  • deep learning
  • big data