4.7 Article

Gene utility recapitulates chromosomal aberrancies in advanced stage neuroblastoma

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出版社

ELSEVIER
DOI: 10.1016/j.csbj.2022.06.024

关键词

Neuroblastoma; Network simulation; Chromosomal abnormalities; Inferred karyotype

资金

  1. National Cancer Institute, United States [R01 CA240323]
  2. United States Department of Defense (DoD) , United States [W81XWH-17-1-0498]
  3. V Foundation for Cancer Research [D2018-005]
  4. National Cancer Institute, United States
  5. United States Department of Defense (DoD) , United States [R01 CA240323]
  6. V Foundation for Cancer Research, United States [W81XWH-17-1-0498]
  7. Mayo Clinic DERIVE Office and Mayo Center for Biomedical Discovery, United States [D2018-005]
  8. Mayo Clinic Cancer Center, Mayo Center for Biomedical Discovery and Center for Individualized Medicine, United States
  9. Glenn Foundation for Medical Research [R01 CA240323]
  10. David F. and Margaret T. Grohne Cancer Immunology and Immunotherapy Program, United States
  11. NIH, United States
  12. [P30CA015083]
  13. [R01AG056318]
  14. [P50CA136393]

向作者/读者索取更多资源

This article introduces the Gene Utility Model (GUM) to understand the impact of differentially utilized genes on neuroblastoma karyotype evolution. Through computational modeling and comparative analysis, genes with differential utilities in neuroblastoma were identified and mapped to a utility karyotype that recapitulates chromosomal abnormalities and provides clues to predisposition sites. This study offers new insights into the etiology of neuroblastoma and facilitates the identification of novel therapeutic targets.
Neuroblastoma (NB) is the most common extracranial solid tumor in children. Although only a few recurrent somatic mutations have been identified, chromosomal abnormalities, including the loss of heterozygosity (LOH) at the chromosome 1p and gains of chromosome 17q, are often seen in the high-risk cases. The biological basis and evolutionary forces that drive such genetic abnormalities remain enigmatic. Here, we conceptualize the Gene Utility Model (GUM) that seeks to identify genes driving biological signaling via their collective gene utilities and apply it to understand the impact of those differentially utilized genes on constraining the evolution of NB karyotypes. By employing a computational processguided flow algorithm to model gene utility in protein-protein networks that built based on transcriptomic data, we conducted several pairwise comparative analyses to uncover genes with differential utilities in stage 4 NBs with distinct classification. We then constructed a utility karyotype by mapping these differentially utilized genes to their respective chromosomal loci. Intriguingly, hotspots of the utility karyotype, to certain extent, can consistently recapitulate the major chromosomal abnormalities of NBs and also provides clues to yet identified predisposition sites. Hence, our study not only provides a new look, from a gene utility perspective, into the known chromosomal abnormalities detected by integrative genomic sequencing efforts, but also offers new insights into the etiology of NB and provides a framework to facilitate the identification of novel therapeutic targets for this devastating childhood cancer.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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