RNA-seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential.

Based on high-throughput sequencing technology, the detection of gene fusions is no longer a big challenge but estimating the oncogenic potential of fusion genes remains challenging. Recent studies successfully applied machine learning methods and gene structural and functional features of fusion mu...

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Publicado en:BioMed Research International Vol. 2017; pp. 1 - 9
Autores principales: Gu, Jian-lei, Chukhman, Morris, Lu, Yao, Liu, Cong, Liu, Shi-yi, Lu, Hui
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 10/17/2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 10/17/2017
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2017/9829175
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        atl: RNA-seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential.
      aug:
        au:
          Gu, Jian-lei
          Chukhman, Morris
          Lu, Yao
          Liu, Cong
          Liu, Shi-yi
          Lu, Hui
        affil: Shanghai Institute of Medical Genetics, Shanghai Children’s Hospital, Shanghai Jiao Tong University, Shanghai 200040, China
      sug:
        subj:
          RNA
          Sequence Analysis
          Genetic Techniques
          Human
          Prostatic Neoplasms Prevention and Control
          Bioinformatics
      ab: Based on high-throughput sequencing technology, the detection of gene fusions is no longer a big challenge but estimating the oncogenic potential of fusion genes remains challenging. Recent studies successfully applied machine learning methods and gene structural and functional features of fusion mutation to predict their oncogenic potentials. However, the transcription characterizations features of fusion genes have not yet been studied. In this study, based on the clonal evolution theory, we hypothesized that a fusion gene is more likely to be an oncogenic genomic alteration, if the neoplastic cells harboring this fusion mutation have larger clonal size than other neoplastic cells in a tumor. We proposed a novel method, called iFCR (internal Fusion Clone Ratio), given an estimation of oncogenic potential for fusion mutations. We have evaluated the iFCR method in three public cancer transcriptome sequencing datasets; the results demonstrated that the fusion mutations occurring in tumor samples have higher internal fusion clone ratio than normal samples. And the most frequent prostate cancer fusion mutation, TMPRSS2-ERG, appears to have a remarkably higher iFCR value in all three independent patients. The preliminary results suggest that the internal fusion clone ratio might potentially advantage current fusion mutation oncogenic potential prediction methods.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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