RNA-seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential
Joint Authors
Gu, Jian-lei
Chukhman, Morris
Lu, Yao
Liu, Cong
Liu, Shi-yi
Lu, Hui
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-17
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Gu, Jian-lei& Chukhman, Morris& Lu, Yao& Liu, Cong& Liu, Shi-yi& Lu, Hui. 2017. RNA-seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential. BioMed Research International،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1139731
Modern Language Association (MLA)
Gu, Jian-lei…[et al.]. RNA-seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential. BioMed Research International No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1139731
American Medical Association (AMA)
Gu, Jian-lei& Chukhman, Morris& Lu, Yao& Liu, Cong& Liu, Shi-yi& Lu, Hui. RNA-seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1139731
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139731