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    Next generation sequencing identifies ‘interactome’ signatures in relapsed and refractory metastatic colorectal cancer

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    9460-PB7-R3.pdf
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    Author
    Johnson, Benny
    Cooke, Laurence
    Mahadevan, Daruka
    Affiliation
    Univ Arizona, Ctr Canc
    Issue Date
    2017-02
    Keywords
    Metastatic colorectal cancer (mCRC)
    RAS
    BRAF
    next generation sequencing (NGS)
    mutational signatures
    interactome
    
    Metadata
    Show full item record
    Publisher
    PIONEER BIOSCIENCE PUBL CO
    Citation
    Next generation sequencing identifies ‘interactome’ signatures in relapsed and refractory metastatic colorectal cancer 2017, 8 (1):20-31 Journal of Gastrointestinal Oncology
    Journal
    Journal of Gastrointestinal Oncology
    Rights
    © Journal of Gastrointestinal Oncology. All rights reserved.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Background: In the management of metastatic colorectal cancer (mCRC), KRAS, NRAS and BRAF mutational status individualizes therapeutic options and identify a cohort of patients (pts) with an aggressive clinical course. We hypothesized that relapsed and refractory mCRC pts develop unique mutational signatures that may guide therapy, predict for a response and highlight key signaling pathways important for clinical decision making. Methods: Relapsed and refractory mCRC pts (N=32) were molecularly profiled utilizing commercially available next generation sequencing (NGS) platforms. Web-based bioinformatics tools (Reactome/Enrichr) were utilized to elucidate mutational profile linked pathways-networks that have the potential to guide therapy. Results: Pts had progressed on fluoropyrimidines, oxaliplatin, irinotecan, bevacizumab, cetuximab and/or panitumumab. Most common histology was adenocarcinoma (colon N=29; rectal N=3). Of the mutations TP53 was the most common, followed by APC, KRAS, PIK3CA, BRAF, SMAD4, SPTA1, FAT1, PDGFRA, ATM, ROS1, ALK, CDKN2A, FBXW7, TGFBR2, NOTCH1 and HER3. Pts had on average had >= 5 unique mutations. The most frequent activated signaling pathways were: HER2, fibroblast growth factor receptor (FGFR), p38 through BRAF-MEK cascade via RIT and RIN, ARMS-mediated activation of MAPK cascade, and VEGFR2. Conclusions: Dominant driver oncogene mutations do not always equate to oncogenic dependence, hence understanding pathogenic ` interactome(s)' in individual pts is key to both clinically relevant targets and in choosing the next best therapy. Mutational signatures derived from corresponding ` pathway-networks' represent a meaningful tool to (I) evaluate functional investigation in the laboratory; (II) predict response to drug therapy; and (III) guide rational drug combinations in relapsed and refractory mCRC pts.
    Note
    Open Access Journal.
    ISSN
    20786891
    2219679X
    PubMed ID
    28280605
    DOI
    10.21037/jgo.2016.09.05
    Version
    Final published version
    Sponsors
    The West Cancer Center; University of Tennessee Health Science Center (UTHSC); UTHSC research grant
    Additional Links
    http://jgo.amegroups.com/article/view/9460/10127
    ae974a485f413a2113503eed53cd6c53
    10.21037/jgo.2016.09.05
    Scopus Count
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