Next generation sequencing identifies ‘interactome’ signatures in relapsed and refractory metastatic colorectal cancer
AffiliationUniv Arizona, Ctr Canc
KeywordsMetastatic colorectal cancer (mCRC)
next generation sequencing (NGS)
MetadataShow full item record
PublisherPIONEER BIOSCIENCE PUBL CO
CitationNext generation sequencing identifies ‘interactome’ signatures in relapsed and refractory metastatic colorectal cancer 2017, 8 (1):20-31 Journal of Gastrointestinal Oncology
Rights© Journal of Gastrointestinal Oncology. All rights reserved.
Collection InformationThis 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 firstname.lastname@example.org.
AbstractBackground: 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.
NoteOpen Access Journal.
VersionFinal published version
SponsorsThe West Cancer Center; University of Tennessee Health Science Center (UTHSC); UTHSC research grant
CollectionsUA Faculty Publications
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