Metabolomic biomarkers of pancreatic cancer: a meta-analysis study
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Khyati Y. Mehta1,*, Hung-Jen Wu7,*, Smrithi S. Menon1, Yassi Fallah1, Xiaogang Zhong2, Nasser Rizk3, Keith Unger4, Mark Mapstone5, Massimo S. Fiandaca5,6, Howard J. Federoff5 and Amrita K. Cheema1,7
1Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
2Department of Biostatistics Bioinformatics and Biomathematics, Georgetown University, Washington, DC, United States of America
3Department of Health Sciences, Qatar University, Doha, Qatar
4Lombardi Comprehensive Cancer Center, Med-Star Georgetown University Hospital, Washington, DC, United States of America
5Department of Neurology, University of California, Irvine, CA, United States of America
6Department of Neurological Surgery, University of California, Irvine, CA, United States of America
7Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC, United States of America
*These authors contributed equally to this work
Amrita K. Cheema, email: [email protected]
Keywords: pancreatic cancer, biomarkers, metabolomics
Received: April 19, 2017 Accepted: August 04, 2017 Published: August 18, 2017
Pancreatic cancer (PC) is an aggressive disease with high mortality rates, however, there is no blood test for early detection and diagnosis of this disease. Several research groups have reported on metabolomics based clinical investigations to identify biomarkers of PC, however there is a lack of a centralized metabolite biomarker repository that can be used for meta-analysis and biomarker validation. Furthermore, since the incidence of PC is associated with metabolic syndrome and Type 2 diabetes mellitus (T2DM), there is a need to uncouple these common metabolic dysregulations that may otherwise diminish the clinical utility of metabolomic biosignatures. Here, we attempted to externally replicate proposed metabolite biomarkers of PC reported by several other groups in an independent group of PC subjects. Our study design included a T2DM cohort that was used as a non-cancer control and a separate cohort diagnosed with colorectal cancer (CRC), as a cancer disease control to eliminate possible generic biomarkers of cancer. We used targeted mass spectrometry for quantitation of literature-curated metabolite markers and identified a biomarker panel that discriminates between normal controls (NC) and PC patients with high accuracy. Further evaluation of our model with CRC, however, showed a drop in specificity for the PC biomarker panel. Taken together, our study underscores the need for a more robust study design for cancer biomarker studies so as to maximize the translational value and clinical implementation.
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