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Article Abstract

Background: A major roadblock to reducing the mortality of colorectal cancer (CRC) is prompt detection and treatment, and a simple blood test is likely to have higher compliance than all of the current methods. The purpose of this report is to examine the utility of a mass spectrometry-based blood serum protein biomarker test for detection of CRC.

Materials And Methods: Blood was drawn from individuals (n = 213) before colonoscopy or from patients with nonmetastatic CRC (n = 50) before surgery. Proteins were isolated from the serum of patients using targeted liquid chromatography-tandem mass spectrometry. We designed a machine-learning statistical model to assess these proteins.

Results: When considered individually, over 70% of the selected biomarkers showed significance by Mann-Whitney testing for distinguishing cancer-bearing cases from cancer-free cases. Using machine-learning methods, peptides derived from epidermal growth factor receptor and leucine-rich alpha-2-glycoprotein 1 were consistently identified as highly predictive for detecting CRC from cancer-free cases. A five-marker panel consisting of leucine-rich alpha-2-glycoprotein 1, epidermal growth factor receptor, inter-alpha-trypsin inhibitor heavy-chain family member 4, hemopexin, and superoxide dismutase 3 performed the best with 70% specificity at over 89% sensitivity (area under the curve = 0.86) in the validation set. For distinguishing regional from localized cancers, cross-validation within the training set showed that a panel of four proteins consisting of CD44 molecule, GC-vitamin D-binding protein, C-reactive protein, and inter-alpha-trypsin inhibitor heavy-chain family member 3 yielded the highest performance (area under the curve = 0.75).

Conclusions: The minimally invasive blood biomarker panels identified here could serve as screening/detection alternatives for CRC in a human population and potentially useful for staging of existing cancer.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6957232PMC
http://dx.doi.org/10.1016/j.jss.2019.08.004DOI Listing

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