Poster Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel (#730)

Abidali Mohamedali 1 , Seong Beom Ahn 2 , Samridhi Sharma 2 , Sadia Mahboob 2 , William J Redmond 2 , Dana Pascovic 3 , Jemma X Wu 3 , Thiri Zaw 3 , Subash Adhikari 2 , Vineet Viabhav 2 , Ed C Nice 4 , Mark S. S Baker 5
  1. Molecular Sciences, Faculty Of Science and Engineering, Macquarie University, Sydney
  2. Biological Sciences, Faculty of Medicine and Health Sciences , Macquarie University, Sydney
  3. Australian Proteome Analysis Facility, Macquarie University, Sydney
  4. Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC
  5. Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia

Background: One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high - as most patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood (FOBT) have low compliance (~40%), and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (>97%), if they can at least match the sensitivity and specificity of FOBTs. However, the discovery of low abundance plasma biomarkers is difficult due to high abundance plasma proteins.

 Methods: A combination of ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasmas (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p<0.05; fold-change>1.5), and further examined with a neural network classification method using in silico augmented 5,000 patient datasets.

 Results: Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, seven candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that maintained accuracy that could discern early (I/II) from late (III/IV) stage CRC.