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Abstract
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 the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (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, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). Methods: A combination of high abundance protein 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 plasma samples (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 5000 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, 7 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 had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. Conclusion: MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.
Original language | English |
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Article number | 34 |
Pages (from-to) | 1-20 |
Number of pages | 20 |
Journal | Clinical Proteomics |
Volume | 16 |
Issue number | 1 |
DOIs | |
Publication status | Published - 28 Aug 2019 |
Bibliographical note
Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Colorectal cancer
- Early stage diagnosis
- High abundant protein depletion
- Plasma protein biomarkers
- Predictive model
- SWATH-MS
Fingerprint
Dive into the research topics of 'Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel'. Together they form a unique fingerprint.Projects
- 1 Finished
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Colorectal Cancer Membrane Protein Interactomics (A Major Discriminator of Clinical Outcome)
Baker, M. S. & Nice, E.
1/01/11 → 31/12/14
Project: Research
Research output
- 57 Citations
- 1 Article
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Deciphering the kidney matrisome: identification and quantification of renal extracellular matrix proteins in healthy mice
Rende, U., Ahn, S. B., Adhikari, S., Moh, E. S. X., Pollock, C. A., Saad, S. & Guller, A., 1 Feb 2023, In: International Journal of Molecular Sciences. 24, 3, p. 1-31 31 p., 2827.Research output: Contribution to journal › Article › peer-review
Open AccessFile6 Citations (Scopus)99 Downloads (Pure)