Journal: Clinical Proteomics
Article Title: Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel
doi: 10.1186/s12014-019-9255-z
Figure Lengend Snippet: Blood-based multi-analyte proteomic signature discovery workflow: a A total of 100 age- and sex-matched EDTA-plasma samples were procured [n = 20 per stage I, II, III, IV, and n = 20 healthy controls (non-menopausal, non-smoking and no history of any cancers)]. b Plasma samples were collected as per ethics requirements. To create a plasma reference library, equal volumes of all patients and healthy plasmas were pooled. For the SWATH experiments, equal volumes of 20 plasma samples were combined to produce pools of each of the 4 CRC stages (I–IV) and healthy controls. c For library generation, HAPs depleted using MARS-14 column (Agilent) followed by tryptic digestion and peptide fractionation by SAX, SCX, SEC and HpH (independently), followed by IDA-MS analysis. d The stage pooled samples were processed through four different experiments (three, where the plasma HAP were depleted and one where it was not). The resulting proteins were digested and subjected to SWATH-MS. Lists of quantifiable proteins were extracted from the SWATH dataset using the peptide library generated in c . e Differentially expressed proteins were first identified using ANOVA/t-test (p-value < 0.05, fold change cut off ± 1.5), resulting in 37 proteins exhibited with differential expression across all CRC stages compared to healthy controls. These 37 proteins were further evaluated by unsupervised clustering method to increase discriminatory power. Differentially expressed proteins were subjected to validation pipeline where they were checked to identify evidence in the literature, followed by experimental validation (ELISA/Western blotting) of a subset that seemed most promising. Concurrently, the samples also underwent a supervised classification method which identified potential candidates which were then validated with an augmented dataset (with a SD 10 times the observed variance). This resulted in a subset of 5 candidate proteins that were able to classify the different stages of the disease. SAX strong anion exchange, SCX strong cation exchange, SEC size exclusion chromatography, HpH high pH reversed phased c18, SWATH sequential window acquisition of all theoretical mass spectra, IDA-MS information-dependent acquisition mass spectrometry, SD standard deviation, HAPs high abundant proteins
Article Snippet: Peptides were injected onto a reverse phase peptide C18 trap (Bruker peptide Captrap) for pre-concentration and desalted at a flow rate of 10 μl/min for 5 min with 0.1% formic acid (v/v) and 2% acetonitrile (v/v).
Techniques: Clinical Proteomics, Data-independent acquisition, Peptide Fractionation, Generated, Quantitative Proteomics, Biomarker Discovery, Enzyme-linked Immunosorbent Assay, Western Blot, Size-exclusion Chromatography, Mass Spectrometry, Standard Deviation
![Blood-based multi-analyte proteomic signature discovery workflow: a A total of 100 age- and sex-matched EDTA-plasma samples were procured [n = 20 per stage I, II, III, IV, and n = 20 healthy controls (non-menopausal, non-smoking and no history of any cancers)]. b Plasma samples were collected as per ethics requirements. To create a plasma reference library, equal volumes of all patients and healthy plasmas were pooled. For the SWATH experiments, equal volumes of 20 plasma samples were combined to produce pools of each of the 4 CRC stages (I–IV) and healthy controls. c For library generation, HAPs depleted using MARS-14 column (Agilent) followed by tryptic digestion and peptide fractionation by SAX, SCX, SEC and HpH (independently), followed by IDA-MS analysis. d The stage pooled samples were processed through four different experiments (three, where the plasma HAP were depleted and one where it was not). The resulting proteins were digested and subjected to SWATH-MS. Lists of quantifiable proteins were extracted from the SWATH dataset using the peptide library generated in c . e Differentially expressed proteins were first identified using ANOVA/t-test (p-value < 0.05, fold change cut off ± 1.5), resulting in 37 proteins exhibited with differential expression across all CRC stages compared to healthy controls. These 37 proteins were further evaluated by unsupervised clustering method to increase discriminatory power. Differentially expressed proteins were subjected to validation pipeline where they were checked to identify evidence in the literature, followed by experimental validation (ELISA/Western blotting) of a subset that seemed most promising. Concurrently, the samples also underwent a supervised classification method which identified potential candidates which were then validated with an augmented dataset (with a SD 10 times the observed variance). This resulted in a subset of 5 candidate proteins that were able to classify the different stages of the disease. SAX strong anion exchange, SCX strong cation exchange, SEC size exclusion chromatography, HpH high pH reversed phased <t>c18,</t> SWATH sequential window acquisition of all theoretical mass spectra, IDA-MS information-dependent acquisition mass spectrometry, SD standard deviation, HAPs high abundant proteins](https://pub-med-central-images-cdn.bioz.com/pub_med_central_ids_ending_with_2843/pmc06712843/pmc06712843__12014_2019_9255_Fig1_HTML.jpg)
