1
|
Dufresne J, Bowden P, Thavarajah T, Florentinus-Mefailoski A, Chen ZZ, Tucholska M, Norzin T, Ho MT, Phan M, Mohamed N, Ravandi A, Stanton E, Slutsky AS, Dos Santos CC, Romaschin A, Marshall JC, Addison C, Malone S, Heyland D, Scheltens P, Killestein J, Teunissen C, Diamandis EP, Siu KWM, Marshall JG. The plasma peptides of breast versus ovarian cancer. Clin Proteomics 2019; 16:43. [PMID: 31889940 PMCID: PMC6927194 DOI: 10.1186/s12014-019-9262-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 12/05/2019] [Indexed: 02/07/2023] Open
Abstract
Background There is a need to demonstrate a proof of principle that proteomics has the capacity to analyze plasma from breast cancer versus other diseases and controls in a multisite clinical trial design. The peptides or proteins that show a high observation frequency, and/or precursor intensity, specific to breast cancer plasma might be discovered by comparison to other diseases and matched controls. The endogenous tryptic peptides of breast cancer plasma were compared to ovarian cancer, female normal, sepsis, heart attack, Alzheimer's and multiple sclerosis along with the institution-matched normal and control samples collected directly onto ice. Methods Endogenous tryptic peptides were extracted from individual breast cancer and control EDTA plasma samples in a step gradient of acetonitrile, and collected over preparative C18 for LC-ESI-MS/MS with a set of LTQ XL linear quadrupole ion traps working together in parallel to randomly and independently sample clinical populations. The MS/MS spectra were fit to fully tryptic peptides or phosphopeptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The observation frequency was subsequently tested by Chi Square analysis. The log10 precursor intensity was compared by ANOVA in the R statistical system. Results Peptides and/or phosphopeptides of common plasma proteins such as APOE, C4A, C4B, C3, APOA1, APOC2, APOC4, ITIH3 and ITIH4 showed increased observation frequency and/or precursor intensity in breast cancer. Many cellular proteins also showed large changes in frequency by Chi Square (χ2 > 100, p < 0.0001) in the breast cancer samples such as CPEB1, LTBP4, HIF-1A, IGHE, RAB44, NEFM, C19orf82, SLC35B1, 1D12A, C8orf34, HIF1A, OCLN, EYA1, HLA-DRB1, LARS, PTPDC1, WWC1, ZNF562, PTMA, MGAT1, NDUFA1, NOGOC, OR1E1, OR1E2, CFI, HSA12, GCSH, ELTD1, TBX15, NR2C2, FLJ00045, PDLIM1, GALNT9, ASH2L, PPFIBP1, LRRC4B, SLCO3A1, BHMT2, CS, FAM188B2, LGALS7, SAT2, SFRS8, SLC22A12, WNT9B, SLC2A4, ZNF101, WT1, CCDC47, ERLIN1, SPFH1, EID2, THOC1, DDX47, MREG, PTPRE, EMILIN1, DKFZp779G1236 and MAP3K8 among others. The protein gene symbols with large Chi Square values were significantly enriched in proteins that showed a complex set of previously established functional and structural relationships by STRING analysis. An increase in mean precursor intensity of peptides was observed for QSER1 as well as SLC35B1, IQCJ-SCHIP1, MREG, BHMT2, LGALS7, THOC1, ANXA4, DHDDS, SAT2, PTMA and FYCO1 among others. In contrast, the QSER1 peptide QPKVKAEPPPK was apparently specific to ovarian cancer. Conclusion There was striking agreement between the breast cancer plasma peptides and proteins discovered by LC-ESI-MS/MS with previous biomarkers from tumors, cells lines or body fluids by genetic or biochemical methods. The results indicate that variation in plasma peptides from breast cancer versus ovarian cancer may be directly discovered by LC-ESI-MS/MS that will be a powerful tool for clinical research. It may be possible to use a battery of sensitive and robust linear quadrupole ion traps for random and independent sampling of plasma from a multisite clinical trial.
Collapse
Affiliation(s)
- Jaimie Dufresne
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Pete Bowden
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Thanusi Thavarajah
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Angelique Florentinus-Mefailoski
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Zhuo Zhen Chen
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Monika Tucholska
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Tenzin Norzin
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Margaret Truc Ho
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Morla Phan
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Nargiz Mohamed
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| | - Amir Ravandi
- 2Institute of Cardiovascular Sciences, St. Boniface Hospital Research Center, University of Manitoba, Winnipeg, Canada
| | - Eric Stanton
- 3Division of Cardiology, Department of Medicine, McMaster University, Hamilton, Canada
| | - Arthur S Slutsky
- 4St. Michael's Hospital, Keenan Chair in Medicine, Professor of Medicine, Surgery & Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Claudia C Dos Santos
- 5St. Michael's Hospital, Keenan Research Centre for Biomedical Science, Toronto, Canada
| | - Alexander Romaschin
- 5St. Michael's Hospital, Keenan Research Centre for Biomedical Science, Toronto, Canada
| | - John C Marshall
- 5St. Michael's Hospital, Keenan Research Centre for Biomedical Science, Toronto, Canada
| | - Christina Addison
- 6Program for Cancer Therapeutics, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Shawn Malone
- 6Program for Cancer Therapeutics, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Daren Heyland
- 7Clinical Evaluation Research Unit, Kingston General Hospital, Kingston, Canada
| | - Philip Scheltens
- 8Alzheimer Center, Dept of Neurology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Joep Killestein
- 9MS Center, Dept of Neurology, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Charlotte Teunissen
- 10Neurochemistry Lab and Biobank, Dept of Clinical Chemsitry, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | | | - K W M Siu
- 12University of Windsor, Windsor, Canada
| | - John G Marshall
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada.,13International Biobank of Luxembourg (IBBL), Luxembourg Institute of Health (formerly CRP Sante Luxembourg), Strassen, Luxembourg
| |
Collapse
|