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 CE, Diamandis EP, Michael Siu KW, Marshall JG. The plasma peptides of ovarian cancer. Clin Proteomics 2018; 15:41. [PMID: 30598658 PMCID: PMC6302491 DOI: 10.1186/s12014-018-9215-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 11/19/2018] [Indexed: 12/13/2022] Open
Abstract
Background It may be possible to discover new diagnostic or therapeutic peptides or proteins from blood plasma by using liquid chromatography and tandem mass spectrometry to identify, quantify and compare the peptides cleaved ex vivo from different clinical populations. The endogenous tryptic peptides of ovarian cancer plasma were compared to breast cancer and female cancer normal controls, other diseases with their matched or normal controls, plus ice cold plasma to control for pre-analytical variation. Methods The endogenous tryptic peptides or tryptic phospho peptides (i.e. without exogenous digestion) were analyzed from 200 μl of EDTA plasma. The plasma peptides were extracted by a step gradient of organic/water with differential centrifugation, dried, and collected over C18 for analytical HPLC nano electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) with a linear quadrupole ion trap. The endogenous peptides of ovarian cancer were compared to multiple disease and normal samples from different institutions alongside ice cold controls. Peptides were randomly and independently sampled by LC–ESI–MS/MS. Precursor ions from peptides > E4 counts were identified by the SEQUEST and X!TANDEM algorithms, filtered in SQL Server, before testing of frequency counts by Chi Square (χ2), for analysis with the STRING algorithm, and comparison of precursor intensity by ANOVA in the R statistical system with the Tukey-Kramer Honestly Significant Difference (HSD) test. Results Peptides and/or phosphopeptides of common plasma proteins such as HPR, HP, HPX, and SERPINA1 showed increased observation frequency and/or precursor intensity in ovarian cancer. Many cellular proteins showed large changes in frequency by Chi Square (χ2 > 60, p < 0.0001) in the ovarian cancer samples such as ZNF91, ZNF254, F13A1, LOC102723511, ZNF253, QSER1, P4HA1, GPC6, LMNB2, PYGB, NBR1, CCNI2, LOC101930455, TRPM5, IGSF1, ITGB1, CHD6, SIRT1, NEFM, SKOR2, SUPT20HL1, PLCE1, CCDC148, CPSF3, MORN3, NMI, XTP11, LOC101927572, SMC5, SEMA6B, LOXL3, SEZ6L2, and DHCR24. 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. Analysis of the frequently observed proteins by ANOVA confirmed increases in mean precursor intensity in ZFN91, TRPM5, SIRT1, CHD6, RIMS1, LOC101930455 (XP_005275896), CCDC37 and GIMAP4 between ovarian cancer versus normal female and other diseases or controls by the Tukey–Kramer HSD test. Conclusion Here we show that separation of endogenous peptides with a step gradient of organic/water and differential centrifugation followed by random and independent sampling by LC–ESI–MS/MS with analysis of peptide frequency and intensity by SQL Server and R revealed significant difference in the ex vivo cleavage of peptides between ovarian cancer and other clinical treatments. There was striking agreement between the proteins discovered from cancer plasma versus previous biomarkers discovered in tumors by genetic or biochemical methods. The results indicate that variation in plasma proteins from ovarian cancer may be directly discovered by LC–ESI–MS/MS that will be a powerful tool for clinical research. Electronic supplementary material The online version of this article (10.1186/s12014-018-9215-z) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Jaimie Dufresne
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada
| | - Pete Bowden
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada
| | - Thanusi Thavarajah
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada
| | | | - Zhuo Zhen Chen
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada
| | - Monika Tucholska
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada
| | - Tenzin Norzin
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada
| | - Margaret Truc Ho
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada
| | - Morla Phan
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada
| | - Nargiz Mohamed
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, 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
- 4Keenan Chair in Medicine, St. Michael's Hospital, University of Toronto, Toronto, Canada
| | - Claudia C Dos Santos
- 5Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Canada
| | - Alexander Romaschin
- 5Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Canada
| | - John C Marshall
- 5Keenan Research Centre for Biomedical Science, St. Michael's Hospital, 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, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
| | - Joep Killestein
- 9MS Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- 10Neurochemistry Lab and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
| | | | | | - John G Marshall
- 1Ryerson Analytical Biochemistry Laboratory (RABL), Department of Chemistry and Biology, Ryerson University, Toronto, Canada.,13International Biobank of Luxembourg (IBBL), Luxembourg Institute of Health (formerly CRP Sante Luxembourg), Strassen, Luxembourg.,14Department of Chemistry and Biology, Faculty of Science, Ryerson University, 350 Victoria St., Toronto, ON Canada
| |
Collapse
|
2
|
Chaerkady R, Harsha HC, Nalli A, Gucek M, Vivekanandan P, Akhtar J, Cole RN, Simmers J, Schulick RD, Singh S, Torbenson M, Pandey A, Thuluvath PJ. A quantitative proteomic approach for identification of potential biomarkers in hepatocellular carcinoma. J Proteome Res 2008; 7:4289-98. [PMID: 18715028 DOI: 10.1021/pr800197z] [Citation(s) in RCA: 106] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. In this study, our objective was to identify differentially regulated proteins in HCC through a quantitative proteomic approach using iTRAQ. More than 600 proteins were quantitated of which 59 proteins were overexpressed and 92 proteins were underexpressed in HCC as compared to adjacent normal tissue. Several differentially expressed proteins were not implicated previously in HCC. A subset of these proteins (six each from upregulated and downregulated groups) was further validated using immunoblotting and immunohistochemical labeling. Some of the overexpressed proteins with no previous description in the context of HCC include fibroleukin, interferon induced 56 kDa protein, milk fat globule-EGF factor 8, and myeloid-associated differentiation marker. Interestingly, all the enzymes of urea metabolic pathway were dramatically downregulated. Immunohistochemical labeling confirmed differential expression of fibroleukin, myeloid associated differentiation marker and ornithine carbamoyl transferase in majority of HCC samples analyzed. Our results demonstrate quantitative proteomics as a robust discovery tool for the identification of differentially regulated proteins in cancers.
Collapse
Affiliation(s)
- Raghothama Chaerkady
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|