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BMC Cancer
Published in: BMC Cancer 1/2017

Open Access 01-12-2017 | Research article

MALDI-TOF-MS analysis in discovery and identification of serum proteomic patterns of ovarian cancer

Authors: Agata Swiatly, Agnieszka Horala, Joanna Hajduk, Jan Matysiak, Ewa Nowak-Markwitz, Zenon J. Kokot

Published in: BMC Cancer | Issue 1/2017

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Abstract

Background

Due to high mortality and lack of efficient screening, new tools for ovarian cancer (OC) diagnosis are urgently needed. To broaden the knowledge on the pathological processes that occur during ovarian cancer tumorigenesis, protein-peptide profiling was proposed.

Methods

Serum proteomic patterns in samples from OC patients were obtained using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF). Eighty nine serum samples (44 ovarian cancer and 45 healthy controls) were pretreated using solid-phase extraction method. Next, a classification model with the most discriminative factors was identified using chemometric algorithms. Finally, the results were verified by external validation on an independent test set of samples.

Results

Main outcome of this study was an identification of potential OC biomarkers by applying liquid chromatography coupled with tandem mass spectrometry. Application of this novel strategy enabled the identification of four potential OC serum biomarkers (complement C3, kininogen-1, inter-alpha-trypsin inhibitor heavy chain H4, and transthyretin). The role of these proteins was discussed in relation to OC pathomechanism.

Conclusions

The study results may contribute to the development of clinically useful multi-component diagnostic tools in OC. In addition, identifying a novel panel of discriminative proteins could provide a new insight into complex signaling and functional networks associated with this multifactorial disease.
Appendix
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Literature
1.
2.
Havrilesky LJ, Sanders GD, Kulasingam S, Myers ER. Reducing ovarian cancer mortality through screening: is it possible, and can we afford it? Gynecol Oncol. 2008;111:179–87.CrossRefPubMed
3.
Romagnolo C, Leon AE, Fabricio ASC, Taborelli M, Polesel J, Del Pup L, et al. HE4, CA125 and risk of ovarian malignancy algorithm (ROMA) as diagnostic tools for ovarian cancer in patients with a pelvic mass: an Italian multicenter study. Gynecol Oncol. 2016;141:303–11.CrossRefPubMed
4.
5.
Terlikowska KM, Dobrzycka B, Witkowska AM, Mackowiak-Matejczyk B, Sledziewski TK, Kinalski M, et al. Preoperative HE4, CA125 and ROMA in the differential diagnosis of benign and malignant adnexal masses. J Ovarian Res. 2016;9:43.CrossRefPubMedPubMedCentral
6.
Karlan BY, Thorpe J, Watabayashi K, Drescher CW, Palomares M, Daly MB, et al. Use of CA125 and HE4 serum markers to predict ovarian cancer in elevated-risk women. Cancer Epidemiol Prev Biomarkers. 2014;23
7.
Chang X, Ye X, Dong L, Cheng H, Cheng Y, Zhu L, et al. Human epididymis protein 4 (HE4) as a serum tumor biomarker in patients with ovarian carcinoma. Int J Gynecol Cancer. 2011;21:852–8.CrossRefPubMed
8.
Moore RG, Miller MC, Eklund EE, Lu KH, Bast RC, Lambert-Messerlian G. Serum levels of the ovarian cancer biomarker HE4 are decreased in pregnancy and increase with age. Am J Obstet Gynecol. 2012;206:349–7.PubMed
9.
Eskander RN, Carpenter BA, Wu HG, Wolf JK. The clinical utility of an elevated-risk multivariate index assay score in ovarian cancer patients. Curr Med Res Opin. 2016;32:1161–5.CrossRefPubMed
10.
Moore RG, Miller MC, Disilvestro P, Landrum LM, Gajewski W, Ball JJ, et al. Evaluation of the diagnostic accuracy of the risk of ovarian malignancy algorithm in women with a pelvic mass. Obstet Gynecol. 2011;118:280–8.CrossRefPubMedPubMedCentral
11.
12.
Widlak P, Pietrowska M, Polanska J, Marczyk M, Ros-Mazurczyk M, Dziadziuszko R, et al. Serum mass profile signature as a biomarker of early lung cancer. Lung Cancer. 2016;99:46–52.CrossRefPubMed
13.
Opstal-van Winden AWJ, Krop EJM, Kåredal MH, Gast M-CW, Lindh CH, Jeppsson MC, et al. Searching for early breast cancer biomarkers by serum protein profiling of pre-diagnostic serum; a nested case-control study. BMC Cancer. 2011;11:381.CrossRefPubMedPubMedCentral
14.
Yang J, Yang J, Gao Y, Zhao L, Liu L, Qin Y, et al. Identification of potential serum proteomic biomarkers for clear cell renal cell carcinoma. PLoS One. 2014;9:e111364.CrossRefPubMedPubMedCentral
15.
Hajduk J, Matysiak J, Kokot ZJ. Challenges in biomarker discovery with MALDI-TOF MS. Clin Chim Acta. 2016;458:84–98.CrossRefPubMed
16.
Petricoin EF, Ardekani AM, Hitt BA, Levine PJ, Fusaro VA, Steinberg SM, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002;359:572–7.CrossRefPubMed
17.
Sandanayake NS, Camuzeaux S, Sinclair J, Blyuss O, Andreola F, Chapman MH, et al. Identification of potential serum peptide biomarkers of biliary tract cancer using MALDI MS profiling. BMC Clin Pathol. 2014;14:7.CrossRefPubMedPubMedCentral
18.
Callesen AK, Madsen JS, Vach W, Kruse TA, Mogensen O, Jensen ON. Serum protein profiling by solid phase extraction and mass spectrometry: A future diagnostics tool. Proteomics. 2009:1428–41.
19.
Bellei E, Bergamini S, Monari E, Fantoni LI, Cuoghi A, Ozben T, et al. High-abundance proteins depletion for serum proteomic analysis: concomitant removal of non-targeted proteins. Amino Acids. 2011;40:145–56.CrossRefPubMed
20.
Hajduk J, Matysiak J, Kokot P, Nowicki P, Dereziński P, Kokot ZJ. The application of fuzzy statistics and linear discriminant analysis as criteria for optimizing the preparation of plasma for matrix-assisted laser desorption/ionization mass spectrometry peptide profiling. Clin Chim Acta. 2015;448:174–81.CrossRefPubMed
21.
Tiss A, Smith C, Camuzeaux S, Kabir M, Gayther S, Menon U, et al. Serum peptide profiling using MALDI mass spectrometry: avoiding the pitfalls of coated magnetic beads using well-established ZipTip technology. Proteomics. 2007;7(Suppl 1):77–89.CrossRefPubMed
22.
Klupczynska A, Swiatly A, Hajduk J, Matysiak J, Dyszkiewicz W, Pawlak K, et al. Identification of serum peptidome signatures of non-small cell lung cancer. Int J Mol Sci. 2016;17
23.
Marcus CS, Maxwell GL, Darcy KM, Hamilton CA, Mcguire WP. Current approaches and challenges in managing and monitoring treatment response in ovarian cancer. J Cancer. 2014;5:25–30.CrossRefPubMedPubMedCentral
24.
Lopez MF, Mikulskis A, Kuzdzal S, Golenko E, Petricoin EF, Liotta LA, et al. A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples. Clin Chem. 2007;53:1067–74.CrossRefPubMed
25.
Periyasamy A, Gopisetty G, Veluswami S, Joyimallaya Subramanium M, Thangarajan R. Identification of candidate biomarker mass (m/z) ranges in serous ovarian adenocarcinoma using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling. Biomarkers. 2015;20:292–8.CrossRefPubMed
26.
Wu S, Xu K, Chen G, Zhang J, Liu Z, Xie X. Identification of serum biomarkers for ovarian cancer using MALDI–TOF-MS combined with magnetic beads. Int J Clin Oncol. 2012;17:89–95.CrossRefPubMed
27.
Yin X, Subramanian S, Hwang S-J, O’Donnell CJ, Fox CS, Courchesne P, et al. Protein biomarkers of new-onset cardiovascular disease. Arterioscler Thromb Vasc Biol. 2014;34(4):939–45.CrossRefPubMedPubMedCentral
28.
Horala A, Swiatly A, Matysiak J, Banach P, Nowak-Markwitz E, Kokot Z. Diagnostic value of serum angiogenesis markers in ovarian cancer using multiplex immunoassay. Int J Mol Sci. 2017;18:123.CrossRefPubMedCentral
29.
Basics on data preparation model generation and spectra classification. In: ClinProTools 3.0 Software for biomarker detection and evaluation User Manual. Bruker Daltonics; Bremen, Germany: 2011.; p. 51–96.
30.
Zhang Y, Chen X, Hu Y, Du S, Shen L, He Y, et al. Preliminary characterizations of a serum biomarker for sarcoidosis by comparative proteomic approach with tandem-mass spectrometry in ethnic Han Chinese patients. Respir. Res. BioMed Central; 2013;14:18.
31.
Bleeker S, Moll H, Steyerberg E, Donders AR, Derksen-Lubsen G, Grobbee D, et al. External validation is necessary in prediction research:: A clinical example. J Clin Epidemiol. 2003;56:826–32.CrossRefPubMed
32.
Ioannidis JPA. A roadmap for successful applications of clinical PROTEOMICS. PROTEOMICS - Clin. Appl. 2011;5:241–7.
33.
Chinello C, Cazzaniga M, De Sio G, Smith AJ, Gianazza E, Grasso A, et al. Urinary Signatures of Renal Cell Carcinoma Investigated by Peptidomic Approaches. Eberini I, editor. PLoS One. 2014;9:e106684.
34.
Rutkowski MJ, Sughrue ME, Kane AJ, Mills SA, Parsa AT, Balkwill F, et al. Cancer and the complement cascade. Mol Cancer Res. 2010;8:1453–65.CrossRefPubMed
35.
36.
Wang J, Wang X, Lin S, Chen C, Wang C, Ma Q, et al. Identification of Kininogen-1 as a serum biomarker for the early detection of advanced colorectal adenoma and colorectal cancer. PLoS One. 2013;8:e70519.CrossRefPubMedPubMedCentral
37.
Abdullah-Soheimi SS, Lim B-K, Hashim OH, Shuib AS. Patients with ovarian carcinoma excrete different altered levels of urine CD59, kininogen-1 and fragments of inter-alpha-trypsin inhibitor heavy chain H4 and albumin. Proteome Sci. 2010;8:58.CrossRefPubMedPubMedCentral
38.
Yu J, Peng R, Chen H, Cui C, Ba J, Wang F. Kininogen 1 and insulin-like growth factor binding protein 6: candidate serum biomarkers of proliferative vitreoretinopathy. Clin Exp Optom. 2014;97:72–9.CrossRefPubMed
39.
Canter MP, Graham CA, Heit MH, Blackwell LS, Wilkey DW, Klein JB, et al. Proteomic techniques identify urine proteins that differentiate patients with interstitial cystitis from asymptomatic control subjects. Am. J. Obstet. Gynecol. 2008;198:553.e1–6.
40.
Rocchetti MT, Centra M, Papale M, Bortone G, Palermo C, Centonze D, et al. Urine protein profile of IgA nephropathy patients may predict the response to ACE-inhibitor therapy. Proteomics. 2008;8:206–16.CrossRefPubMed
41.
Subbannayya Y, Mir SA, Renuse S, Manda SS, Pinto SM, Puttamallesh VN, et al. Identification of differentially expressed serum proteins in gastric adenocarcinoma. J Proteome. 2015;127:80–8.CrossRef
42.
Mohamed E, Abdul-Rahman PS, Doustjalali SR, Chen Y, Lim B, Omar SZ, et al. Lectin-based electrophoretic analysis of the expression of the 35 kDa inter-α-trypsin inhibitor heavy chain H4 fragment in sera of patients with five different malignancies. Electrophoresis. 2008;29:2645–50.CrossRefPubMed
43.
Jayapalan JJ, Ng KL, Shuib AS, Razack AHA, Hashim OH. Urine of patients with early prostate cancer contains lower levels of light chain fragments of inter-alpha-trypsin inhibitor and saposin B but increased expression of an inter-alpha-trypsin inhibitor heavy chain 4 fragment. Electrophoresis. 2013;34:1663–9.CrossRefPubMed
44.
van den Broek I, Sparidans RW, van Winden AWJ, Gast M-CW, van Dulken EJ, Schellens JHM, et al. The absolute quantification of eight inter-α-trypsin inhibitor heavy chain 4 (ITIH4)-derived peptides in serum from breast cancer patients. Proteomics Clin Appl. 2010;4:931–9.CrossRefPubMed
45.
Song J, Patel M, Rosenzweig CN, Chan-Li Y, Sokoll LJ, Fung ET, et al. Quantification of fragments of human serum inter-alpha-trypsin inhibitor heavy chain 4 by a surface-enhanced laser desorption/ionization-based immunoassay. Clin Chem. 2006;52:1045–53.CrossRefPubMed
46.
Moore LE, Fung ET, McGuire M, Rabkin CC, Molinaro A, Wang Z, et al. Evaluation of apolipoprotein A1 and Posttranslationally modified forms of transthyretin as biomarkers for ovarian cancer detection in an independent study population. Cancer Epidemiol Biomark Prev. 2006;15:1641–6.CrossRef
47.
Husseinzadeh N. Status of tumor markers in epithelial ovarian cancer has there been any progress? A review Gynecol Oncol. 2011;120:152–7.CrossRefPubMed
48.
Doldo E, Costanza G, Agostinelli S, Tarquini C, Ferlosio A, Arcuri G, et al. Vitamin a, cancer treatment and prevention: the new role of cellular retinol binding proteins. Biomed Res Int. 2015;2015:624627.CrossRefPubMedPubMedCentral
49.
Liu C, Shen J, Pan C, Yang L, Mou S, Wang H, et al. MALDI-TOF MS combined with magnetic beads for detecting serum protein biomarkers and establishment of boosting decision tree model for diagnosis of hepatocellular carcinoma. Am J Clin Pathol. 2010;134:235–41.CrossRefPubMed
Metadata
Title
MALDI-TOF-MS analysis in discovery and identification of serum proteomic patterns of ovarian cancer
Authors
Agata Swiatly
Agnieszka Horala
Joanna Hajduk
Jan Matysiak
Ewa Nowak-Markwitz
Zenon J. Kokot
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2017
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-017-3467-2

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