Data-Independent Acquisition and Parallel Reaction Monitoring Mass Spectrometry Identification of Serum Biomarkers for Ovarian Cancer

Overview

Journal Biomark Insights

Publisher Sage Publications

Date 2017 Jun 16

PMID 28615921

Citations 15

Authors

Navin Rauniyar

Gang Peng

TuKiet T Lam

Hongyu Zhao

Gil Mor

Kenneth R Williams

Affiliations

Soon will be listed here.

Abstract

A data-independent acquisition (DIA)/parallel reaction monitoring (PRM) workflow was implemented to identify improved ovarian cancer biomarkers. Data-independent acquisition on ovarian cancer versus control sera and literature searches identified 50 biomarkers and indicated that apolipoprotein A-IV (ApoA-IV) is the most significantly differentially regulated protein. Parallel reaction monitoring with Targeted Ovarian Cancer Proteome Assay validated differential ApoA-IV expression and quantified 9 other biomarkers. Random Forest (RF) analyses achieved 92.3% classification accuracy and confirmed ApoA-IV as the leading biomarker. Indeed, all samples were classified correctly with an [ApoA-IV] breakpoint. The next best biomarkers were C-reactive protein, transferrin, and transthyretin. The Targeted Ovarian Cancer Proteome Assay suggests that ApoA-IV is a more reliable biomarker than had been determined by immunological assays and it is a better biomarker than ApoA-I, which is in the OVA1 test for ovarian cancer. This research provides a PRM/RF approach together with 4 promising biomarkers to speed the development of a clinical assay for ovarian cancer.

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References

Lai C, Parnell L, Ordovas J . The APOA1/C3/A4/A5 gene cluster, lipid metabolism and cardiovascular disease risk. Curr Opin Lipidol. 2005; 16(2):153-66. DOI: 10.1097/01.mol.0000162320.54795.68. View

Shushan B . A review of clinical diagnostic applications of liquid chromatography-tandem mass spectrometry. Mass Spectrom Rev. 2010; 29(6):930-44. DOI: 10.1002/mas.20295. View

Boente M, Schilder R, Ozols R . Gynecological cancers. Cancer Chemother Biol Response Modif. 2000; 18:418-34. View

Jain S, Gautam V, Naseem S . Acute-phase proteins: As diagnostic tool. J Pharm Bioallied Sci. 2011; 3(1):118-27. PMC: 3053509. DOI: 10.4103/0975-7406.76489. View

Carr S, Abbatiello S, Ackermann B, Borchers C, Domon B, Deutsch E . Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach. Mol Cell Proteomics. 2014; 13(3):907-17. PMC: 3945918. DOI: 10.1074/mcp.M113.036095. View

Shi J, Qin J, Ye H, Wang P, Wang K, Zhang J . Tumor associated antigens or anti-TAA autoantibodies as biomarkers in the diagnosis of ovarian cancer: a systematic review with meta-analysis. Expert Rev Mol Diagn. 2015; 15(6):829-52. DOI: 10.1586/14737159.2015.1035713. View

Jacobs I, Menon U . Progress and challenges in screening for early detection of ovarian cancer. Mol Cell Proteomics. 2004; 3(4):355-66. DOI: 10.1074/mcp.R400006-MCP200. View

McSorley M, Alberg A, Allen D, Allen N, Brinton L, Dorgan J . C-reactive protein concentrations and subsequent ovarian cancer risk. Obstet Gynecol. 2007; 109(4):933-41. DOI: 10.1097/01.AOG.0000257126.68803.03. View

Edgell T, Martin-Roussety G, Barker G, Autelitano D, Allen D, Grant P . Phase II biomarker trial of a multimarker diagnostic for ovarian cancer. J Cancer Res Clin Oncol. 2010; 136(7):1079-88. PMC: 2874491. DOI: 10.1007/s00432-009-0755-5. View

10.

Gallien S, Kim S, Domon B . Large-Scale Targeted Proteomics Using Internal Standard Triggered-Parallel Reaction Monitoring (IS-PRM). Mol Cell Proteomics. 2015; 14(6):1630-44. PMC: 4458725. DOI: 10.1074/mcp.O114.043968. View

11.

Huttenhain R, Soste M, Selevsek N, Rost H, Sethi A, Carapito C . Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics. Sci Transl Med. 2012; 4(142):142ra94. PMC: 3766734. DOI: 10.1126/scitranslmed.3003989. View

12.

Colangelo C, Shifman M, Cheung K, Stone K, Carriero N, Gulcicek E . YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research. Genomics Proteomics Bioinformatics. 2015; 13(1):25-35. PMC: 4411476. DOI: 10.1016/j.gpb.2014.11.002. View

13.

Shifman M, Sun K, Colangelo C, Cheung K, Miller P, Williams K . YPED: a proteomics database for protein expression analysis. AMIA Annu Symp Proc. 2006; :1111. PMC: 1560545. View

14.

Abraham K, Muller C, Gruters A, Wahn U, Schweigert F . Minimal inflammation, acute phase response and avoidance of misclassification of vitamin A and iron status in infants--importance of a high-sensitivity C-reactive protein (CRP) assay. Int J Vitam Nutr Res. 2004; 73(6):423-30. DOI: 10.1024/0300-9831.73.6.423. View

15.

Marcon E, Jain H, Bhattacharya A, Guo H, Phanse S, Pu S . Assessment of a method to characterize antibody selectivity and specificity for use in immunoprecipitation. Nat Methods. 2015; 12(8):725-31. DOI: 10.1038/nmeth.3472. View

16.

Gericke B, Raila J, Sehouli J, Haebel S, Konsgen D, Mustea A . Microheterogeneity of transthyretin in serum and ascitic fluid of ovarian cancer patients. BMC Cancer. 2005; 5:133. PMC: 1274304. DOI: 10.1186/1471-2407-5-133. View

17.

Peterson A, Russell J, Bailey D, Westphall M, Coon J . Parallel reaction monitoring for high resolution and high mass accuracy quantitative, targeted proteomics. Mol Cell Proteomics. 2012; 11(11):1475-88. PMC: 3494192. DOI: 10.1074/mcp.O112.020131. View

18.

Domanski D, Percy A, Yang J, Chambers A, Hill J, Cohen Freue G . MRM-based multiplexed quantitation of 67 putative cardiovascular disease biomarkers in human plasma. Proteomics. 2012; 12(8):1222-43. DOI: 10.1002/pmic.201100568. View

19.

Wu B, Abbott T, Fishman D, McMurray W, Mor G, Stone K . Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data. Bioinformatics. 2003; 19(13):1636-43. DOI: 10.1093/bioinformatics/btg210. View

20.

Bilbao A, Varesio E, Luban J, Strambio-De-Castillia C, Hopfgartner G, Muller M . Processing strategies and software solutions for data-independent acquisition in mass spectrometry. Proteomics. 2014; 15(5-6):964-80. DOI: 10.1002/pmic.201400323. View