The plasma peptides of ovarian cancer

Abstract

BackgroundIt 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.MethodsThe 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.ResultsPeptides 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.ConclusionHere 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 tumor...

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

“…For example, methods have been developed to focus on specific sub-proteomes (plasma glycoproteome and phosphoproteome) [76][77][78] , proteins that have a specific activity (cytokines for signaling), or those that originate from specific compartments (membrane proteins) 79 . In addition to functional-based enrichment, physical properties of proteins have also been utilized to increase target-protein concentrations 69,80 .…”

LOXL3 Function Beyond Amino Oxidase and Role in Pathologies, Including Cancer

“…LOXL3 expression was also detected in various kinds of tumors, such as myeloproliferative neoplasms [43] and ovarian carcinoma (primary tumor, metastasis, and peritoneum and pleura effusions) [41]. LOXL3 peptide was detected in the plasma of ovarian cancer patients [44]. Furthermore, LOXL3 expression has been detected in circulating tumor cells of colorectal cancer, and its expression has been correlated with treatment response and prognosis [45,46].…”

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

“…In this approach, workflows are used to increase the sensitivity for specific proteins of interest 62 . For example, methods have been developed to focus on specific sub-proteomes (plasma glycoproteome and phosphoproteome) [76][77][78] , proteins that have a specific activity (cytokines for signaling), or those that originate from specific compartments (membrane proteins) 79 . In addition to functional-based enrichment, physical properties of proteins have also been utilized to increase target-protein concentrations 69,80 .…”