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The Empirical Statistical Model (ESM) for decoy library searching fused the expected amino acid sequence of 18 non-human protein standards to a human decoy library. The ESM assumed a priori the standards were pure such that only the 18 nominal proteins were true positive, all other proteins were false positive, there was no overlap in the peptides of non-human proteins versus human proteins, and that the score distribution of individual peptides would resolve true positive from false positive results or noise. The results of random and independent sampling by LC-ESI-MS/MS indicated that the fundamental assumptions of the ESM were not in good agreement with the actual purity of the commercial test standards and so the method showed a 99.7% false negative rate. The ESM for decoy library searching apparently showed poor agreement with SDS-PAGE using silver staining, goodness of fit of MS/MS spectra by X!TANDEM, FDR correction by Benjamini and Hochberg, or comparison to the observation frequency of null random MS/MS spectra, that all confirmed the standards contain hundreds of proteins with a low FDR of primary structural identification. The protein observation frequency increased with abundance and the log 10 precursor intensity distributions were Gaussian and nearly ideal for relative quantification. Image 1 • The ESM that is the basis of the entirely novel decoy library method for FDR showed a 99.7% false negative rate. • Protein standards were analyzed by SDS-PAGE, LC-ESI-MS/MS and compared to random MS/MS spectra controls. • SDS-PAGE, LC-ESI-MS/MS and random MS/MS spectra controls agree the protein standards contain hundreds of proteins. • X!TANDEM protein p-value and FDR q-value from R statistical analysis controls error rates. • Linear quadrupole ion trap was sufficient for identification and quantification of proteins with low type I error rate. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]