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Record W2077333201 · doi:10.1074/mcp.m600378-mcp200

Endometrial Carcinoma Biomarker Discovery and Verification Using Differentially Tagged Clinical Samples with Multidimensional Liquid Chromatography and Tandem Mass Spectrometry

2007· article· en· W2077333201 on OpenAlex
Leroi V. DeSouza, Jörg Grigull, Shaun Ghanny, Valérie Dubé, Alexander D. Romaschin, Terence J. Colgan, K. W. Michael Siu

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Bibliographic record

VenueMolecular & Cellular Proteomics · 2007
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsSt. Michael's HospitalMount Sinai HospitalUniversity of TorontoYork University
Fundersnot available
KeywordsBiomarker discoveryChromatographyTandem mass spectrometryMass spectrometryLiquid chromatography–mass spectrometryBiomarkerChemistryProteomics

Abstract

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The utility of differentially expressed proteins discovered and identified in an earlier study (DeSouza, L., Diehl, G., Rodrigues, M. J., Guo, J., Romaschin, A. D., Colgan, T. J., and Siu, K. W. M. (2005) Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and cleavable ICAT with multidimensional liquid chromatography and tandem mass spectrometry. J. Proteome Res. 4, 377–386) to discriminate malignant and benign endometrial tissue samples was verified in a 40-sample iTRAQ (isobaric tags for relative and absolute quantitation) labeling study involving normal proliferative and secretory samples and Types I and II endometrial cancer samples. None of these proteins had the sensitivity and specificity to be used individually to discriminate between normal and cancer samples. However, a panel of pyruvate kinase, chaperonin 10, and α1-antitrypsin achieved the best results with a sensitivity, specificity, predictive value, and positive predictive value of 0.95 each in a logistic regression analysis. In addition, three new potential markers were discovered, whereas two other proteins showed promising trends but were not detected in sufficient numbers of samples to permit statistical validation. Differential expressions of some of these candidate biomarkers were independently verified using immunohistochemistry. The utility of differentially expressed proteins discovered and identified in an earlier study (DeSouza, L., Diehl, G., Rodrigues, M. J., Guo, J., Romaschin, A. D., Colgan, T. J., and Siu, K. W. M. (2005) Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and cleavable ICAT with multidimensional liquid chromatography and tandem mass spectrometry. J. Proteome Res. 4, 377–386) to discriminate malignant and benign endometrial tissue samples was verified in a 40-sample iTRAQ (isobaric tags for relative and absolute quantitation) labeling study involving normal proliferative and secretory samples and Types I and II endometrial cancer samples. None of these proteins had the sensitivity and specificity to be used individually to discriminate between normal and cancer samples. However, a panel of pyruvate kinase, chaperonin 10, and α1-antitrypsin achieved the best results with a sensitivity, specificity, predictive value, and positive predictive value of 0.95 each in a logistic regression analysis. In addition, three new potential markers were discovered, whereas two other proteins showed promising trends but were not detected in sufficient numbers of samples to permit statistical validation. Differential expressions of some of these candidate biomarkers were independently verified using immunohistochemistry. Differential tagging with isotopic reagents, such as ICAT (1Gygi S.P. Rist B. Gerber S.A. Turecek F. Gelb M.H. Aebersold R. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.Nat. Biotechnol. 1999; 17: 994-999Crossref PubMed Scopus (4293) Google Scholar) or the more recent variation that uses isobaric tagging reagents, iTRAQ 1The abbreviations used are: iTRAQ, isobaric tags for relative and absolute quantitation; PCM, potential cancer marker; EmCa, endometrial carcinoma; SCX, strong cation exchange; RP, reverse phase; PIGR, polymeric immunoglobulin receptor; PK, pyruvate kinase; Cpn 10, chaperonin 10; PV, predictive value; PPV, positive predictive value; AUC, area under the curve; MIF, macrophage migration-inhibitory factor; AAT, α1-antitrypsin; CKB, creatine kinase chain B; PEBP, phosphatidylethanolamine-binding protein; hnRNP D0, heterogeneous nuclear ribonucleoprotein D0; WFDC2, WAP four-disulfide core domain protein 2; PMN, polymorphonuclear neutrophil; MMP-2, metalloproteinase-2; RA, retinoic acid; P-LAP, placental leucine aminopeptidase; IL, interleukin; LAP3, leucine aminopeptidase 3; SLPI, secretory leucocyte protease inhibitor; NE, neutrophil elastase. 1The abbreviations used are: iTRAQ, isobaric tags for relative and absolute quantitation; PCM, potential cancer marker; EmCa, endometrial carcinoma; SCX, strong cation exchange; RP, reverse phase; PIGR, polymeric immunoglobulin receptor; PK, pyruvate kinase; Cpn 10, chaperonin 10; PV, predictive value; PPV, positive predictive value; AUC, area under the curve; MIF, macrophage migration-inhibitory factor; AAT, α1-antitrypsin; CKB, creatine kinase chain B; PEBP, phosphatidylethanolamine-binding protein; hnRNP D0, heterogeneous nuclear ribonucleoprotein D0; WFDC2, WAP four-disulfide core domain protein 2; PMN, polymorphonuclear neutrophil; MMP-2, metalloproteinase-2; RA, retinoic acid; P-LAP, placental leucine aminopeptidase; IL, interleukin; LAP3, leucine aminopeptidase 3; SLPI, secretory leucocyte protease inhibitor; NE, neutrophil elastase. (Applied Biosystems, Foster City, CA), followed by multidimensional LC and MS/MS analysis is quickly being recognized as one of the more powerful methodologies in the search for biomarkers for various disease states. Our recent studies using both ICAT and iTRAQ reagents as means to facilitate the and relative of proteins from endometrial tissue in some potential cancer markers J. analysis of the proliferative and secretory of the protein and protein PubMed Scopus Google J. Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and with multidimensional liquid chromatography and tandem mass Proteome Res. PubMed Scopus Google were study the results of a more using a of samples and the iTRAQ and was the earlier results as as the panel of a cancer of the of the is the cancer in of of of and and is panel of biomarkers that in be for or cancer the for such biomarkers be from such as or the iTRAQ from tissues J. analysis of the proliferative and secretory of the protein and protein PubMed Scopus Google J. Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and with multidimensional liquid chromatography and tandem mass Proteome Res. PubMed Scopus Google The for is that the of is in the tissue and not in the In addition, the of the tissue the to that differentially expressed protein detected from the endometrial the of differentially expressed protein in the a of potential other the The of tissues a heterogeneous with the being by the and and the variation in protein of for that is the of to the malignant from the samples J. analysis of endometrial and by mass PubMed Scopus Google is not for in a the of differentially expressed proteins discovered J. analysis of the proliferative and secretory of the protein and protein PubMed Scopus Google J. Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and with multidimensional liquid chromatography and tandem mass Proteome Res. PubMed Scopus Google Scholar) to proteins as the MS/MS that were more in in a complex in the search for markers a between the and the two proliferative and of the normal J. Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and with multidimensional liquid chromatography and tandem mass Proteome Res. PubMed Scopus Google and of the M. and in normal and normal proliferative and secretory samples as The by the iTRAQ reagents, in is for such a in of the that endometrial two and I in and and a II and and and a T. R. by in and of the J. PubMed Scopus Google In the between these two iTRAQ labeling in the analysis. to mass tagging is the to the samples and mass analysis. that in of proteins a of between the samples in the and not an of in or and such as the that between samples from the were in of samples the normal proliferative samples that were used as the in each of the were labeled and with each other in a of the of the of variation to for each of the as as a means of the of protein in to the in the normal proliferative samples. tissues were from an endometrial tissue samples from had in liquid of The and were by the of and samples were and The for each was using of a and of each tissue The tissue from the of the was three in of with a of protease as and J. Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and with multidimensional liquid chromatography and tandem mass Proteome Res. PubMed Scopus Google The tissue was in of with protease using a were in liquid and were and by and the protein was by a using protein of each of the samples were labeled individually with an iTRAQ were using the (Applied used two of each for labeling each and labeling were to the normal I and II cancer samples were labeled with the and The and labeled samples were in of with each one of each of in in of labeled samples was by using an with a with with of the was of the was as J. Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and with multidimensional liquid chromatography and tandem mass Proteome Res. PubMed Scopus Google each was with the in to a of and the was to with were using a the was using a was in to the was were using an an of to the in a of were by and in of The from to were by using the LC The with a were a reverse and for the in with the The used was a from LC with with or an with from The used for the was and the was as in used for in a new were a mass (Applied Foster City, in with the to a followed by MS/MS of the for the of the was to one of followed by a for a of The was to the in the that to a of The of were using the but and with a of was a of two and a of three The for each was using an by that to that to be R. The of for protein PubMed Scopus Google B. M. Aebersold R. with PubMed Scopus Google Scholar) for proteins that were to be of the results of the of protein were using the MS/MS of J. Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and with multidimensional liquid chromatography and tandem mass Proteome Res. 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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.279
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it