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Record W2115701133 · doi:10.1021/pr800312m

Multiple Reaction Monitoring of mTRAQ-Labeled Peptides Enables Absolute Quantification of Endogenous Levels of a Potential Cancer Marker in Cancerous and Normal Endometrial Tissues

2008· article· en· W2115701133 on OpenAlex
Leroi V. DeSouza, Adrian M. Taylor, Wěi Li, Marjorie Sue Minkoff, Alexander D. Romaschin, Terence J. Colgan, K. W. Michael Siu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Proteome Research · 2008
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsQuantitative proteomicsChemistryPyruvate kinaseComputational biologyCancerSelected reaction monitoringProteomicsBiochemistryBiologyChromatographyEnzymeMass spectrometryTandem mass spectrometryGlycolysisGenetics

Abstract

fetched live from OpenAlex

While iTRAQ analyses have proved invaluable for the discovery of potential cancer markers, two outstanding issues that remained were its ineffectiveness to consistently detect specific proteins of interest in a complex sample and to determine the absolute abundance of those proteins. These have been addressed by availability of the mTRAQ reagents (Applied Biosystems, Inc., Foster City, CA) a nonisobaric variant of iTRAQ. We have applied this newly emerging technique to quantify one of our potential markers for endometrial cancer, viz. pyruvate kinase M1/M2. The mTRAQ methodolgy relies on multiple reaction monitoring (MRM) to target tryptic peptides from the protein of interest, thus, ensuring maximal opportunity for detection, while the nonisobaric tags enable specific quantification of each version of the labeled peptides through unique MRM transitions conferred by the labels. Known amounts of synthetic peptides tagged with one of the two available mTRAQ labels, when used as quantification standards in a mixture with the oppositely labeled tryptically digested sample, permit determination of the absolute amounts of the corresponding protein in the sample. The ability to label the sample and reference peptides with either one of the two possible combinations is an inherent advantage of this method, as it provides a means for verification of the reported ratios. In this study, we determined that the amount of pyruvate kinase present in the homogenate from a biopsied EmCa tissue sample was 85 nmol/g of total proteins, while the equivalent concentration in the nonmalignant controls was 21-26 nmol/g of total proteins. This approximately 4-fold higher amount of pyruvate kinase in the cancer sample was further confirmed not only by a direct comparison between the cancer sample and one of the nonmalignant controls, but also independently by an enzyme-linked immunosorbant assay (ELISA). Additionally, the 4-fold higher level of pyruvate kinase amount in the cancer homogenate reported in this study is considerably higher than the 2-fold higher ratio reported across 20 cancer samples in the discovery phase with the iTRAQ technique, suggesting that there exists a possibility that the dynamic range of ratios determined by the iTRAQ technique may have been compressed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 categoriesnone
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 score0.022
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.152
GPT teacher head0.387
Teacher spread0.235 · 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