Verification of Endometrial Tissue Biomarkers Previously Discovered Using Mass Spectrometry-Based Proteomics by Means of Immunohistochemistry in a Tissue Microarray Format
Bibliographic record
Abstract
Verification of candidate protein biomarkers is a necessary step in moving from the initial discovery to application. Here, we report results of a verification exercise involving six candidate endometrial cancer biomarkers previously discovered using mass-tagging and multidimensional liquid chromatography/tandem mass spectrometry (DeSouza L., et al. J. Proteome Res. 2005, 4, 377-386) on a cohort of 148 patient samples by means of immunohistochemistry on a tissue microarray format. A panel of the three best-performing biomarkers, chaperonin 10, pyruvate kinase M2, and alpha-1-antitrypsin, achieved a sensitivity of 0.85, specificity of 0.93, predictive value of 0.90, and positive predictive value of 0.88 in discriminating malignant from benign endometrium. The ruggedness of this panel of biomarkers was verified in a 2/3-training-set-1/3-test-set cross-validation analysis by randomly splitting the cohort in 10 ways. The roles of chaperonin 10 and pyruvate kinase M2 in tumorigenesis confirm them as credible cancer biomarkers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".