HE4 Transcription- and Splice Variants-Specific Expression in Endometrial Cancer and Correlation with Patient Survival
Bibliographic record
Abstract
We investigated the HE4 variant-specific expression patterns in various normal tissues as well as in normal and malignant endometrial tissues. The relationships between mRNA variants and age, body weight, or survival are analyzed. ICAT-labeled normal and endometrial cancer (EC) tissues were analyzed with multidimensional liquid chromatography followed by tandem mass spectrometry. Levels of HE4 mRNA variants were measured by real-time PCR. Mean mRNA levels were compared among 16 normal endometrial samples, 14 grade 1 and 14 grade 3 endometrioid EC, 15 papillary serous EC, and 14 normal human tissue samples. The relationship between levels of HE4 variants and EC patient characteristics was analyzed with the use of Pearson correlation test. We found that, although all five HE4 mRNA variants are detectable in normal tissue samples, their expression is highly tissue-specific, with epididymis, trachea, breast and endometrium containing the highest levels. HE4-V0, -V1, and -V3 are the most abundant variants in both normal and malignant tissues. All variants are significantly increased in both endometrioid and papillary serous EC, with higher levels observed in grade 3 endometrioid EC. In the EC group, HE4-V1, -V3, and -V4 levels inversely correlate with EC patient survival, whereas HE4-V0 levels positively correlate with age. HE4 variants exhibit tissue-specific expression, suggesting that each variant may exert distinct functions in normal and malignant cells. HE4 levels appear to correlate with EC patient survival in a variant-specific manner. When using HE4 as a biomarker for EC management, the effects of age should be considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".