O76: SERUM JAM-A AS A PREDICTOR OF TREATMENT RESISTANCE IN BREAST CANCER PATIENTS
Bibliographic record
Abstract
Abstract Introduction Junctional Adhesion Molecule-A (JAM-A) has important physiological functions in epithelial and endothelial barriers, but its overexpression has also been linked with tumour progression and poor prognosis in various malignancies. Since JAM-A can be enzymatically cleaved (cJAM-A) and has been detected in the bloodstream, we hypothesized that cJAM-A shed from tumours overexpressing JAM-A may represent a possible predictor of treatment resistance in breast cancer. Method An assay was optimised to detect cJAM-A in serum/plasma. Samples were obtained from HER2-positive breast cancer patients (n=20) in Beaumont Hospital. Independently, serial samples were obtained from a Canadian cohort of locally advanced breast cancer (LABC) patients (n=53). Result Serum cJAM-A levels in therapy-resistant patients was significantly higher than those in treatment-sensitive patients (p<0.05) in an Irish cohort of HER2 positive patients. In a diverse international cohort of LABC patients, the development of metastatic disease was associated with higher levels of cJAM-A (p<0.05) as well as shorter time to progression (p<0.05). Conclusion Our data suggest that cJAM-A merits further investigation as a novel biomarker enabling prospective identification of patients at greatest risk of developing therapeutic resistance. Take-home message Our data suggest that cJAM-A merits further investigation as a novel biomarker enabling prospective identification of patients at greatest risk of developing therapeutic resistance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".