Abstract A1: Clinical and biological significance of GSK-3β inactivation in breast cancer: An immunohistochemical study
Bibliographic record
Abstract
Abstract Glycogen synthase kinase 3β (GSK-3β), recently found to be functionally abnormal in various types of human disease, is negatively regulated by the PI3K/Akt signaling pathway. Since Akt is constitutively activated in a subset of breast cancer, we hypothesized that GSK-3β is inappropriately inactivated in these cases. In this study, we aimed to assess (1) the overall frequency of GSK-3β inactivation in breast cancer; (2) if there is an association between Akt activation and GSK-3β inactivation; and (3) whether there is correlation between GSK-3β inactivation and various pathologic and clinical parameters. The expression of the phosphorylated form of GSK-3β (pGSK-3β) and Akt (pAkt) were used as surrogate markers of GSK-3β inactivation and Akt activation, respectively. Immunohistochemistry applied to paraffin-embedded tissues was used to assess 72 consecutive invasive mammary carcinomas, of which 50 were estrogen receptor (ER)-positive. Overall, pGSK-3β and pAkt were positive in 34 (47.2%) and 35 (48.6%) cases, respectively. These two markers were significantly correlated with each other in the overall group and in the ER-positive subgroup (p=0.01 and 0.003, Spearman, respectively). Importantly, pGSK-3β, but not pAkt, significantly correlated a worse clinical outcome in this cohort (p=0.004, Log rank). In summary, evidence of GSK-3β inactivation was found in approximately half of the invasive mammary carcinomas. Our data suggest that this abnormality is likely attributed to Akt activation and that GSK-3β inactivation confers a worse clinical outcome. Citation Information: Clin Cancer Res 2010;16(14 Suppl):A1.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 0.001 |
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".