Association of HER2 Ile655Val and Ala1170Pro polymorphisms with breast cancer prognosis factors
Bibliographic record
Abstract
The human epidermal growth factor receptor‐2 (HER2) overexpression occurs in about 15% of human breast cancers and is a marker of poor survival. However, it is unclear if common HER2 polymorphisms are associated with breast cancer prognosis factors. This study aimed to evaluate the association between HER2 polymorphisms and breast cancer prognostic factors in non‐metastatic HER2‐positive breast cancer patients. Among 73 women, HER2 polymorphisms (Ile655Val and Ala1170Pro) were assessed using TaqMan assays in normal and tumor breast tissues. In normal breast tissue, the variant allele 1170Pro was associated with younger age ( P =0.007) and the presence of lymphovascular invasion ( P =0.06). Similar associations were observed when polymorphism was assessed in tumor breast tissue. No association was found between Ile655Val polymorphism and breast cancer prognostic factors. However, we observed a difference of Ile655Val or Ala1170Pro genotyping between normal and tumor breast tissues ( P =0.03 and P =0.01, respectively). These preliminary results suggest that HER2 Ile655Val and Ala1170Pro polymorphisms may play a role in breast carcinogenesis, but only Ala1170Pro polymorphism is associated with breast cancer prognostic factors in non‐metastatic HER2‐positive breast cancer patients.
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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) | 0.002 | 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".