Gene Expression Analyses of HER-2/neu and ESR1 in Patients with Breast Cancer
Bibliographic record
Abstract
Background: Her-2 and ESR1 genes, that interact in the cell signaling pathway, are the most important molecular markers of breast cancer, which have been amplified or overexpressed in 30% and 70%, respectively. This study was performed to evaluate the gene expression levels of Her-2 and ESR1 genes in tumor cells and its adjacent normal tissue of breast cancer patients and compared them whit clinical-pathological features. Methods: In total, 80 tissue specimens from 40 patients, with an average age of 48.47 years, were examined by Real-time PCR technique, and ultimately evaluated the expression level of Her-2 and ESR1genes. The data were analyzed by REST 2009 V2.0.13 statistical software. Results: HER2 and ESR1 overexpression was identified in 19 (48%) and 12 (30%) of 40 patients respectively, which was higher and lower than that recorded in international statistics, respectively. ESR1 overexpression was associated with Stage 3A and lymph node involvement 2 (N2) (P = 0.04 and P = 0.047, respectively). No significant correlation was observed between the expression of HER2 and ESR1 and other clinical-pathological features, however, the relative differences were identified in the expression levels of genes between main group and groups that were classified according to the clinical-pathological features and age. Conclusions: Overexpression of Her-2 and ESR1 genes in the patients of our study are higher and lower than international statistics, respectively, indicating the differences in genetic, environmental and ethnic factors that involved in the developing of breast cancer.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".