Pharmacogenomics of third-generation aromatase inhibitors
Bibliographic record
Abstract
INTRODUCTION: Breast cancer is a common, life-threatening disease among women. Contemporary hormonal therapy with third-generation aromatase inhibitors for estrogen-receptor-positive breast cancers in postmenopausal women is still facing the challenge of interpatient variability in therapeutic response and intensity of adverse effects. AREAS COVERED: This review highlights up-to-date literature regarding genomic findings in the literature pertaining to anastrozole, exemestane and letrozole metabolism, as well as the drug target aromatase. Genetic polymorphisms in phase I and II aromatase inhibitor metabolizing enzymes that contribute to altered responses among different patient genotypes are discussed. Similarly, aromatase CYP19A1 functional genetic polymorphisms are presented in correlation to altered aromatase activity, disease prognosis and severity of aromatase inhibitor adverse effects. EXPERT OPINION: The field of pharmacogenomics has shown remarkable progress over the last few years, notably in cancer. However, large comprehensive genotyping studies, evaluated under clinical settings, are still needed to unravel the potential impact of aromatase inhibitor pharmacogenomics on breast cancer treatment, monitoring and predicting adverse effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".