Influence of <i>ABCB1</i> and <i>ABCG2</i> polymorphisms on doxorubicin disposition in Asian breast cancer patients
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Bibliographic record
Abstract
The influence of three high frequency ABCB1 polymorphisms (c.1236C>T, c.2677G>A/T, and c.3435C>T) and the ABCG2 c.421C>A polymorphism on the disposition of doxorubicin in Asian breast cancer patients receiving adjuvant chemotherapy was investigated in the present study. The allelic frequency of the ABCB1 c.1236T, c.2677T, c.2677A, and c.3435T variants were 60%, 38%, 7%, and 22%, respectively, and the frequency of the ABCG2 c.421A allele was 23%. Pairwise analysis showed increased exposure levels to doxorubicin in patients harboring at least one ABCB1 c.1236T allele (P = 0.03). Patients homozygous for the CC-GG-CC genotype had significantly lower doxorubicin exposure levels compared to the patients who had CT-GT-CT (P = 0.02) and TT-TT-TT genotypes (P = 0.03). Significantly increased clearance of doxorubicin was also observed in patients harboring CC-GG-CC genotypes when compared to patients harboring the CT-GT-CT genotype (P = 0.01). Patients harboring the CC-GG-CC genotypes had significantly lower peak plasma concentrations of doxorubicinol compared to patients who had TT-TT-TT genotypes (P = 0.03). No significant influences on doxorubicin pharmacokinetic parameters were observed in relation to the ABCG2 c.421C>A polymorphism. In conclusion, the present exploratory study suggests that the three high frequency linked polymorphisms in the ABCB1 gene might be functionally important with regards to the altered pharmacokinetics of doxorubicin in Asian breast cancer patients, resulting in significantly increased exposure levels and reduced clearance.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it