P5-12-03: An Innovative Quantification Method for Tamoxifen and Three Metabolites in Formalin-Fixed Paraffin-Embedded Tissues by Liquid Chromatography and Tandem Mass Spectrometry.
Bibliographic record
Abstract
Abstract Background Tamoxifen (TAM) has been commonly used as a selective estrogen receptor modulator for the treatment and prevention of breast cancer. Although this drug is effective in many patients, some develop resistant and eventually relapse. Recent studies suggest that the cancer recurrence could possibly be due to changes in drug metabolism. TAM is metabolized by the cytochrome P450 enzyme pathway into several metabolites including 4-hydroxy-tamoxifen (4-OH), N-desmethyl-tamoxifen (DMT) and N-desmethyl-4-hydroxy-tamoxifen (endoxifen). These metabolites have variable potencies in suppressing estrogen-dependent breast cancer. Differences in metabolism may contribute to the clinical inter-individual variability in TAM response. The aim of our study was to provide a comprehensive evaluation of TAM and its metabolites through quantitative measurement in breast cancer patients to help better understand the pharmacological effects of TAM therapy. In the past, most methods used to measure the levels of TAM and its metabolites were in plasma or fresh/frozen tissue samples. These samples are typically not available retrospectively, and their long-term storage is expensive and laborious. Methods: We therefore explored the possibility to utilize formalin-fixed and paraffin-embedded (FFPE) tissues archived post breast surgery for quantification of TAM and its metabolites. Our laboratory has developed a rapid, sensitive and specific analytical method using liquid chromatography and tandem mass spectrometry (LC-MS/MS) for the measurement of TAM and its metabolites in FFPE tissues. The FFPE tissues were thin sectioned and deparaffinized by incubating twice with xylene for 10 min at room temperature. Sample clean-up was carried out subsequently using C2 solid-phase extraction, and detection was performed in the multiple-reaction monitoring mode with a triple quadrupole mass spectrometer. This method allows simultaneous quantification of TAM and three metabolites in FFPE tissues with a run time of 12 min. Results: The assay had good inter- and intra-assay precisions (2-6 %CV), and was linear over the range of 0.01-5 ng/g for 4-OH and endoxifen, and 0.1-50 ng/g for TAM and DMT. The extraction recoveries were between 83–88%. The validated method was successfully applied to analyze the FFPE tissues obtained from two groups of breast cancer patients. Patients were categorized into those with tumor recurrence (R) and those without recurrence (NR) after at least 2 months of 20 mg/d TAM treatment. Levels of TAM, 4-OH, DMT and endoxifen in FFPE tissues were compared between the two groups. Our preliminary data show that the ratio of DMT/TAM was significantly higher in the R (6.7, n = 13) than the NR patients (14.2, n = 9) (p<0.05). Discussion: The assay described here not only allows accurate quantification of TAM and metabolites in FFPE tissues, but also opens up an incredible opportunity and new challenges for researchers to excavate precious information from FFPE tissues, especially when these archival samples represent the only source of biomaterial available. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P5-12-03.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".