Abstract 4683: Verapamil and tamoxifen modulate ABCB1 expression in multidrug-resistant cells and resensitize them to conventional chemotherapy
Bibliographic record
Abstract
Abstract Multidrug-resistant (MDR) tumors are an increasingly important obstacle in cancer treatment, wherein many cases are associated with the overexpression of P-glycoprotein 1 (P-gp1, ABCB1). Previous efforts to sensitize ABCB1-expressing tumor cells to anti-cancer drugs were associated with severe side effects, so interest in clinical trials using these drugs has dwindled. Studies have shown P-glycoprotein-overexpressing cells to be hyper sensitive (or collaterally sensitive) to a diverse group of non-toxic compounds. Given earlier results demonstrating a significant increase in ABCB1 expression post-chemotherapeutic treatment of cancer patients (e.g., breast, ovarian, myeloma, and acute myeloid leukemia), and the role of ABCB1 in drug resistance, it was determined that targeting ABCB1-expressing tumor cells with effective collateral sensitivity drugs should increase the effectiveness of current chemotherapeutic treatments. In this report, it was of interest to determine the effect of the collateral sensitivity drugs verapamil and tamoxifen on P-glycoprotein 1 expression at the level of cells and individual cell clones. Clones from P-gp1-overexpressing Chinese hamster ovarian cell lines (CHRC5) or triple negative breast cancer cells (MDA-MB-231/400 nM doxo) were treated with varying levels of collateral sensitivity drugs and ABCB1 expression was determined by Western blots and ELISAs. The sensitivity of each cell clone to anti-cancer or collateral sensitivity drugs was determined using cytotoxicity assays. Our results demonstrate a drop in ABCB1 expression in each clone, together with decreased collateral sensitivity and overall increased sensitivity to anti-cancer drugs in cell lines selected with verapamil and tamoxifen. Work is in progress to study the various mechanisms responsible for this drop in ABCB1 expression and its impact on treatment outcome. Citation Format: Georgia Limniatis, Elias Georges. Verapamil and tamoxifen modulate ABCB1 expression in multidrug-resistant cells and resensitize them to conventional chemotherapy. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4683.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".