Abstract LB-225: Resistance to paclitaxel in triple negative breast cancer cells is associated with ABCB1 overexpression and gene amplification, and can be reversed by anti-EGFR targeting.
Bibliographic record
Abstract
Abstract Background: Due to the absence of expression of estrogen, progesterone and HER2 receptors, triple negative breast cancer (TNBC) patients do not benefit from targeted therapies. Therefore, chemotherapy remains the only treatment of choice for patients with TNBC. Despite initial clinical responses to chemotherapy, the majority of TNBC patients acquire resistance and develop progressive disease. There is little data about mechanisms of resistance to chemotherapy in TNBCs. Methods: We investigated the molecular mechanisms of acquired resistance to paclitaxel (PTX) in TNBCs. Four TNBC cell lines (BT20, SUM149, MA-MB-231 and MDA-MB-436) were cultured in the presence of increasing concentrations of paclitaxel until they acquired resistance. Gene expression and aCGH analysis were performed on all parental and resistant pairs. Results: We found a novel amplification of the ABCB1 gene in BT20 and SUM149 resistant cell lines only. Gene expression analysis revealed significant up-regulation of expression of ABCB1 and EGFR ligands in SUM149 and BT20 resistant cells compared to parental cell lines. The functional activity of ABC transporters assessed using rhodamine 123 efflux assay demonstrated a marked increase in the efflux of rhodamine in SUM149-R and BT20-R which was reversed by verapamil. We treated resistant cells with two anti-EGFR drugs, lapatinib and neratinib, which are also known ABC transporter inhibitors, and found that both drugs inhibited rhodamine 123 efflux and restored sensitivity to PTX in these PTX-resistant TNBC cells. Conclusion: This is the first report of ABCB1 gene amplification in paclitaxel resistant triple negative breast cancer cells. Our results suggest that ABCB1 gene amplification and EGFR ligand over-expression plays a critical role in the development of PTX resistance in TNBC cells, and that this resistance can be targeted by therapy with anti-EGFR agents. Thus, ABCB1 gene amplification and EGFR ligand expression may be novel predictive biomarkers for both chemotherapy and anti-EGFR therapy in TNBCs. Citation Format: Elaheh Ahmadzadeh, Ewa Przybytkowski, Adriana Aguilar-Mahecha, Mark Basik. Resistance to paclitaxel in triple negative breast cancer cells is associated with ABCB1 overexpression and gene amplification, and can be reversed by anti-EGFR targeting. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-225. doi:10.1158/1538-7445.AM2013-LB-225
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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 | 0.000 |
| 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".