Abstract B23: Citral reduces ALDH1A3 activity in breast cancer: Potential applications in targeting breast cancer stem cells
Bibliographic record
Abstract
Abstract Breast tumors contain a subpopulation of cells known as cancer stem cells (CSCs) which are highly tumorigenic, resistant to typical chemo- and radiotherapy, and express high levels of aldehyde dehydrogenase (ALDH) isoforms ALDH1A3 and ALDH1A1. These enzymes initiate retinoic acid (RA) signaling and potentially contribute to detoxification of chemotherapy. A compound that inhibits these enzymes could be used as an adjuvant therapy to target breast CSCs and/or re-sensitize this population to chemotherapy. In particular, there are no currently characterized inhibitors of the ALDH1A3 isoform, so twelve general ALDH inhibitors were tested for their effectiveness in targeting ALDH1A3 activity. Ability to directly inhibit ALDH activity was quantified with the Aldefluor assay on a patient tumor xenograft and on breast cancer cell lines MDA-MB-231, MDA-MB-468, and SKBR3. Inhibition of RA signaling was quantified by measuring RA-inducible gene expression after 24 hours treatment with ALDH inhibitor. To investigate the anti-cancer properties of these compounds, apoptosis was quantified with the annexin V assay after 24 hours treatment. To determine if increased ALDH1A3 expression is involved in chemoresistance, MDA-MB-231 cells overexpressing ALDH1A3 and MDA-MB-468 cells with ALDH1A3 shRNA knockdown were treated for 72 hours with doxorubicin, 4-hydroperoxycyclophosphamide, or paclitaxel. Increased ALDH1A3 expression did not affect the amount of chemotherapy-induced apoptosis or cell proliferation rates. Citral significantly reduced ALDH1A3-mediated expression of RA-inducible genes and significantly reduced the ALDH activity of the patient-derived xenograft as well as ALDH1A3-overexpression MDA-MB-231 cells. Citral induced apoptosis in an ALDH1A3-dependant manner in breast cancer cell lines, and its ability to reduce MDA-MB-231 in vivo growth was investigated by implanting MDA-MB-231 cells in female NOD/SCID mice and injecting with 0.1mg/kg citral. Tumor size was not affected by citral injections, however recent data suggests that micelle-encapsulated citral has the potential to reduce tumor bulk. Should citral prove to be an effective breast cancer and ALDH1A3 inhibitor in future tumor xenograft experiments, this compound could potentially be used as adjuvant therapy for breast cancer patients. Citation Format: Margaret L. Thomas, Krysta M. Coyle, Brianne Cruickshank, Michael Giacomantonio, Melissa Wallace, Carman Giacomantonio, Paola Marcato. Citral reduces ALDH1A3 activity in breast cancer: Potential applications in targeting breast cancer stem cells. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr B23.
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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) | 0.004 | 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".