Abstract 196: Targeting breast cancer stem cells with a panel of potential ALDH1A3 inhibitors
Bibliographic record
Abstract
Abstract Aldehyde dehydrogenase (ALDH) isoform ALDH1A3 is selectively expressed in breast cancer stem cells (CSCs) and is a key mediator in breast cancer progression via initiation of retinoic acid (RA) signaling and expression of RA-inducible genes. Expression of ALDH1A3 and its induced RA-inducible genes are associated with less favorable patient outcomes. This suggests that ALDH1A3 represents a novel anti-breast cancer therapeutic target. To target the specific ALDH1A3 isoform, a panel of general ALDH inhibitors was attained and the compounds’ effectiveness in targeting ALDH1A3 activity was quantified by their ability to decrease expression of the downstream genes retinoic acid receptor beta (RARβ) and retinoic acid receptor responder protein 1 (RARRES1). Eleven compounds were tested in total, and the essential oil citral was shown to significantly decrease ALDH1A3-mediated expression of both RA-inducible genes in a dose dependent manner. Citral is already used in cosmetics and food additives and recent work shows that it can induce apoptosis of breast cancer cells making it a promising therapeutic agent and a potential subject of a future xenograft study in mice to determine its effects on CSCs in vivo. Citation Format: Margaret L. Thomas, Melissa Wallace, Carman Giacomantonio, Paola Marcato. Targeting breast cancer stem cells with a panel of potential ALDH1A3 inhibitors. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 196. doi:10.1158/1538-7445.AM2014-196
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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) | 0.008 | 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".