Abstract 743: Assessment of novel tyrosine-chlorambucil hybrid molecules on a panel of breast, ovarian, and uterine cancer cell lines
Bibliographic record
Abstract
Abstract Site-specific drug targeting is the suject of very intense research to improve selectivity and therapeutic index towards breast and gynecological (ovarian and endometrial) cancers. Recently, our group have designed and synthesized a new class of amino acid-linked nitrogen mustard hybrids. The new hybrids are designed to mimic 17β-estradiol in order to target ERα-overexpressing tumor cells. For this purpose, tyrosine was used as the starting material to which chlorambucil was added to construct several tyrosine-chlorambucil hybrids. The phenol group of the tyrosine moiety imitates the phenol group of estradiol. Thus, the new hybrids are designed to target the estrogen receptor and to direct the cytotoxic moiety to hormone-dependent cancer cells. Chlorambucil is a slow acting nitrogen mustard mainly used in chronic lymphocytic leukemia and primary macroglobulinemia. It is also useful in treating lymphosarcoma and Hodgkin's disease. Two different families of hybrids were made. The aim of the study was to determine the cytotoxic effects of these unique molecules using estrogen dependent (ER+; Ishikawa, Ovcar-3, MCF-7, ZR-75-1) and independent (ER-; Hec-1A, A2780, MDA-MB-468) human breast, ovarian and uterine cancer cells. The results show the possible interactions of the two families of hybrids with ERα as demonstrated by molecular modeling. The biological activity of these compounds was evaluated in vitro using the MTT cell proliferation assay. Depending of the different hybrids tested the novel compounds generally possess up to 10 time higher biological activities when compared to the parent drug. Given the significant cytotoxic activity of these original tyrosine-chlorambucil hybrids, we believe that they represent a promising alternative treatment for hormone-dependent female cancers. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 743.
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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) | 0.001 | 0.000 |
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".