Abstract 3247: Discovery of a novel drug that affects centrosome clustering
Bibliographic record
Abstract
Abstract Our goal is to identify molecular regulators of a mechanism that occurs uniquely in cancer cells, and to develop a selective anti-cancer drug. Most chemotherapies are non-selective, causing severe side-effects. In additions, cancers often develop resistance to some of the more commonly used chemotherapies. To expand the repertoire of available drugs, and to design drugs that are selective, we need to identify molecules that regulate the physiological changes that occur primarily in cancer cells. For example, cancer cells in many hard-to-treat cancers have aberrant centrosomes, which may be supernumerary or fragmented. During mitosis, these aberrant centrosomes must cluster to form bipolar spindles for successful division. Thus, targeting a process like centrosome clustering is ideal, since it is not necessary in healthy cells. We synthesized a small, stable scaffold with amenability to structure-activity-relationship studies, and found several analogues with IC50 values < 50 nM, depending on the cancer cell line. Preliminary tests showed that these compounds prevent tumors from forming and/or cause their regression in vitro. We performed cell biological studies to characterize their mechanism of action. In several different types of cancer cells, these compounds cause mitotic arrest and centrosome declustering at concentrations where they have little affect on non-cancerous cells. Live imaging revealed that within minutes of adding the compounds to HeLa cells expressing GFP-tagged tubulin, we observed rapid microtubule depolymerization and centrosome declustering. After washing out the compound, microtubule polymerization recovered, but the mitotic spindles were multipolar. Adding similar concentrations of Nocodazole, a microtubule-depolymerizing drug, also caused rapid microtubule depolymerization, but after washing out the drug, the spindles were bipolar. We are in the process of identifying the molecular target of these compounds to provide crucial insight to the mechanism governing centrosome clustering, and are continuing to perform SAR studies to obtain compounds with higher efficacy and selectivity. Citation Format: Dilan B. Jaunky, Kevin Larocque, Javier Porro Suardiaz, Dan Yang, Emma J. Furze, Pat Forgione, Alisa Piekny. Discovery of a novel drug that affects centrosome clustering [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3247. doi:10.1158/1538-7445.AM2017-3247
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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 | 0.001 | 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".