Abstract A188: Diazonamide DZ 2384, a potential therapeutic for pancreatic cancer, binds to tubulin with a unique impact on microtubule dynamics and tubulin curvature
Bibliographic record
Abstract
Abstract Microtubules are critical for cell proliferation, cellular invasion, migration and trafficking. As such, anti-mitotic tubulin binding agents continue to be a cornerstone of adjuvant chemotherapies across many different tumor indications. A major challenge in the development of new anti-tubulin agents is to overcome toxicities associated with targeting microtubule dynamics while maintaining a high degree of anti-cancer potency. Diazonamide A is a natural product isolated from Diazona angulata, which has previously been shown to block cell division at mitosis but with an unusual safety profile compared to other anti-mitotics. DZ 2384 is a novel and more potent synthetic analog of diazonamide A. In an unbiased functional genomics, biochemical and high resolution structure approach to determine its cellular target, we found that DZ 2384 binds in the vinca domain of tubulin but imparts distinct effects on microtubule dynamics compared to vinorelbine that targets the same site. DZ 2384 and vinorelbine both inhibit the growth rate of microtubules; however, DZ 2384 also increases the rescue frequency while vinorelbine decreases the growth length of microtubules increasing the time spent in a paused or attenuated state. These dynamic characteristics are consistent with the observations that the microtubule network is preserved in interphase cells and in primary cortical neurons treated with DZ 2384 compared to vinorelbine. X-ray crystallography and electron microscopy studies demonstrate that DZ 2384 causes a straightening of curved protofilaments, an effect that has not been observed for other vinca-domain binders so far, and which may account for the observed differences in microtubule dynamics and toxicity of this class of compounds. DZ 2384 has potent anti-tumor activity in xenograft models of pancreatic and colon cancer and a higher therapeutic window than vinorelbine considering body weight, blood chemistry, hematology and bone marrow. DZ 2384 was also tested in a KrasG12D-driven genetically engineered murine model of pancreatic ductal adenocarcinoma that carries a Rgs16::GFP reporter transgene to enable tumor burden quantitation. In this model, DZ 2384 demonstrates strong antitumor activity in combination with gemcitabine; comparable with or better than that of gemcitabine + Abraxane on developing pancreatic tumors. DZ 2384 also reduces new tumor formation in this model. Taken together, DZ 2384 represents a novel class of microtubule-targeting agents that operates with a distinct mechanistic impact on microtubule dynamics and structure. We propose DZ 2384 as a promising new agent for the treatment of pancreatic ductal adenocarcinoma. Citation Format: Michal Wieczorek, Joseph Tcherkezian, Cynthia Bernier, Ozhan Ocal, Sami Chabaan, Yanneve Rolland, Claude Godbout, Mark Hancock, Cecilia Rocha, Natacha Olieric, Andrea E. Prota, Michel O. Steinmetz, Thomas M. Wilkie, Rolf A. Brekken, Hui Ding, Patrick Harran, Gordon C. Shore, Gary Brouhard, Anne Roulston. Diazonamide DZ 2384, a potential therapeutic for pancreatic cancer, binds to tubulin with a unique impact on microtubule dynamics and tubulin curvature. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A188.
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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) | 0.006 | 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".