Abstract A019: Discovery of a potent and brain-penetrable tubulin inhibitor SB-216 that shows efficacy in primary tumor growth and brain metastasis
Bibliographic record
Abstract
Abstract A major clinical challenge in cancer treatment is to prevent and treat metastatic disease. Despite the significant advancements in targeted therapy and immunotherapy, chemotherapeutic drugs, including taxanes, remain one of the mainline systemic treatment options for several major cancer types. However, the prolonged use of taxanes has been associated with the development of multidrug resistance, dose-limiting hematopoietic toxicity, and neurotoxicity, frequently presenting as persistent peripheral neuropathy. In addition, these drugs have limited blood-brain barrier penetration, and thus they are not effective in treating brain tumors or brain metastases from other cancer types, particularly breast cancer metastases. We have developed a new generation of tubulin inhibitors, termed colchicine binding site inhibitors (CBSIs). Unlike taxanes, these compounds bind to the colchicine site in tubulin, structurally less complex than taxanes which enables fine-tuning of physical-chemical properties, and shows the ability to overcome acquired drug resistance to existing taxane drugs. One of the best inhibitors in this class of compounds is SB-216. We have solved the high-resolution crystal structure of SB-216 in a complex with tubulin protein (PDB: 6X1F) and confirmed its mode of action. Extensive preclinical evaluations of SB-216 in a number of tumor models, including taxane-resistant prostate cancer, melanoma, ovarian cancer, and triple-negative breast cancer, indicated that SB-216 is highly potent in suppressing both primary tumor growth and tumor metastases. Importantly, SB-216 shows high brain penetration and shows efficacy in suppressing brain metastases from triple-negative breast cancer. SB-216 also has good drug-like properties and shows strong promise as a new generation of tubulin inhibitor for systemic cancer treatments, not only in brain metastasis from non-CNS tumors but also potentially be useful for brain tumors such as glioma. The work is supported by NIH/NCI grants R01CA14876 and R01CA276152 and the DoD grant HT9425-23-1-0216. Citation Format: Kelli L. Adeleye, Satyanarayana Pochampally, Raisa Krutilina, Rui Wang, Junming Yue, Tiffany Seagroves, Duane D.Miller, Wei Li. Discovery of a potent and brain-penetrable tubulin inhibitor SB-216 that shows efficacy in primary tumor growth and brain metastasis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr A019.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.002 | 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".