Abstract 5228: Small molecule activation of the LKB1 tumor suppressor
Bibliographic record
Abstract
Abstract Cancer treatment has been considerably advanced by the relatively recent development of small molecules capable of inhibiting oncogenic kinase signaling, but exogenous enhancement of tumor suppressive signaling remains elusive. Here, we sought to design small molecules capable of activating the tumor suppressor kinase LKB1. Designing compounds capable of increasing kinase activity has been more structurally challenging than those aimed at inhibiting them: apart from the ATP-binding pocket, there is rarely a site that would be conducive to binding a small molecule. Unlike most protein kinases, LKB1 signals as part of an obligate trimer consisting of itself, a scaffolding protein (MO25), and a pseudokinase (STRAD). As part of its mechanism of activation, LKB1 must bind to an ATP-bound STRAD to take on its active kinase conformation. Targeting STRAD provides a unique opportunity to allosterically stabilize and enhance LKB1 kinase activity. Using a structure-based drug design, we developed compounds that are able to selectively bind STRAD's ATP-binding pocket. We confirmed that our STRAD targeting small molecules are able to enhance the activity of recombinant LKB1 in a kinase assay. The observed increase in LKB1's kinase activity corresponds to increased association of complex components after drug treatment, as suggested by immunoprecipitation of the trimer. To understand the clinical contexts in which our compounds might be most effective, we performed a viability screen across multiple histologies to determine which cancer cells could be sensitive to LKB1 activation. Sensitive cells were used to investigate the mechanism of action of exogenous LKB1 stimulation. LKB1 signals through members of the AMPK-related kinase family to carry out its tumor suppressive functions in the cell. Thus, we used western blot analysis of LKB1 proximal and distal mediators to assess changes in downstream signaling. We found that activation of multiple LKB1 effectors was dose dependent and occurred rapidly, with signal enhancement seen in more tumor-relevant low adherence cell culture conditions. Real-time microscopy confirmed that our compounds slowed cell proliferation in a dose-dependent manner. This work demonstrates that targeting a pseudokinase with a small molecule to allosterically activate of a tumor suppressor kinase is possible, therapeutically effective in vitro, and triggers multiple downstream signaling pathways to decrease cancer cell proliferation. Citation Format: Dominique C. Mitchell, Jin Liu, Zheng Wang, Changliang He, Luo Ding, Marc Adler, LeeAnn L. Wang, Aidan Keith, Y. Christina Hwang, Tsz Kin M. Tsui, Roopa Ramamoorthi, Sarah Lively, Robert A. Drakas, Vijay Ramani, Kliment A. Verba, Tingting Qing, Richard T. Beresis, John D. Gordan. Small molecule activation of the LKB1 tumor suppressor [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5228.
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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) | 0.003 | 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".