Abstract 5396: Characterization of small molecule inhibitors of the PIM kinases in <i>in vitro</i> models of hematological malignancies
Bibliographic record
Abstract
Abstract The three members of the Pim kinase family, Pim-1, -2, and -3, are established oncogenes and are attractive targets in hematological malignancies. We have developed multiple potent and selective scaffolds of pan-Pim inhibitors with picomolar enzymatic potency and nanomolar cellular potency. Using these agents, we have observed that the abolishment of Pim activity impairs tumor cell viability in multiple settings, both in vitro and in vivo. We have developed numerous assays to measure Pim protein levels and activity, including Pim downstream markers p-PDCD4 and p-BAD, that might be broadly applicable to human tissues. These assays have allowed us to establish a correlation between Pim protein levels and sensitivity to Pim inhibition across multiple tumor settings, in vitro. We have observed that all tested multiple myeloma (MM) cell lines express high levels of Pim-2 protein and that pan-Pim inhibition impairs viability in 90% of these lines and induces apoptosis in a subset. In acute myelogenous leukemia (AML) cell lines, sensitivity to Pim inhibition significantly correlates with Pim-1 protein expression. Numerous diffuse, large B-cell lymphoma (DLBCL) cell lines have high Pim levels and many are sensitive to Pim inhibition. We have also assessed Pim expression and activity in human tumor and normal tissues. Studies performed with myeloma cells isolated from patient bone marrow aspirates have revealed elevated Pim-2 protein levels as well as sensitivity to ex vivo dosing with Pim inhibitors, as evidenced by inhibition of PDCD4 phosphorylation. Primary patient samples from numerous other hematological tumors have also been found to have high Pim-1 or Pim-2 protein levels. To expand the possible utility of Pim inhibitors in the clinic, we have combined our molecules with numerous clinical agents, including dexamethasone, carfilzomib, and PI3K inhibitors, across multiple settings, in vitro. In all indications surveyed, we have observed that the combination of Pim molecules and these agents can lead to synergistic effects on cell viability, apoptosis and pathway signaling. In some cases, cell lines that show mild or no response to either single agent alone are sensitive to combination treatment. Collectively, our data provide a rationale for the development of Pim kinase inhibitors for use either as monotherapy or in combination with other agents in diverse tumor settings. Citation Format: Christine E. Sastri, Nadia Guerrero, Dongyin Yu, Bethany Mattson, Ken Dellamaggiore, Yajing Yang, Paul Hughes, Hui-Ling Wang, Victor Cee, Brian A. Lanman, Liping Pettus, Anthony B. Reed, Bin Wu, Ryan Wurz, Andrew Tasker, Li-Ya Huang, Daniel Branstetter, Karen Rex, Jeffrey Winston, Teresa L. Burgess, Richard Kendall, J Russell Lipford. Characterization of small molecule inhibitors of the PIM kinases in in vitro models of hematological malignancies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5396. doi:10.1158/1538-7445.AM2015-5396
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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) | 0.001 | 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".