Abstract PO-62: Overcoming venetoclax resistance in B-cell malignancies by antagonism of stromal TGF-beta-mediated drug resistance
Bibliographic record
Abstract
Abstract Novel targeted therapies have substantially improved the prognosis of patients with B-cell malignancies. However, a substantial fraction of patients relapse, even after initially achieving deep remissions. Many studies have characterized the interactions between tumor cells and their microenvironment as integral to leukemia/lymphoma homeostasis and for the provision of survival signals, also contributing to drug resistance (referred to as environment-mediated drug resistance [EMDR]). Therapeutic efforts to antagonize microenvironment-emanating survival cues have predominantly focused on perturbation of tumor cell adhesion enabling the physical displacement from protective niches. In an effort to address whether direct stromal targeting could more precisely mitigate EMDR, we antagonized stromal expressed PKC-beta, which we have previously shown to be a stroma-autonomous signaling pathway critical for the survival of malignant B cells (Lutzny et al., Cancer Cell 2013). The dependency on stroma PKC-b was uniformly found for acute (ALL) and chronic (CLL, MCL) B-cell malignancies. In particular, our data demonstrate that stroma PKC-b is of key importance for multidrug resistance of malignant B cells (Park et al., Science Trans Med 2020). Here we demonstrate novel mechanistic insights into stroma-mediated drug resistance in B-cell malignancies. We identified that stroma PKC-b drives a transcriptional program, activating TGF-b and BMP-signaling in tumor cells. Our data show that antagonizing stroma signals with TGF-b inhibitors abrogated upregulation of BCL-XL and overcomes stroma-dependent resistance to venetoclax. This activation operates in parallel to the activation of the transcription factor EB (TFEB) as a downstream target of PKC-b. Interference with these signaling pathways impairs plasma membrane integrity of MSCs by downregulation of numerous adhesion and signaling molecules (e.g., ADAM17), required for the reciprocal stabilization of BCL-XL in tumor cells. The significance of microenvironment PKC-b for drug resistance was demonstrated in vivo, using C57B/6 mice, diseased with EuTCL-1 driven B-cell tumors and treated with venetoclax in combination with or without enzastaurin (PKC-b inhibitor). Combined treatment significantly prolonged survival, based on PKC-b mediated impairment of lysosome biogenesis in vivo. Similarly, concurrent treatment of PKC-b inhibitors with chemotherapy also improved survival in an ALL-PDx model. Our data demonstrate that mitigating EMDR with small-molecule inhibitors of PKC-b or TGF-b signaling enhances the effectiveness of both targeted and nontargeted chemotherapies and, moreover, has the ability to overcome venetoclax resistance in B-cell malignancies in vivo. A clinical trial to test the dual inhibition of stroma and tumor cells in lymphoma patients is in preparation. Citation Format: Eugene Park, Jingyu Chen, Andrew Moore, Maurizio Mangolini, Joseph R. Byod, Hilde Schjerven, James C. Williamson, Paul J. Lehner, Michael Leitges, Alexander Egle, Marc Schmidt-Supprian, Seth Frietze, Ingo Ringshausen. Overcoming venetoclax resistance in B-cell malignancies by antagonism of stromal TGF-beta-mediated drug resistance [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr PO-62.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".