Abstract 3976: Antihistamines as synergists with targeted therapies in chronic lymphocytic leukemia
Bibliographic record
Abstract
Abstract Chronic Lymphocytic Leukemia (CLL) is a B-cell derived cancer and is the most commonly diagnosed leukemia in older adults. Several survival signals contribute to the accumulation of CLL cells including constitutive activation the B-cell receptor (BCR) signaling pathway. Approved treatments for CLL are nucleoside analogs such as Fludarabine, alkylating agents including Chlorambucil and Bendamustine, and targeted therapies inhibiting BCR-associated kinases such as Ibrutinib and Idelalisib. Unfortunately, CLL remains incurable, but other weaknesses of the disease have been identified. Recent studies have shown CLL cells to be sensitive to lysosomal membrane permeabilization (LMP) and release of lysosomal contents due to altered sphingosine metabolism. Drugs that induce LMP are referred to as lysosomotropic agents and include antidepressants and antimalarials. These drugs accumulate in lysosomes and inhibit enzymes in the sphingolipid metabolic pathway, causing lysosomal membrane damage. Effectors are released from lysosomes including cathepsin proteases and reactive oxygen species (ROS), which cause dysfunction in cellular machinery and cell death via apoptosis. Our data indicates that kinase inhibitors induce synergic death when combined with lysosomotropic agents in vitro in many cancer models. A non-small cell lung cancer study showed that antihistamines acted as lysosomotropic agents, and were correlated with better patient outcomes when combined with chemotherapy. Therefore, the objective of this study is to characterize the cytotoxicity of antihistamines in B-cell cancer models and identify synergistic interactions with clinically relevant drugs used in CLL. We have shown that three commonly prescribed over-the-counter antihistamines, Desloratadine, Loratadine and Clemastine, induce cell death at concentrations that are clinically achievable in the B-cell lines BJAB and I83, as well as CLL patient derived primary lymphocytes. Each antihistamine caused synergic cell death in combination treatments with Ibrutinib and Idelalisib, but not Fludarabine, Chlorambucil or Bendamustine, which may indicate that the synergy is specific to kinase inhibitors. In addition, the treatment with antihistamines was shown to induce cell death at significantly lower concentrations in primary CLL cells compared to normal lymphocytes from age-matched donors. Both the antihistamine-induced cell death and combination treatments depend on intracellular soluble ROS, but the main effectors of the apoptotic pathways remain to be determined. Taken together, this study intends to exploit the vulnerabilities of CLL by repurposing allergy drugs in combination with kinase inhibitors already available for treating CLL patients. Citation Format: Aaron P. Chanas-LaRue, James B. Johnston, Spencer B. Gibson. Antihistamines as synergists with targeted therapies in chronic lymphocytic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3976.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".