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Record W2886701506 · doi:10.1158/1538-7445.am2018-1891

Abstract 1891: Cross-resistance and synergy between idelalisib and bendamustine in chronic lymphocytic leukemia

2018· article· en· W2886701506 on OpenAlexaff
Sara E. Kost, Ali Saleh, Edgard M. Mejia, Marina Mostafizar, Eric D.J. Bouchard, Versha Banerji, Aaron J. Marshall, Spencer B. Gibson, Sachin Katyal, James B. Johnston

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversité de Saint-BonifaceUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsBendamustineIdelalisibChronic lymphocytic leukemiaPeripheral blood mononuclear cellCancer researchCytotoxic T cellCytotoxicityIn vitroLeukemiaBiologyImmunologyBiochemistryIbrutinib

Abstract

fetched live from OpenAlex

Abstract Idelalisib (IDE) is an inhibitor of the δ isoform of PI3 kinase and has shown high activity in chronic lymphocytic leukemia (CLL) either when given alone or in combination with bendamustine (BEN) /rituximab (BR). In the present study, we have determined whether there is cross-resistance between BEN and IDE in primary CLL cells in vitro and whether synergy is observed upon combining these agents. In primary CLL cells in vitro, cross-resistance was not observed between BEN and IDE suggesting different modes of cytotoxicity. In contrast to BEN, sensitivity to IDE was not influenced by prior clinical treatment or the presence of a del 17p. Marked synergy in cytotoxicity was seen between BEN and IDE, which was paralleled by changes in γ-H2AX staining. These findings suggest that the synergistic antitumor effect was related to enhanced DNA damage by the drug combination. The degree of cytotoxic synergy varied and synergy was observed in some cases that were resistant to BEN or IDE, and those with del 17p. Synergy between BEN and IDE was also seen in the B cell lines, BJAB and I83, and in healthy donor peripheral blood mononuclear cells indicating that the phenomenon was not CLL-specific. To simulate the microenvironment, CLL cells were pre-stimulating with CD40L and IL4 prior to drug treatment. Interestingly this treatment caused the cells to become resistant to IDE, but BEN sensitivity was unaffected. However, combining BEN and IDE produced greater synergy than observed when cells were incubated without IL4/CD40. To examine the role of PI3Kδ for synergy, B cells from C57 BL/6 mice, both wild type and with non-functioning PI3Kδ protein, were exposed to BEN and/or IDE. Cells with the non-functioning PI3Kδ protein were more resistant to IDE than the wild-type cells and showed lesser synergy confirming the importance of this protein for the synergistic effect. In summary, these results confirm that IDE can be active against BEN-resistant CLL cells, while BEN may remain active against IDE-resistant samples, demonstrating different modes of anti-tumor activity. However, the unique yet inconsistent synergy seen between these two agents suggest an overlapping mechanism of action. Ongoing studies are evaluating the mechanism for this synergy. Citation Format: Sara E. F. Kost, Ali Saleh, Edgard M. Mejia, Marina Mostafizar, Eric D. J. Bouchard, Versha Banerji, Aaron J. Marshall, Spencer B. Gibson, Sachin Katyal, James B. Johnston. Cross-resistance and synergy between idelalisib and bendamustine 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 1891.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.072
GPT teacher head0.438
Teacher spread0.366 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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