MétaCan
Menu
← Back to cohort
Record W2494861028 · doi:10.1158/1538-7445.am2016-4683

Abstract 4683: Verapamil and tamoxifen modulate ABCB1 expression in multidrug-resistant cells and resensitize them to conventional chemotherapy

2016· article· en· W2494861028 on OpenAlexaff
Georgia Limniatis, Elias Georges

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsMcGill UniversitySte. Anne's Hospital
Fundersnot available
KeywordsVerapamilMultiple drug resistanceTamoxifenP-glycoproteinCancer researchCancerPharmacologyOvarian cancerCancer cellBreast cancerMedicineChemotherapyclone (Java method)BiologyDrug resistanceInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Multidrug-resistant (MDR) tumors are an increasingly important obstacle in cancer treatment, wherein many cases are associated with the overexpression of P-glycoprotein 1 (P-gp1, ABCB1). Previous efforts to sensitize ABCB1-expressing tumor cells to anti-cancer drugs were associated with severe side effects, so interest in clinical trials using these drugs has dwindled. Studies have shown P-glycoprotein-overexpressing cells to be hyper sensitive (or collaterally sensitive) to a diverse group of non-toxic compounds. Given earlier results demonstrating a significant increase in ABCB1 expression post-chemotherapeutic treatment of cancer patients (e.g., breast, ovarian, myeloma, and acute myeloid leukemia), and the role of ABCB1 in drug resistance, it was determined that targeting ABCB1-expressing tumor cells with effective collateral sensitivity drugs should increase the effectiveness of current chemotherapeutic treatments. In this report, it was of interest to determine the effect of the collateral sensitivity drugs verapamil and tamoxifen on P-glycoprotein 1 expression at the level of cells and individual cell clones. Clones from P-gp1-overexpressing Chinese hamster ovarian cell lines (CHRC5) or triple negative breast cancer cells (MDA-MB-231/400 nM doxo) were treated with varying levels of collateral sensitivity drugs and ABCB1 expression was determined by Western blots and ELISAs. The sensitivity of each cell clone to anti-cancer or collateral sensitivity drugs was determined using cytotoxicity assays. Our results demonstrate a drop in ABCB1 expression in each clone, together with decreased collateral sensitivity and overall increased sensitivity to anti-cancer drugs in cell lines selected with verapamil and tamoxifen. Work is in progress to study the various mechanisms responsible for this drop in ABCB1 expression and its impact on treatment outcome. Citation Format: Georgia Limniatis, Elias Georges. Verapamil and tamoxifen modulate ABCB1 expression in multidrug-resistant cells and resensitize them to conventional chemotherapy. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4683.

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 score0.010

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 integrity0.0000.001
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 head0.054
GPT teacher head0.354
Teacher spread0.300 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCancer Research→Same topicDrug Transport and Resistance Mechanisms→French-language works237,207→