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Record W2117321015 · doi:10.1158/0008-5472.can-0482-2

Multidrug-resistant Cancer Cells Facilitate E1-independent Adenoviral Replication

2004· article· en· W2117321015 on OpenAlexaff
Per Sonne Holm, Hermann Lage, Stephan Bergmann, Karsten Jürchott, Gabriel Glockzin, Alexandra Bernshausen, Klaus Mantwill, Axel Ladhoff, Anke Wichert, Joe S. Mymryk, Thomas Ritter, Manfred Dietel, Bernd Gänsbacher, Hans‐Dieter Royer

Bibliographic record

VenueCancer Research · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsMcMaster University
FundersDeutsche KrebshilfeDeutsche Forschungsgemeinschaft
KeywordsMultiple drug resistanceReplication (statistics)VirologyCancerBiologyCancer researchMedicineGeneticsDrug resistance

Abstract

fetched live from OpenAlex

Resistance to chemotherapy is responsible for a failure of current treatment regimens in cancer patients. We have reported previously that the Y-box protein YB-1 regulates expression of the P-glycoprotein gene mdr1, which plays a major role in the development of a multidrug resistant-tumor phenotype. YB-1 predicts drug resistance and patient outcome in breast cancer. Thus, YB-1 is a promising target for new therapeutic approaches to defeat multidrug resistance. In drug-resistant cancer cells and in adenovirus-infected cells YB-1 is found in the nucleus. Nuclear accumulation of YB-1 in adenovirus-infected cells is a function of the E1 region, and we have shown that YB-1 facilitates adenovirus replication. Here we report that E1A-deleted or mutant adenovirus vectors, such as Ad312 and Ad520, replicate efficiently in multidrug-resistant (MDR) cancer cells and induce an adenovirus cytopathic effect resulting in host cell lysis. Thus, replication-defective adenoviruses are a previously unrecognized vector system for a selective elimination of MDR cancer cells. Our work forms the basis for the development of novel oncolytic adenovirus vectors for the treatment of MDR malignant diseases in the clinical setting.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.030
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.077
GPT teacher head0.407
Teacher spread0.329 · 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 teacher head, 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

Citations48
Published2004
Admission routes1
Has abstractyes

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