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Record W1984698740 · doi:10.1089/10430340152528165

A Novel Parasite-Derived Suicide Gene for Cancer Gene Therapy with Specificity for Lung Cancer Cells

2001· article· en· W1984698740 on OpenAlexaff
Caroline Trudeau, Shala Yuan, Jacques Galipeau, Naciba Benlimame, Moulay A. Alaoui‐Jamali, Gerald Batist

Bibliographic record

VenueHuman Gene Therapy · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsJewish General Hospital
FundersNational Cancer Institute
KeywordsSuicide geneProdrugCancer researchCytotoxicityLung cancerBiologyAllopurinolCytotoxic T cellCytosine deaminaseGenetic enhancementPharmacologyMolecular biologyChemistryBiochemistryGeneMedicineIn vitroPathology

Abstract

fetched live from OpenAlex

The enzyme hypoxanthine-guanine phosphoribosyltransferase (HGPRT) expressed by the parasite Trypanosoma brucei (Tb) can convert allopurinol, a purine analogue, to corresponding nucleotides with greater efficiency than its human homologue. We have developed a retroviral system that expresses the parasitic enzyme and tested its capacity to activate the prodrug allopurinol to a cytotoxic metabolite. Cytotoxicity assays demonstrated that five non-small cell lung carcinoma cell lines transduced with the construct were sensitized to the prodrug by 2.1- to 7.6-fold compared with control values. This selectivity was not observed in seven other cell lines also expressing the construct, such as breast carcinoma. Assays indicated that enhanced cytotoxicity to allopurinol correlated with induction of apoptosis in lung cancer cells. The selectivity of this suicide gene was not explained either by the TbHGPRT expression or by the allopurinol accumulation. Our study shows that this novel system may represent a therapeutic tool for gene prodrug targeting of lung cancer, considering the fact that allopurinol is well tolerated in humans.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.054
GPT teacher head0.353
Teacher spread0.299 · 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.

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

Citations9
Published2001
Admission routes1
Has abstractyes

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