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Record W2784964219 · doi:10.1371/journal.pone.0191766

Novel anti-cancer drug COTI-2 synergizes with therapeutic agents and does not induce resistance or exhibit cross-resistance in human cancer cell lines

2018· article· en· W2784964219 on OpenAlexaff
Saman Maleki Vareki, Kowthar Y. Salim, Wayne R. Danter, James Koropatnick

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsWestern UniversityLawson Health Research Institute
Fundersnot available
KeywordsDrug resistanceIn vivoCancerCancer cellDrugMedicinePharmacologyCombination therapyChemotherapyCancer researchChemotherapeutic drugsLimitingInternal medicineBiologyBiotechnology

Abstract

fetched live from OpenAlex

Emerging drug-resistance and drug-associated toxicities are two major factors limiting successful cancer therapy. Combinations of chemotherapeutic drugs have been used in the clinic to improve patient outcome. However, cancer cells can acquire resistance to drugs, alone or in combination. Resistant tumors can also exhibit cross-resistance to other chemotherapeutic agents, resulting in sub-optimal treatment and/or treatment failure. Therefore, developing novel oncology drugs that induce no or little acquired resistance and with a favorable safety profile is essential. We show here that combining COTI-2, a novel clinical stage agent, with multiple chemotherapeutic and targeted agents enhances the activity of these drugs in vitro and in vivo. Importantly, no overt toxicity was observed in the combination treatment groups in vivo. Furthermore, unlike the tested chemotherapeutic drugs, cancer cells did not develop resistance to COTI-2. Finally, some chemo-resistant tumor cell lines only showed mild cross-resistance to COTI-2 while most remained sensitive to it.

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 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 score0.046
Threshold uncertainty score0.971

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 head0.043
GPT teacher head0.293
Teacher spread0.250 · 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

Citations45
Published2018
Admission routes1
Has abstractyes

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