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Record W2911467060 · doi:10.1186/s13046-018-0999-5

Therapeutic impact of Nintedanib with paclitaxel and/or a PD-L1 antibody in preclinical models of orthotopic primary or metastatic triple negative breast cancer

2019· article· en· W2911467060 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Experimental & Clinical Cancer Research · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsOntario Institute for Cancer ResearchUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsTriple-negative breast cancerPaclitaxelMedicineNintedanibOncologyBreast cancerInternal medicineTriple negativeMetastatic breast cancerAntibodyDocetaxelCancerCancer researchImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Triple negative breast cancer (TNBC) is an aggressive malignancy with poor prognosis, in part because of the current lack of any approved molecularly targeted therapy. We evaluated various combinations of three different drugs: nintedanib, an antiangiogenic TKI targeting VEGF receptors, paclitaxel (PTX), or a PD-L1 antibody, using models of orthotopic primary or advanced metastatic TNBC involving a metastatic variant of the MDA-MB-231 human cell line (called LM2-4) in SCID mice and two mouse lines (EMT-6 and a drug-resistant variant, EMT-6/CDDP) in immunocompetent mice. These drugs were selected based on the following: PTX is approved for TNBC; nintedanib combined with docetaxel has shown phase III clinical trial success, albeit in NSCLC; VEGF can act as local immunosuppressive factor; and PD-L1 antibody plus taxane therapy was recently reported to have encouraging phase III trial benefit in TNBC. METHODS: Statistical analyses were performed with ANOVA followed by Tukey's Multiple Comparison Test or with Kruskal-Wallis test followed by Dunn's Multiple Comparison Test. Survival curves were analyzed using a Log-rank (Mantel Cox) test. Differences were considered statistically significant when p values were < 0.05. RESULTS: Toxicity analyses showed that nintedanib is well tolerated when administered 5-days ON 2-days OFF; PTX toxicity differed in mice, varied with cell lines used and may have influenced median survival in the metastatic EMT6/CDDP model; while toxicity of PD-L1 therapy depended on the cell lines and treatment settings tested. In the LM2-4 system, combining nintedanib with PTX enhanced overall antitumor efficacy in both primary and metastatic treatment settings. In immunocompetent mice, combining nintedanib or PTX with the PD-L1 antibody improved overall antitumor efficacy. Using the advanced metastatic EMT-6/CDDP model, optimal efficacy results were obtained using the triple combination. CONCLUSIONS: These results suggest circumstances where nintedanib plus PTX may be potentially effective in treating TNBC, and nintedanib with PTX may improve PD-L1 therapy of metastatic TNBC.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.232
GPT teacher head0.570
Teacher spread0.338 · 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