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Record W3139363653 · doi:10.11159/nddte19.102

Half-Chain Trastuzumab Nanoconjugates Enhance Antitumor Activityin HER2+ breast cancer

2019· article· en· W3139363653 on OpenAlexvenueno aff
Marta Truffi, Miriam Colombo, Luca Sorrentino, Serena Mazzucchelli, Laura Pandolfi, Arianna Bonizzi, Davide Prosperi, Fabio Corsi

Bibliographic record

VenueProceedings of the World Congress on Recent Advances in Nanotechnology · 2019
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsnot available
Fundersnot available
KeywordsTrastuzumabBreast cancerCancer researchCancerOncologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

The human epidermal growth factor receptor 2 (HER2) is overexpressed in about 20-30% of all breast cancers, where it triggers multiple downstream pathways required for the abnormal proliferation of cancer cells.[1] In HER2+ breast cancer population, anti-HER2-specific therapies have revolutionized the clinical management of the disease. In particular, since its approval by the Food and Drug Administration, the monoclonal antibody trastuzumab (TZ) has represented the gold standard for the treatment, with improved disease-free and overall survival.[2] In vivo, the antiproliferative mechanism of TZ is prominently hold by recruitment of antitumor immunity, through a mechanism called antibody-dependent cell-mediated cytotoxicity (ADCC). However, TZ may also exert direct blockade of HER2-mediated downstream signaling, with inhibition of pathways supporting tumor growth and proliferation.[3, 4] Several nanoconjugates have exploited TZ as a potent and effective targeting molecule to improve specificity for HER2-overexpressing tumor cells.[5-7] However, there is no real investigation on how the activity and the therapeutic efficacy of TZ may vary due to conjugation and spatial exposure on the surface of nanoparticles. Small colloidal iron oxide nanoparticles were functionalized with multiple half chains of TZ upon reduction of disulfide bridges between the two heavy chains of the IgG. Resulting nanoparticles (MNP-HC) showed hydrodynamic diameter of 48.7 ± 1.0 nm and ζ-potential of-44.5 ± 9.9 mV. MNP-HC were assessed for their capability to interact with human breast cancer cell lines and compared to aspecific IgG-coupled nanoparticles or same dosage of free TZ. MNP-HC revealed dose-dependent binding to breast cancer cells, with increasing percentage of positivity for those cell lines overexpressing HER2. Specificity of MNP-HC for HER2 was confirmed by competition assay in presence of a molar excess of free TZ. Interaction of MNP-HC with TZ-sensitive cells induced tyrosine-specific phosphorylation in the catalytic site of HER2 receptor even at low dosage, and rapid cellular uptake by endocytosis. Treatment with MNP-HC decreased viability of breast cancer cells, leading to enhanced antitumor efficacy as compared to equal dosage of free TZ. Reduced viability was associated with increased expression of the cell cycle inhibitor p27Kip1 and cell cycle arrest in G1 phase. MNP-HC did not loose capability to activate ADCC, further indicating valuable potential for the nanocomplex. Moreover, MNP-HC were tested on TZ-resistant breast cancer cells, where they were able to induce direct reduction of cell viability and sensitization to chemotherapy. In conclusion, multiple and oriented immobilization of TZ half chains on carriers with narrow size amplified recognition of HER2 and enhanced anti-HER2 efficacy of TZ antibody. Improved antitumor performance of MNP-HC was mainly attributed to sustained blockade of HER2-mediated downstream signaling, although capability to prime ADCC was still maintained. Powerful inhibition of HER2 signaling also promoted responsiveness of TZ-resistant cells, thus suggesting MNP-HC as strategy option for drug re-sensitization in the treatment of HER2-positive breast cancer.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
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 head0.010
GPT teacher head0.323
Teacher spread0.313 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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Same venueProceedings of the World Congress on Recent Advances in NanotechnologySame topicHER2/EGFR in Cancer ResearchFrench-language works237,207