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Record W2562164765

Development of Novel Antiangiogenic Biologics

2012· dissertation· en· W2562164765 on OpenAlexvenueno aff
Iacovos P. Michael

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2012
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsCancer researchFibronectinChemistryAngiogenesisAntibodyExtracellular matrixMolecular biologyCell biologyMedicineBiologyImmunologyBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Current anti-VEGF biologics, such as bevacizumab and VEGF trap, have been successfully used as therapeutic agents for cancer and age-related macular degeneration (AMD). Since these strategies target VEGF systemically, their toxicity profile, including proteinuria and thromboembolic events, and need for frequent eye injections in AMD treatment, prevail. Therefore, the aim of this PhD thesis was to generate novel anti-VEGF biologics that inhibit VEGF activity specifically at the desired target site.\nTwo classes of biologics were engineered that simultaneously bind VEGF and either: 1) the extracellular matrix (ECM) or 2) target-site specific antigens. The first subgroup, “sticky-traps”, is composed of VEGF trap linked to a sequence of hydrophobic amino acids, with affinity for heparin sulfate proteoglycans of the ECM. The second subgroup, “lassos”, is composed of a C-terminus positioned form of VEGF trap linked to single-chain variable domain antibodies specific for either HER2 (HER2/V lasso) or fibronectin extra domain B (EDB; EDB/V lasso), expressed on breast cancer cell surfaces or in the vascular bed of solid tumours, respectively.\nii\nUsing a novel transgenic method, piggyBac transposons, biologics were expressed in transgenic cancer cell lines in a doxycycline inducible manner. They were shown to inhibit VEGF activity and also retain the native function of their constituent domains. Specifically, the sticky-traps adhered to the ECM and the HER2/V lasso inhibited the proliferation of HER2 positive cancer cell lines.\nSticky-traps as well as lassos were able to inhibit or delay tumour growth of A-673, Pc-3, SKOV-3 and HT-29 xenografts. In contrast to soluble VEGF trap, sticky-traps were retained at the tumour site and were undetectable in the circulation. Moreover, sticky-traps, in contrast to VEGF trap, did not delay wound healing and regression of trachea blood vessels. Furthermore, transgenic studies indicated that HER2/V lasso is more effective compared to anti-HER2 Ab and VEGF trap used alone or in combination.\nThese novel classes of antiangiogenic molecules could be advantageous in a clinical setting. Using the principles established in my PhD thesis work, similar dual function biologics can be designed for inhibition of other molecules with disease relevance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.179
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)Same topicAngiogenesis and VEGF in CancerFrench-language works237,207