MétaCan
Menu
← Back to cohort
Record W2885657565 · doi:10.1158/1538-7445.am2018-5610

Abstract 5610: CD125xCNE bispecific antibody development to treat bladder cancer

2018· article· en· W2885657565 on OpenAlexaff
Judit Hunyadkürti, Jeffrey V. Leyton, Laurent Fafard-Couture, Vincent Lacasse, Marc‐André Bonin, Angel F. López

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBladder cancerAntibodyUrotheliumCancerCancer researchCarcinogenesisMonoclonal antibodyChemistryMolecular biologyMedicineInternal medicineImmunologyBiologyUrinary system

Abstract

fetched live from OpenAlex

Abstract Background: Bladder cancer is one of the most prevalent cancers impacting adults worldwide.Although,successfully treated in its early stages, there are no effective therapies when the cancer has progressed into the surrounding muscle layer, clinically classified as muscle invasive bladder cancer (MIBC). CD125 was recently shown to be involved in MIBC progression and uniquely overexpressed in MIBC tumors relative to healthy urothelium or superficial tumors. Cyclin E (CNE) is a critical cell cycle protein and regulates progression of normal cells to replicate their DNA. There is a strong link between CNE dysregulation and tumorigenesis and was recently found to be overexpressed in MIBC. We characterized the monoclonal antibodies (mAbs) A14 specific for CD125, and HE-12 and HE-172 specific for CNE with a long-term purpose to develop a CD125xCNE therapeutic bispecific antibody. In order, for the antibody to efficiently target CNEour group developed a natural composite compound (termed Accum)that conjugates to surface lysines and enables mAbs to escape endosomal entrapment followed by active routing to and efficient accumulation in the nucleus. Methods: For Accum conjugation, maleimide groups were introduced into A14 by reaction with 10-to-100-fold molar excess of a PEGylated SMCC crosslinker at RT for 1 h. Purified and concentrated maleimide-derivatized A14 was reacted with 100-fold molar excess Accum for 18 h at 4 °C. Excess Accum-A14 was purified and concentrated. Conjugation was characterized by SDS-PAGE. CD125-positive MIBC cells were treated with Accum-A14 and nuclear localization efficiency determined by confocal microscopy.HE-12 and HE-172 mAbs were evaluated for binding nuclear CNE by flow cytometry using the whole cell and fractionated cell lysate along with saponin to enable the mAbs to diffuse into the cell. In addition, HE-12 and HE-172 mAb binding was evaluated by co-immunoprecipitation. PCR amplification of A14, HE-12, and HE-172 was performed. Results: A14 is readily loaded with Accum with minimal aggregation.Accum-A14 undergoesCD125-specific internalization and has 25-60-fold increased nuclear localization relative to A14 in MIBC cells.The binding of the intracellular CNE by mAb HE-12 and HE-172 was specific. Conclusion: This preliminary data demonstrates that Accum modification of A14 retains CD125 specificity and efficiently localizes to the nucleus of MIBC cells. HE-12 and HE172 recognized CNE. On going work will construct the CD125xCNE bispecific antibody. Future studies will determine the efficiency to target CNE and its impact to MIBC progression. Citation Format: Judit Hunyadkurti, Jeffrey Leyton, Laurent Fafard-Couture, Vincent Lacasse, Marc-Andre Bonin, Angel Lopez. CD125xCNE bispecific antibody development to treat bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5610.

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 integrity0.0000.000
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 head0.070
GPT teacher head0.425
Teacher spread0.355 · 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCancer Research→Same topicCancer, Hypoxia, and Metabolism→French-language works237,207→