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Record W2067886336 · doi:10.1158/1538-7445.am2013-4636

Abstract 4636: AMF-1c-120: an antibody specific for misfolded prion protein expressed on ovarian cancer cells.

2013· article· en· W2067886336 on OpenAlexaff
Marni D. Uger, Viengthong Chai, Veronica Ciolfi, Hui Chen, Ewa Plawinski, Tapfuma Mutukura, Andrew P. Sage, Ryan W. Demers, Leo Lau, Pierre Lee, Xiuwen Liu, Jun Guan, Yuzhuo Wang, William Guest, Steven S. Plotkin, Neil R. Cashman

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of British ColumbiaAmorfix (Canada)
Fundersnot available
KeywordsEpitopeOvarian cancerAntibodyMonoclonal antibodyBiologyCancer researchCancerCancer cellCellMolecular biologyCell biologyChemistryBiochemistryImmunologyGenetics

Abstract

fetched live from OpenAlex

Abstract We tested the hypothesis that cancer cells might display misfolded protein molecules at the cell surface, due to oxidative covalent modifications, defective glycosylation, and/or other factors relevant to cancer. We developed a computational algorithm to predict regions of proteins which were most likely to undergo loss of structure and resemble free unstructured peptides against which antibodies could be generated and screened. Antibodies directed against these misfolding-prone regions, termed disease-specific epitopes (DSEs), are therefore expected to recognize cancer cells while sparing natively folded proteins on healthy cells. We have applied this strategy to develop an antibody that is specific for ovarian cancer cells, which does not bind to normal ovarian epithelium. Using the ProMIS™ computational algorithm to predict unstable regions in proteins, three DSEs in the prion protein (PrP) were identified. Ultra-high sensitivity antibodies are required for binding to isolated misfolded protein molecules at the cell surface, and thus rabbits were immunized with peptides corresponding to the PrP DSE sequences and rabbit monoclonal anti-peptide antibodies were generated. One antibody, AMF-1c-120, has sub-nanomolar binding affinity for denatured PrP, but does not bind to native PrP. AMF-1c-120 binds to four ovarian tumor cell lines and one ovarian tumor implanted and propagated in mice, but does not bind to normal ovarian epithelial cells. Proteinase K sensitivity of the AMF-1c-120 epitope is consistent with partial denaturation of PrP at the cell surface of ovarian cancer cell lines. Preclinical efficacy studies are in progress to investigate the anti-tumor effects of AMF-1c-120. Citation Format: Marni D. Uger, Viengthong Chai, Veronica Ciolfi, Hui Chen, Ewa Plawinski, Tapfuma Mutukura, Andrew Sage, Ryan Demers, Leo Lau, Pierre Lee, Xiuwen Liu, Jun Guan, Yuzhuo Wang, William C. Guest, Steven S. Plotkin, Neil R. Cashman. AMF-1c-120: an antibody specific for misfolded prion protein expressed on ovarian cancer cells. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4636. doi:10.1158/1538-7445.AM2013-4636

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 score0.004

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)0.0010.000

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 head0.131
GPT teacher head0.446
Teacher spread0.315 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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