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Record W2108012124 · doi:10.1016/j.molonc.2013.03.005

Blocking the attachment of cancer cells in vivo with DNA aptamers displaying anti‐adhesive properties against the carcinoembryonic antigen

2013· article· en· W2108012124 on OpenAlexafffund
Erik W. Orava, Aws Abdul‐Wahid, Eric H.‐B. Huang, Amirul Islam Mallick, Jean Gariépy

Bibliographic record

VenueMolecular Oncology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsAptamerCarcinoembryonic antigenCancer cellCell adhesionCancer researchIn vivoCancerCellDNAAdhesionAntigenChemistryCell biologyBiologyMolecular biologyImmunologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

The formation of metastatic foci occurs through a series of cellular events, initiated by the attachment and aggregation of cancer cells leading to the establishment of micrometastases. We report the derivation of synthetic DNA aptamers bearing anti-adhesive properties directed at cancer cells expressing the carcinoembryonic antigen (CEA). Two DNA aptamers targeting the homotypic and heterotypic IgV-like binding domain of CEA were shown to block the cell adhesion properties of CEA, while not recognizing other IgV-like domains of CEACAM family members that share strong sequence and structural homologies. More importantly, the pre-treatment of CEA-expressing tumour cells with these aptamers prior to their intraperitoneal implantation resulted in the prevention of peritoneal tumour foci formation. Taken together, these results highlight the effectiveness of targeting the cell adhesion properties of cancer cells with aptamers in preventing tumour implantation.

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 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 score0.005
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.265
Teacher spread0.255 · 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.

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

Citations22
Published2013
Admission routes2
Has abstractyes

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