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Record W2168693931 · doi:10.1084/jem.20102575

CEACAM1 dampens antitumor immunity by down-regulating NKG2D ligand expression on tumor cells

2011· article· en· W2168693931 on OpenAlexafffund
Zhangguo Chen, Lanfen Chen, Kristi Baker, Torsten Olszak, Sebastian Zeißig, Yu‐Hwa Huang, Timothy Kuo, Ofer Mandelboim, Nicole Beauchemin, Lewis L. Lanier, Richard S. Blumberg

Bibliographic record

VenueThe Journal of Experimental Medicine · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMcGill University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health Research
KeywordsNKG2DCytolysisCarcinoembryonic antigenBiologyCancer researchImmune systemCell adhesion moleculeTumor progressionCellNatural killer cellSuppressorMetastasisCell biologyIn vitroImmunologyCytotoxicityCancer

Abstract

fetched live from OpenAlex

Although carcinoembryonic antigen (CEA)-related cell adhesion molecule 1 (CEACAM1) has been viewed as a tumor suppressor, increasing clinical evidence shows that high levels of CEACAM1 expression on tumors correlates with poor prognosis and high risk of metastasis. Here, we examined the consequences of CEACAM1 expression on tumor cells. We show that tumor cell-associated CEACAM1 causes intracellular retention of various NKG2D ligands in mouse and human tumor cells. CEACAM1-silenced tumor cells expressed more cell surface NKG2D ligands and exhibited greater sensitivity to natural killer cell-mediated cytolysis in vitro and rejection in vivo. Our studies reveal a novel mechanism through which CEACAM1-bearing tumor cells may escape immune-surveillance.

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 score0.001
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 integrity0.0000.001
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 head0.024
GPT teacher head0.264
Teacher spread0.241 · 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

Citations68
Published2011
Admission routes2
Has abstractyes

Explore more

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