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Record W2772712497 · doi:10.1158/0008-5472.can-17-1688

The Inhibitory NKR-P1B:Clr-b Recognition Axis Facilitates Detection of Oncogenic Transformation and Cancer Immunosurveillance

2018· article· en· W2772712497 on OpenAlexafffund
Miho Tanaka, Jason H. Fine, Christina L. Kirkham, Oscar A. Aguilar, A. Belcheva, Alberto Martín, Troy Ketela, Jason Moffat, David Allan, James R. Carlyle

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsAmgen (Canada)University of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health ResearchUniversity of TorontoGovernment of Canada
KeywordsImmunosurveillanceBiologyCancer researchMHC class ICancer cellCancerImmune systemMajor histocompatibility complexImmunology

Abstract

fetched live from OpenAlex

Abstract Natural killer (NK) cells express receptors specific for MHC class I (MHC-I) molecules involved in “missing-self” recognition of cancer and virus-infected cells. Here we elucidate the role of MHC-I-independent NKR-P1B:Clr-b interactions in the detection of oncogenic transformation by NK cells. Ras oncogene overexpression was found to promote a real-time loss of Clr-b on mouse fibroblasts and leukemia cells, mediated in part via the Raf/MEK/ERK and PI3K pathways. Ras-driven Clr-b downregulation occurred at the level of the Clrb (Clec2d) promoter, nascent Clr-b transcripts, and cell surface Clr-b protein, in turn promoting missing-self recognition via the NKR-P1B inhibitory receptor. Both Ras- and c-Myc–mediated Clr-b loss selectively augmented cytotoxicity of oncogene-transformed leukemia cells by NKR-P1B+ NK cells in vitro and enhanced rejection by WT mice in vivo. Interestingly, genetic ablation of either one (Clr-b+/−) or two Clr-b alleles (Clr-b−/−) enhanced survival of Eμ-cMyc transgenic mice in a primary lymphoma model despite preferential rejection of Clr-b−/− hematopoietic cells previously observed following adoptive transfer into naïve wild-type mice in vivo. Collectively, these findings suggest that the inhibitory NKR-P1B:Clr-b axis plays a beneficial role in innate detection of oncogenic transformation via NK-cell–mediated cancer immune surveillance, in addition to a pathologic role in the immune escape of primary lymphoma cells in Eμ-cMyc mice in vivo. These results provide a model for the human NKR-P1A:LLT1 system in cancer immunosurveillance in patients with lymphoma and suggest it may represent a target for immune checkpoint therapy. Significance: A mouse model shows that an MHC-independent NK-cell recognition axis enables the detection of leukemia cells, with implications for a novel immune checkpoint therapy target in human lymphoma. Cancer Res; 78(13); 3589–603. ©2018 AACR.

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)0.0010.001

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 head0.049
GPT teacher head0.340
Teacher spread0.291 · 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

Citations9
Published2018
Admission routes2
Has abstractyes

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