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Record W2896378740 · doi:10.3389/fimmu.2018.02391

MUC1 Mucin: A Putative Regulatory (Checkpoint) Molecule of T Cells

2018· review· en· W2896378740 on OpenAlexaff
Babita Agrawal, Nancy Gupta, Jeffrey D. Konowalchuk

Bibliographic record

VenueFrontiers in Immunology · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsImmune systemT cellCell biologyBiologyAcquired immune systemT-cell receptorAntigen-presenting cellCancer immunotherapyImmunotherapyImmunology

Abstract

fetched live from OpenAlex

T lymphocytes are at the center of inducing an effective adaptive immune response and maintaining homeostasis. T cell responses are initiated through interactions between antigen presenting cells (APCs) and T cells. The type and strength of signals delivered through the T cell receptor (TCR) may modulate how the cells respond. The TCR-MHC (T cell receptor-major histocompatibility complex molecules) complex dictates the specificity, whereas co-stimulatory signals induced by interaction of various accessory cell surface molecules strengthen and optimize T cell responses. Multiple immune regulatory mechanisms brought about by co-inhibitory molecules expressed on T cells play a key role in orchestrating successful and non-damaging immunity. These co-inhibitory molecules are also referred to as initiators of immune check-points or co-inhibitory pathways. Knowledge of co-inhibitory pathways associated with activated T lymphocytes has allowed a better understanding of (a) the inflammatory and anti-inflammatory processes associated with infectious diseases and autoimmune diseases, and (b) mechanisms by which tumors evade immune attack. Many of these regulatory pathways are non-redundant and function in a highly concerted manner. Targeting them has provided effective approaches in treating cancer and autoimmune diseases. For this reason, it is valuable to identify any co-inhibitory molecules that affect these pathways. MUC1 mucin (CD227) has long been known to be expressed by epithelial cells and overexpressed by a multitude of adenocarcinomas. As long ago as 1998 we made a surprising discovery that MUC1 is also expressed by activated human T cells and we provided the first evidence of the role of MUC1 as a novel T cell regulator. Subsequent studies from different laboratories, as well as ours, supported an immuno-regulatory role of MUC1 in infections, inflammation, and autoimmunity that corroborated our original findings establishing MUC1 as a novel T cell regulatory molecule. In this article, we will discuss the experimental evidence supporting MUC1 as a putative regulatory molecule or a "checkpoint molecule" of T cells with implications as a novel biomarker and therapeutic target in chronic diseases such as autoimmunity, inflammation and cancer, and possibly infections.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
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 head0.015
GPT teacher head0.260
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2018
Admission routes1
Has abstractyes

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