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Record W4224297813 · doi:10.3389/fcell.2022.839041

Inflammasomes in Cancer Progression and Anti-Tumor Immunity

2022· review· en· W4224297813 on OpenAlexaff
Sebastian Lillo, Maya Saleh

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersFondation ARC pour la Recherche sur le Cancer
KeywordsInflammasomeInnate immune systemBiologyProinflammatory cytokineCancerProteasesInflammationImmunologyCarcinogenesisImmunityPattern recognition receptorCaspase 1Programmed cell deathCancer researchImmune systemApoptosis

Abstract

fetched live from OpenAlex

The inflammasomes are critical regulators of innate immunity, inflammation and cell death and have emerged as important regulators of cancer development and control. Inflammasomes are assembled by pattern recognition receptors (PRR) following the sensing of microbial- or danger-associated molecular patterns (MAMPs/DAMPs) and elicit inflammation through the oligomerization and activation of inflammatory caspases. These cysteinyl-aspartate proteases cleave the proinflammatory cytokines IL-1β and IL-18 into their biologically active mature form. The roles of the inflammasomes and associated pro-inflammatory cytokines vary greatly depending on the cancer type. Here we discuss recent studies highlighting contrasting roles of the inflammasome pathway in curbing versus promoting tumorigenesis. On one hand, the inflammasomes participate in stimulating anti-tumor immunity, but they have also been shown to contribute to immunosuppression or to directly promote tumor cell survival, proliferation, and metastasis. A better understanding of inflammasome functions in different cancers is thus critical for the design of novel cancer immunotherapies.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.015
GPT teacher head0.285
Teacher spread0.270 · 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.

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

Citations51
Published2022
Admission routes1
Has abstractyes

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