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Record W2161308975 · doi:10.4049/jimmunol.169.8.4467

Synergistic Engagement of an Ineffective Endogenous Anti-Tumor Immune Response and Induction of IFN-γ and Fas-Ligand-Dependent Tumor Eradication by Combined Administration of IL-18 and IL-2

2002· article· en· W2161308975 on OpenAlexaff
Jon M. Wigginton, Jong‐Keuk Lee, T A Wiltrout, W. Gregory Alvord, Julie A. Hixon, Jeffrey Subleski, Timothy Back, Robert H. Wiltrout

Bibliographic record

VenueThe Journal of Immunology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsPediatric Oncology Group
FundersNational Cancer InstituteNational Institutes of Health
KeywordsEndogenyImmune systemFas ligandCytokineIn vivoImmunologyCancer researchCD8BiologyEx vivoApoptosisEndocrinologyProgrammed cell deathBiochemistry

Abstract

fetched live from OpenAlex

IFN-gamma is a critical component of the endogenous and many cytokine-induced antitumor immune responses. In this study we have shown that the combination of IL-18 and IL-2 (IL-18/IL-2) synergistically enhances IFN-gamma production both in vitro and in vivo, and synergizes in vivo to induce complete durable regression of well-established 3LL tumors in >80% of treated mice. We have observed a nascent, but ineffective, host immune response against 3LL that depends on endogenous IFN-gamma and IL-12 production and the Fas/Fas ligand (Fas-L) pathway. The combined administration of IL-18/IL-2 engages this endogenous response to induce tumor regression via a mechanism that is independent of NK and NKT cells or IL-12, but is critically dependent on CD8(+) T cells, IFN-gamma, and the Fas/Fas-L pathway. These studies demonstrate the importance of IFN-gamma as well as the Fas/Fas-L pathway in both endogenous and cytokine-driven antitumor immune responses engaged by IL-18/IL-2 and provide preclinical impetus for clinical investigation of this potent anti-tumor combination.

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)0.001
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 score0.034
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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

Citations70
Published2002
Admission routes1
Has abstractyes

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