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Record W1661409319 · doi:10.4049/jimmunol.180.6.3766

Modulation of the Tumor Cell Phenotype by IFN-γ Results in Resistance of Uveal Melanoma Cells to Granule-Mediated Lysis by Cytotoxic Lymphocytes

2008· article· en· W1661409319 on OpenAlexaff
Kristian Hallermalm, Kazutake Seki, Anna De Geer, Bruce Motyka, R. Chris Bleackley, Martine J. Jager, Christopher J. Froelich, Rolf Kiessling, Victor Levitsky, Jelena Levitskaya

Bibliographic record

VenueThe Journal of Immunology · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversity of Alberta
FundersCancerfonden
KeywordsCytotoxic T cellPhenotypeMelanomaLysisGranule (geology)CytotoxicityCellCancer researchTumor cellsChemistryImmunologyIn vitroBiologyCell biologyGeneBiochemistry

Abstract

fetched live from OpenAlex

IFN-gamma, a pleiotropic immune regulator, is implicated in both tumor immune surveillance and selection of tumor variants resistant to immune control, i.e., immunoediting. In uveal melanoma patients, elevated serum levels of IFN-gamma correlate with the spread of metastasis and represent a negative prognostic marker. Treatment with IFN-gamma boosted the MHC class I presentation machinery in uveal melanoma cells but suppressed their MHC class I-restricted CTL lysis. Tumor cells exposed to IFN-gamma efficiently activated specific CTL but were less susceptible to permeabilization by perforin and exhibited a decreased capacity to bind and incorporate granzyme B. These results define a novel mechanism of resistance to granule-mediated CTL lysis in human tumors. Furthermore, the data suggest that immunoediting is not limited to genetic or epigenetic changes resulting in stable cellular phenotypes but also involves an inducible modulation of tumor cells in response to a microenvironment associated with immune activation.

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 score0.023
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations48
Published2008
Admission routes1
Has abstractyes

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