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Record W4403957774 · doi:10.1111/gtc.13177

Immunotherapy‐induced reprogramming of cancer‐associated fibroblasts can promote tumor progression

2024· article· en· W4403957774 on OpenAlexfundno aff
Tomoya Yamashita, Haruki Horiguchi, Tsuyoshi Kadomatsu, Michio Sato, Toshiro Moroishi, Yuichi Oike

Bibliographic record

VenueGenes to Cells · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
FundersCanadian Mental Health AssociationMinistry of Education, Culture, Sports, Science and TechnologyTakeda Science Foundation
KeywordsCancer-Associated FibroblastsBiologyCancer researchImmunotherapyReprogrammingCancer immunotherapyTumor microenvironmentTumor progressionTumor necrosis factor alphaMelanomaImmune systemCancerContext (archaeology)CrosstalkImmunologyCell

Abstract

fetched live from OpenAlex

Use of immune checkpoint inhibitors (ICIs) as cancer immunotherapy has advanced rapidly in the clinic; however, ICI initiation can also cause an unexpectedly rapid acceleration of cancer progression in some patients. Here, we used a murine syngeneic melanoma model to conduct mechanistic analysis of cancer-associated fibroblast (CAF) function in cancer progression in the context of immunotherapy. We found that after ICI treatment CAFs acquire inflammatory properties, which can promote tumor progression. Mechanistically, we show that T-cell-derived interferon-γ (IFN-γ) stimulates production of tumor necrosis factor-α (TNF-α) by macrophages, facilitating CAF conversion to inflammatory CAFs. Our findings suggest that CAF/immune cell crosstalk plays an essential role in ICI-associated tumor progression.

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 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 score0.363
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.319
Teacher spread0.302 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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