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Record W2401143451 · doi:10.1126/science.aad3018

The tumor microenvironment underlies acquired resistance to CSF-1R inhibition in gliomas

2016· article· en· W2401143451 on OpenAlexfundno aff
Daniela F. Quail, Robert L. Bowman, Leila Akkari, Marsha L. Quick, Alberto J. Schuhmacher, Jason T. Huse, Eric C. Holland, James Sutton, Johanna A. Joyce

Bibliographic record

VenueScience · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Cancer InstituteLudwig Institute for Cancer ResearchAmerican Brain Tumor Association
KeywordsTumor microenvironmentBlockadeCancer researchGlioblastomaCancerGliomaReceptorMacrophage colony-stimulating factorMedicineBiologyMacrophageImmunologyTumor cellsInternal medicineIn vitro

Abstract

fetched live from OpenAlex

Macrophages accumulate with glioblastoma multiforme (GBM) progression and can be targeted via inhibition of colony-stimulating factor-1 receptor (CSF-1R) to regress high-grade tumors in animal models of this cancer. However, whether and how resistance emerges in response to sustained CSF-1R blockade is unknown. We show that although overall survival is significantly prolonged, tumors recur in >50% of mice. Gliomas reestablish sensitivity to CSF-1R inhibition upon transplantation, indicating that resistance is tumor microenvironment-driven. Phosphatidylinositol 3-kinase (PI3K) pathway activity was elevated in recurrent GBM, driven by macrophage-derived insulin-like growth factor-1 (IGF-1) and tumor cell IGF-1 receptor (IGF-1R). Combining IGF-1R or PI3K blockade with CSF-1R inhibition in recurrent tumors significantly prolonged overall survival. Our findings thus reveal a potential therapeutic approach for treating resistance to CSF-1R inhibitors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), 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

Citations660
Published2016
Admission routes1
Has abstractyes

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