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Record W2954220199 · doi:10.3390/cancers11070904

Wnt Signaling in Cancer Metabolism and Immunity

2019· review· en· W2954220199 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCancers · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of China
KeywordsWnt signaling pathwayTumor microenvironmentBiologyCancer researchCancer stem cellGlutaminolysisCarcinogenesisCancerCancer immunotherapyLRP6Cancer cellReprogrammingCell biologyImmune systemSignal transductionImmunotherapyImmunologyStem cellCellTumor cellsGenetics

Abstract

fetched live from OpenAlex

The Wingless (Wnt)/β-catenin pathway has long been associated with tumorigenesis, tumor plasticity, and tumor-initiating cells called cancer stem cells (CSCs). Wnt signaling has recently been implicated in the metabolic reprogramming of cancer cells. Aberrant Wnt signaling is considered to be a driver of metabolic alterations of glycolysis, glutaminolysis, and lipogenesis, processes essential to the survival of bulk and CSC populations. Over the past decade, the Wnt pathway has also been shown to regulate the tumor microenvironment (TME) and anti-cancer immunity. Wnt ligands released by tumor cells in the TME facilitate the immune evasion of cancer cells and hamper immunotherapy. In this review, we illustrate the role of the canonical Wnt/β-catenin pathway in cancer metabolism and immunity to explore the potential therapeutic approach of targeting Wnt signaling from a metabolic and immunological perspective.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.757

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 science0.0000.000
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 head0.055
GPT teacher head0.358
Teacher spread0.303 · 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