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Record W2160615924 · doi:10.1158/0008-5472.can-13-1791

Tumor–Stroma Interaction: Revealing Fibroblast-Secreted Exosomes as Potent Regulators of Wnt-Planar Cell Polarity Signaling in Cancer Metastasis

2013· review· en· W2160615924 on OpenAlexafffund
Valbona Luga, Jeffrey L. Wrana

Bibliographic record

VenueCancer Research · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersCanadian Institutes of Health Research
KeywordsMicrovesiclesWnt signaling pathwayMetastasisAutocrine signallingBiologyCancer researchCell biologyStromaCancer cellCell polarityCell signalingExosomeCell migrationTumor microenvironmentCancerSignal transductionCellmicroRNAImmunologyCell cultureTumor cellsGenetics

Abstract

fetched live from OpenAlex

Cancer-associated fibroblasts (CAF) regulate tumor progression, but their role in cancer metastasis remains largely unexplored. Exosomes are secreted microvesicles that are emerging as potent mediators of cell-cell communication that are of particular importance in tumor-stroma interactions. The Wnt-planar cell polarity (PCP) pathway is the primary regulator of convergent extension cell movements during vertebrate development, but the role of this signaling pathway in cancer cell migration and metastasis has been unclear. Recently, we revealed that fibroblasts secrete exosomes that promote breast cancer cell (BCC) protrusive activity, motility, and metastasis by activating autocrine Wnt-PCP signaling in BCCs. Moreover, we showed that Wnt ligands produced by BCCs tether to fibroblast exosomes upon trafficking of exosomes in BCCs. These findings have several implications that motivate promising future research in the fields of tumor-stroma communication, exosome function, and Wnt-PCP signaling in cancer metastasis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.099
GPT teacher head0.430
Teacher spread0.331 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations175
Published2013
Admission routes2
Has abstractyes

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