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Record W4407064351 · doi:10.1016/j.bbcan.2025.189275

Extracellular vesicles and the tumour microenvironment

2025· review· en· W4407064351 on OpenAlexaff
Szilárd-Krisztián Belényesi, Sean Patmore, Lorraine O’Driscoll

Bibliographic record

VenueBiochimica et Biophysica Acta (BBA) - Reviews on Cancer · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsTrinity College
FundersHigher Education Authority
KeywordsExtracellular vesiclesExtracellularVesicleChemistryCell biologyBiophysicsTumor microenvironmentMicrovesiclesExtracellular matrixCancer researchBiochemistryBiologyMembraneTumor cellsmicroRNA

Abstract

fetched live from OpenAlex

Extracellular vesicles (EVs), tiny packages of information released by cells, are well established as being involved in unwanted cell-to-cell communication in cancer. EVs from cancer cells have been associated with the spread of drug resistance, immune suppression, and metastasis. Additional to cancer cells, the tumour microenvironment (TME) involves many cell types -including immune cells, fibroblasts, and endothelial cells, each of which has a potential role in how tumours grow, spread, and respond (or otherwise) to therapy. This review collates and distils research developments regarding the role of EVs in multi-way communication between cells in the TME. Further research including tailored clinical studies are now warranted to determine how best to prevent this extensive adverse communication occurring and/or how best to exploit it for biomarker discovery and as a therapeutic approach, in the interest of patients and also for economic benefit.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.316
Teacher spread0.294 · 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.

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

Citations16
Published2025
Admission routes1
Has abstractyes

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