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Record W4413074138 · doi:10.2478/ebtj-2025-0018

Messaging malignancy: Tumour-derived exosomes at the nexus of immune escape, vascular remodelling and metastatic competence

2025· article· en· W4413074138 on OpenAlexaff
Duygu T. Yildirim, Abdulbaki Yildirim, Michel Salzet, Matteo Bertelli, Tommaso Beccari, Satya Prakash, Luisa Pascucci, Munis Dündar

Bibliographic record

VenueThe EuroBiotech Journal · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsMcGill University
Fundersnot available
KeywordsMicrovesiclesExosomeAngiogenesisMetastasisImmune systemTumor microenvironmentCrosstalkExtracellular vesiclesBiologyTumor progressionMalignancyCancer researchMedicinemicroRNAImmunologyCell biologyCancerPathology

Abstract

fetched live from OpenAlex

Abstract Exosomes, nano-sized extracellular vesicles secreted by all varieties of living cells, have emerged as pivotal mediators of intercellular communication within the tumor microenvironment. While exosomes significantly contribute to tumor progression, metastasis, immune modulation, and resistance to therapy, the mechanisms of cargo selection and clinical translation remain controversial and insufficiently resolved. Recent high-throughput technologies have enabled detailed profiling of exosomal cargo; however, substantial challenges persist in their clinical application due to issues in isolation and standardization. This review systematically dissects these molecular biogenesis controversies, the roles of tumor-derived exosomes in modulating angiogenesis, immune escape, metastasis, and therapy resistance, and critically evaluates barriers hindering their clinical adoption.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.235
Teacher spread0.227 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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