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Record W4386029355 · doi:10.1186/s12862-023-02147-5

A model for the dissemination of circulating tumour cell clusters involving platelet recruitment and a plastic switch between cooperative and individual behaviours

2023· article· en· W4386029355 on OpenAlexafffund
Jorian D. Hapeman, Caroline S. Carneiro, Aurora M. Nedelcu

Bibliographic record

VenueBMC Ecology and Evolution · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of New Brunswick
FundersNew Brunswick Innovation FoundationUniversity of New Brunswick
KeywordsPlateletBiologyComputational biologyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: In spite of extensive research, cancer remains a major health problem worldwide. As cancer progresses, cells acquire traits that allow them to disperse and disseminate to distant locations in the body - a process known as metastasis. While in the vasculature, these cells are referred to as circulating tumour cells (CTCs) and can manifest either as single cells or clusters of cells (i.e., CTC clusters), with the latter being the most aggressive. The increased metastatic potential of CTC clusters is generally associated with cooperative group benefits in terms of survival, including increased resistance to shear stress, anoikis, immune attacks and drugs. However, the adoption of a group phenotype poses a challenge when exiting the vasculature (extravasation) as the large size can hinder the passage through vessel walls. Despite their significant role in the metastatic process, the mechanisms through which CTC clusters extravasate remain largely unknown. Based on the observed in vivo association between CTC clusters and platelets, we hypothesized that cancer cells take advantage of the platelet-derived Transforming Growth Factor Beta 1 (TGF-β1) - a signalling factor that has been widely implicated in many aspects of cancer, to facilitate their own dissemination. To address this possibility, we evaluated the effect of exogenous TGF-β1 on an experimentally evolved non-small cell lung cancer cell line that we previously developed and used to investigate the biology of CTC clusters. RESULTS: We found that exogenous TGF-β1 induced the dissociation of clusters in suspension into adherent single cells. Once adhered, cells released their own TGF-β1 and were able to individually migrate and invade in the absence of exogenous TGF-β1. Based on these findings we developed a model that involves a TGF-β1-mediated plastic switch between a cooperative phenotype and a single-celled stage that enables the extravasation of CTC clusters. CONCLUSIONS: This model allows for the possibility that therapies can be developed against TGF-β1 signalling components and/or TGF-β1 target genes to suppress the metastatic potential of CTC clusters. Considering the negative impact that metastasis has on cancer prognosis and the lack of therapies against this process, interfering with the ability of CTC clusters to switch between cooperative and individual behaviours could provide new strategies to improve patient survival.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.100
GPT teacher head0.327
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 designSimulation or modeling
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

Citations9
Published2023
Admission routes2
Has abstractyes

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