MétaCan
Menu
Back to cohort
Record W4362544237 · doi:10.1158/1538-7445.am2023-3708

Abstract 3708: Platelet-derived microparticles modulate breast cancer malignant processes

2023· article· en· W4362544237 on OpenAlexaff
Vanessa Veilleux, Nicolas Pichaud, Luc H. Boudreau, Gilles A. Robichaud

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsBreast cancerCancerMetastasisMalignancyInternalizationCancer researchCancer cellMedicinePlatelet activationPlateletMitochondrionMetastatic breast cancerImmunologyBiologyPathologyInternal medicineCell biologyReceptor

Abstract

fetched live from OpenAlex

Abstract Breast cancer is one of the leading causes of morbidity and mortality among women, where metastasis accounts for the majority of deaths associated with this disease. Thus, the potential to effectively target tumor malignancy offers hope to mitigate disease progression and improve patient outcomes. It is well established that platelets promote multiple processes of metastasis cascade. Recently, platelets have received new attention for their impact in cancer through the production of platelet-derived microparticles (PMPs). Interestingly, PMPs allow intercellular exchange and trafficking of bioactive material through the internalization of these vesicles into recipient cells. As a result, the delivery of the intravesicular cargo can modulate signaling and activation processes of recipient cells. We recently identified a new subpopulation of these vesicles (termed mitoMPs) containing functional mitochondria. Given the predominant role of mitochondria in cancer malignancy, we believe that mitoMPs provide an important source of foreign mitochondria to support recipient breast cancer cells in malignancy and disease progression. We therefore set out to study the impact of mitoMPs on breast cancer metabolic and phenotypic processes involved in metastasis. Technically, PMPs were generated and purified from human blood platelets and co-incubated with various breast cell models (MB231, MCF7 and MCF10A). The physiological significance of mitoMPs in breast cancer disease was then assessed using various cellular and molecular assays. We demonstrate that the level of PMP internalization is highly dependent upon the type of breast cancer recipient cells. Furthermore, we show that the cargo of mitoMPs (notably mitochondria) is biologically active where recipient breast cancer cells acquired mitochondria-dependent functions, such as increased oxygen consumption rates and intracellular ATP production. Finally, we observe that mitoMPs promote malignant features such as cancer cell migration and invasion. Overall, we demonstrate that PMPs can modulate cancer cell activation and behaviour. These findings provide a better understanding of the extracellular tumor environment and the contribution of mitoMPs in supporting breast cancer cells through the metastatic landscape. The knowledge gained will further provide new avenues for therapeutic strategies in breast cancer patients. Citation Format: Vanessa Veilleux, Nicolas Pichaud, Luc H. Boudreau, Gilles A. Robichaud. Platelet-derived microparticles modulate breast cancer malignant processes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3708.

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: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.001

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 head0.049
GPT teacher head0.373
Teacher spread0.323 · 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
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicExtracellular vesicles in diseaseFrench-language works237,207