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Record W4386474194 · doi:10.1126/sciadv.adh2023

Loss of attachment promotes proline accumulation and excretion in cancer cells

2023· article· en· W4386474194 on OpenAlexaff
Steven E. Pilley, Marc Hennequart, Anke Vandekeere, Julianna Blagih, Nathalie Legrave, Sarah‐Maria Fendt, Karen H. Vousden, Christiaan F. Labuschagne

Bibliographic record

VenueScience Advances · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsHôpital Maisonneuve-Rosemont
FundersMedical Research CouncilFrancis Crick InstituteCancer Research UKWellcome Trust
KeywordsProlineSecretionAmino acidExtracellularExtracellular matrixStromal cellCancer cellChemistryCell biologyBiochemistryBiologyCancerCancer research

Abstract

fetched live from OpenAlex

Previous studies have revealed a role for proline metabolism in supporting cancer development and metastasis. In this study, we show that many cancer cells respond to loss of attachment by accumulating and secreting proline. Detached cells display reduced proliferation accompanied by a general decrease in overall protein production and de novo amino acid synthesis compared to attached cells. However, proline synthesis was maintained under detached conditions. Furthermore, while overall proline incorporation into proteins was lower in detached cells compared to other amino acids, there was an increased production of the proline-rich protein collagen. The increased excretion of proline from detached cells was also shown to be used by macrophages, an abundant and important component of the tumor microenvironment. Our study suggests that detachment induced accumulation and secretion of proline may contribute to tumor progression by supporting increased production of extracellular matrix and providing proline to surrounding stromal cells.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.353
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations23
Published2023
Admission routes1
Has abstractyes

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