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Record W4312196389 · doi:10.3390/cells11244132

PCSK9 in Liver Cancers at the Crossroads between Lipid Metabolism and Immunity

2022· review· en· W4312196389 on OpenAlexafffund
Malak Alannan, Nabil G. Seidah, Aksam Merched

Bibliographic record

VenueCells · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversité de MontréalMontreal Clinical Research Institute
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsPCSK9Proprotein convertaseKexinBiologyLipid metabolismLDL receptorImmune systemCancer researchImmunologyCholesterolLipoproteinEndocrinology

Abstract

fetched live from OpenAlex

Metabolic rewiring and defective immune responses are considered to be the main driving forces sustaining cell growth and oncogenesis in many cancers. The atypical enzyme, proprotein convertase subtilisin/kexin type 9 (PCSK9), is produced by the liver in large amounts and plays a major role in lipid metabolism via the control of the low density lipoprotein receptor (LDLR) and other cell surface receptors. In this context, many clinical studies have clearly demonstrated the high efficacy of PCSK9 inhibitors in treating hyperlipidemia and cardiovascular diseases. Recent data implicated PCSK9 in the degradation of major histocompatibility complex I (MHC-I) receptors and the immune system as well as in other physiological activities. This review highlights the complex crosstalk between PCSK9, lipid metabolism and immunosuppression and underlines the latest advances in understanding the involvement of this convertase in other critical functions. We present a comprehensive assessment of the different strategies targeting PCSK9 and show how these approaches could be extended to future therapeutic options to treat cancers with a main focus on the liver.

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 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 score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.032
GPT teacher head0.294
Teacher spread0.262 · 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

Citations13
Published2022
Admission routes2
Has abstractyes

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