PCSK9 in Liver Cancers at the Crossroads between Lipid Metabolism and Immunity
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".