Proprotein Convertase Subtilisin Kexin 9 (PCSK9) Inhibitors in the Treatment of Hypercholesterolemia and other Pathologies
Bibliographic record
Abstract
The discovery of PCSK9 in 2003 and its identification as the third protagonist responsible for ADH opened many new avenues of research in the cardiovascular field. Liver PCSK9 binds the LDLR and promotes its degradation in the endosomal/lysosomal pathway. A higher activity of PCSK9 leads to lower liver LDLR levels, resulting in a reduction in LDL-uptake from circulation, and thus in hypercholesterolemia and associated atherosclerosis. Although PCSK9 mutations are rare, their associated phenotypes can be devastating. The most powerful PCSK9 gain-of-function mutation, D374Y, is responsible for LDL cholesterol (LDLc) levels of ~10 mmol/L versus ~3 mmol/L in normal subjects.The aim of this manuscript is to review the available literature on the identification and pharmacological applications of potent inhibitors of PCSK9 function and/or activity, and to present the latest data on the ongoing clinical trials, mostly related to the use of monoclonal antibodies (mAb) that interfere with PCSK9 function on the LDLR, resulting in a significant drop in circulating LDLc.The clinical data, so far, are very encouraging with Phase-2 trials from various pharmaceutical companies showing a drop of >60% in LDLc for at least 2 weeks after a single injection of a humanized PCSK9 mAb in the presence or absence of adjunct statin therapy. In view of the absence of overt toxicity associated with this treatment Phase-3 clinical trials have started with >20,000 individuals being tested and anticipated primary outcomes results should be forthcoming by 2016. Other approaches including the use of recombinant adnectins, antisense RNAi or small molecule inhibitors are also undergoing early pre-clinical testing or are already in Phase-1 clinical trials.Very recent data revealed that absence of PCSK9 can be protective against melanoma invasion in mouse liver, and that this is due to lower circulating LDLc. This opens the door to novel applications of PCSK9 inhibitors/silencers in cancer/metastasis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".