The role of proprotein convertases in cancer
Bibliographic record
Abstract
Cancer is a leading cause of death worldwide and accounts for about one fifth of all death in the Western world. In 2008, nearly 12.7 million new cancer cases and 7.6 million cancer deaths occurred worldwide. The development of cancer is a multistage process, during which cells acquire a series of mutations that eventually lead to unrestrained cell growth, evasion of cell death, angiogenesis, invasion of the surrounding tissue and finally spreading to other parts of the body. The mammalian proprotein convertases (PCs) constitute a family of nine secretory serine proteases that are related to bacterial subtilisin and yeast kexin. They have been associated with cancer since the early 1990s. By processing cancer-associated factors, PCs are believed to play key roles in almost every step of cancer development. Seven of these PCs (PC1, PC2, furin, PC4, PC5/6, PACE4 and PC7) activate, or less frequently inactivate, a wide variety of substrates, including hormones, growth factors, receptors, adhesion molecules, angiogenic factors, metalloproteases. Among these substrates, some of them are key factors controlling cancer progression and metastasis. The last member of this family proprotein convertase subtilisin kexin 9 (PCSK9) only cleaves itself and participates in maintaining the levels of cholesterol, which was shown to have impacts on cancer incidence.In this thesis, I focused on the role of two PCs, PC5/6 and PCSK9, in cancer development. I first showed that PC5/6 is systematically down-regulated in human and mice intestinal tumors. In ApcMin/+ mice which are a colonic cancer model and develop numerous adenocarcinomas along the intestinal tract, the specific knockout of PC5/6 in the intestine and colon leads to higher number of tumors, particularly in duodenum. This suggests that PC5/6 plays a protective role against tumorigenesis in the intestine. Although PC5/6 is protective in intestinal cancer, it has been shown to promote tumor progression in other cancer types e.g., brain and skin. Interestingly, PC5/6 is inhibited by some natural inhibitors, the latent TGFbeta binding proteins 2 and 3 (LTBP-2, -3). These two proteins reduce the enzymatic activity of PC5/6A and reduce the bio-availability of PC5/6A by sequestering the zymogen proPC5/6 in the extracellular matrix. Finally, I demonstrated that the lack of PCSK9 leads to a significantly lower level of liver metastasis of melanoma cells. This cancer protective effect is due to low plasma cholesterol levels as well as high apoptosis in liver stroma and metastasized tumors that are associated with PCSK9 deficiency.In summary, the present cumulative data define some of the in vivo roles of PC5/6 and PCSK9 in cancer and should enhance our appreciation of the physiological impact of PC inhibition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".