MétaCan
Menu
← Back to cohort
Record W7033792942

The role of proprotein convertases in cancer

2013· dissertation· en· W7033792942 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsProprotein ConvertasesCancerKexinFurinProprotein convertaseCancer cellProteasesPancreatic cancer
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.019
GPT teacher head0.290
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueeScholarship@McGill (McGill)→Same topicSport and Mega-Event Impacts→French-language works237,207→