Comprendre les mécanismes d’action d’Hsp27 conduisant à la résistance à la castration des cancers de la prostate
Bibliographic record
Abstract
Une des strategies visant a ameliorer la therapie actuelle des cancers de la prostate resistants a la castration (CRPC) avances, implique le ciblage des genes de survie surexprimes afin de restaurer la sensibilite aux traitements. L’equipe d’accueil dirigee par le Dr. P. Rocchi a identifie la proteine Hsp27 comme etant surexprimee dans les CRPC. L’equipe a developpe un inhibiteur qui cible l'ARNm de cette proteine, un oligonucleotide antisens (ASO) de deuxieme generation (OGX-427, Apatorsen). Ce dernier est actuellement en essai clinique phase II au Canada et aux Etats-Unis. Pendant ma these, j’ai demontre que la Menine interagit avec Hsp27 et que sa surexpression est correlee a l’etat d’avancement de la maladie et au risque de recidive. J’ai developpe et brevete un oligonucleotide antisensinhibiteur de l’expression proteique de la Menine. J’ai demontre que cet inhibiteur provoque une diminution significative de la proliferation, une augmentation de l’apoptose et une chimiotherapie amelioree dans les modeles CRPC in vitro et in vivo chez la souris. En utilisant la technique d’immuno-precipitation de la chromatine « Chip-seq », j’ai demontre comment le gene suppresseur de tumeur (NEM1) peut se transformer en oncogene en CRPC. Ce travail a permis d’identifier les voies de signalisation essentielles de la progression des CRPC regulees par Menine tels que la proliferation, la migration, l’angiogenese et la resistance aux traitements. L’ensemble de mes travaux ont montre que l’inhibition de Menine par l’ASO est une approche therapeutique pertinente pour restaurer la sensibilite aux traitements des CRPC.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".