Mechanisms of oncogene induced senescence in MAPK- driven cancer development
Notice bibliographique
Résumé
Cancer is caused by the accumulation of genetic mutations that promote the abnormal growth of cells.Oncogene Induced Senescence (OIS), a tumour suppressive mechanism, provides a robust barrier to proliferation promoted by commonly mutated oncogenes, such as Raf or Ras, and the bypass of this barrier is a critical event on the path to malignancy.The mechanisms involved in OIS bypass are not yet fully understood.Many questions remain such as whether the timing of genetic mutations is relevant, whether additional mutations can permit escape from OIS, what cellular processes are required to establish OIS, and how senescent tumour cells can contribute to the tissue microenvironment.Using a Flp-activated Braf allele paired with a Cre-conditionally null p53 allele, p53 was ablated at six independent timepoints following the initiation of Braf V600E lung adenomas in the mouse lung, allowing for temporal dissection of tumour progression and OIS.Using this dualrecombinase system, it was determined that p53 loss after OIS is established is not sufficient to permit malignant adenocarcinoma (LUAD) development.Braf V600E adenomas are stably restrained from malignancy by OIS by approximately 24 weeks after Braf V600E expression, and several senescence and SASP markers can be detected in those adenomas.Interestingly, the length of time until OIS establishment could be modulated by the initiating viral titres of adenoviral-Flp.Lower initiating adenoviral titre produced lower tumour density in the lung that was correlated with smaller, more proliferative tumours.Lower-density tumour environments also permitted bypass of OIS and LUAD development at 24-32 weeks, suggesting that higher proliferation is due to delay in OIS.mutations in MAPK-related factors.Elucidating the mechanisms underlying the establishment and maintenance of OIS will help us understand how cells might bypass or reverse these intrinsic barriers to become malignant.In addition, many common cancer chemotherapies induce senescence in tumour cells, making understanding senescence critical to the clinic (Ewald et al., 2010).In particular, this work helps to uncover the mechanisms that underlie OIS using both in vivo mouse models and an in vitro genetic screen. CancerOverview Cancer is a disease resulting from unrestricted cell proliferation or survival caused by genetic mutations.Cancerous cells acquire a number of common characteristics described by Hanahan & Weinberg in 2000 as the "Hallmarks of Cancer", which are: sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis (Hanahan and Weinberg, 2000).Mutations underlying cancer development fall into two general categories: oncogenes, and tumour suppressor genes (TSGs).Typically, as tumours evolve, they accumulate mutations in a stepwise fashion, leading to an increasingly aggressive disease (Fearon and Vogelstein, 1990;Arends, 2000;McGranahan and Swanton, 2017).The large diversity of cancer types and aggressiveness can be partially attributed to the variety of different genetic mutations that can cause cancer, as well as the underlying genetic instability of cancer that contributes to these hallmark characteristics (Negrini et al., 2010;McGranahan and Swanton, 2017).
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».