Genomic adaptation to disease: A role for DNA demethylation of microRNA regulation in cancer and chronic neuropathic pain
Notice bibliographique
Résumé
Cancer and chronic pain are two common pathologies affecting millions of patients worldwide. Much like most other disease states, they can be determined genetically, environmentally, or both. Unlike the static genome, the epigenome is responsible for interpreting environmental interactions and is often altered in disease states. A subset of epigenetic modifications, known as DNA methylation, is capable of mediating gene silencing. In this thesis, two cases will be explored probing the nature of DNA methylation in cancer and in peripheral neuropathy. Aberrant DNA methylation is a common hallmark of cancer often resulting in the methylation of tumor suppressors and the demethylation of oncogenes. The identity of a DNA methylase, however, remains elusive. One candidate, methyl binding domain 2 (MBD2), has been previously characterized as a demethylase and also functions as a transcriptional repressor. One possible explanation for its role as a repressor may involve the direct activation of a repressor which can then mediate silencing. An attractive class of genes for this model are microRNAs, which are capable of binding several targets in the cell and mediate their silencing. We therefore test the hypothesis that MBD2 is capable of activating a microRNA which is capable of negatively-regulating target genes. In this thesis, we delineate mechanisms that demonstrate MBD2 is capable of binding a microRNA, mir-496, which is then capable of inducing itsiactivation. We further show that mir-496 can mediate a repressive action on three separate genes in the cell that have tumor suppressive roles in cancer. Chronic pain has been shown to alter gene expression and brain anatomy and is often accompanied with comorbidities that affect cognitive processing, sleep and anxiety. Interestingly, these changes have been shown to be reversible following effective treatment of pain, suggesting the mechanisms behind pain may also be reversible, thus prompting the study of pain epigenetics. We therefore proposed to test the hypothesis that the methylome and transcriptome are altered in the brain following peripheral nerve injury. We were able to identify a signature of DNA methylation and transcription specific to the prefrontal cortex and amygdala that accompanied peripheral nerve injury and behavioral signs of neuropathy. Furthermore we were able reverse behavioral signs of neuropathic pain and altered methylation states in the prefrontal cortex with environmental enrichment, demonstrating their reversible nature. Taken together, this thesis explores the role of DNA methylation in two complex diseases: through small scale processes in cancer and through broader changes at the level of the methylome and transcriptome in chronic pain. In identifying these molecular pathways and signatures, we hope to improve the mechanistic understanding of these pathologicaliistates, ultimately resulting in better treatment outcomes for millions of patients worldwide.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».