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Record W7066159079

Genomic adaptation to disease: A role for DNA demethylation of microRNA regulation in cancer and chronic neuropathic pain

2013· dissertation· en· W7066159079 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersNational Institute on Drug AbuseMcGill University Health CentreCanadian Institutes of Health ResearchScheme for Promotion of Academic and Research CollaborationNational Institutes of HealthMcGill University
KeywordsDNA methylationEpigeneticsmicroRNAEpigenomeCancerGeneDemethylaseDNA demethylationRepressor
DOInot available

Abstract

fetched live from OpenAlex

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.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.255
Teacher spread0.241 · 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 designObservational
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

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