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Record W2314451628 · doi:10.1158/1940-6207.prev-10-a21

Abstract A21: Global DNA methylation analysis of bronchial epithelia of former smokers with COPD, with and without lung cancer

2010· article· en· W2314451628 on OpenAlexaff
Emily A. Vucic, Ian M. Wilson, Raj Chari, Jennifer Y. Kennett, Kim M. Lonergan, Stephen Lam, Wan L. Lam

Bibliographic record

VenueCancer Prevention Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsCOPDLung cancerDNA methylationMedicineEpigeneticsLungEpigenomicsCancerMethylationImmunologyCancer researchPathologyInternal medicineBiologyGeneGene expressionGenetics

Abstract

fetched live from OpenAlex

Abstract Introduction: Emerging evidence suggests that aberrant epigenetic regulation is involved in the development and progression of malignant and nonmalignant respiratory diseases, including chronic obstructive pulmonary disease (COPD) and lung cancer. Moreover, patients with COPD have an increased risk of developing lung cancer. Besides similar risk factors such as tobacco smoke exposure, little is known about the shared biology between COPD and lung cancer. Smoking causes aberrations in airway and lung parenchyma at both the genomic and epigenomic levels, resulting in global changes to gene expression. In this study, we hypothesize that alterations at the level of DNA methylation in airway epithelia of former smokers (FS) with COPD with and without non-small cell lung cancer (NSCLC) may be used to identify genes involved in the pathogenesis of these respiratory diseases, independent of the effects of active smoking. Methods: Bronchial epithelial cells were obtained from brushings of small airways (< 2 mm diameter) during bronchoscopy from FS with COPD (n=22), without COPD (n=22) and patients with COPD as well as previous surgical resection of Stage I NSCLC (n=6). Illumina's Infinium Methylation (HM27) assay was used to assess DNA methylation status of 27,578 CpG sites associated with 14,475 genes. Results: COPD patients are distinguished from non-COPD patients based on airway methylation profiles. Genes differentially methylated in airways between COPD and non-COPD patients include several modulators of aryl hydrocarbon receptor and IL6 signaling, as well as genes previously implicated in COPD, including immune chemotaxis regulators (CXCL11, CCR8) and GABA receptor signaling (GABRA5). Airway epithelial DNA from COPD patients with NSCLC compared to those without NSCLC was differentially methylated at sites encoding multiple key regulators of xenobiotic metabolism, regulators of free radical savaging/detoxification and retinol metabolic pathway components including several alcohol dehydrogenase, glutathione S transferase, and UDP glucoronosyltransferase genes. Conclusion: Our preliminary results suggest a role for DNA methylation in the deregulation of previously identified COPD-related genes, and specifically highlight differences in airways of COPD patients with/without NSCLC corresponding to well-known smoking-related metabolomic processes. Knowledge of DNA methylation disruption will further our understanding of the etiological role of COPD in the development of lung cancer, and contribute to the development of chemo-prevention strategies targeting the biology of both COPD and NSCLC. Supported by CIHR. Citation Information: Cancer Prev Res 2010;3(12 Suppl):A21.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.403
Teacher spread0.377 · 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 teacher head, 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
Published2010
Admission routes1
Has abstractyes

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