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Abstract LB-146: A study of p16 inactivation in lung cancer cell lines and tumor samples with a meta-analysis of the literature

2012· article· en· W2328077432 on OpenAlexaff
Kit Tam, Wei Zhang, Junichi Soh, Min Chen, Han Sun, Victor Stastny, Kelsie L. Thu, Wan L. Lam, Adi F. Gazdar

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsKRASMethylationAdenocarcinomaLung cancerMutationCancer researchBiologyCancerMeta-analysisOncologyGeneticsMedicineInternal medicineGene

Abstract

fetched live from OpenAlex

Abstract Introduction: p16 inactivation is a common genetic alteration in lung adenocarcinoma and is often inactivated by homozygous deletion (HD) or methylation of promoter, or rarely by point mutation. While p16 methylation was reported to be linked to KRAS mutation and smoking, the association between specific p16 inactivation mechanism and other common genetic changes and smoking status remains controversial. In this study, we examined all of the three p16 inactivation mechanisms and correlated them with other common genetic chanes in lung adenocarcinoma: EGFR, KRAS, and LKB1, and smoking status. We also performed a meta-analysis to study the effect of smoking on p16 inactivation. Methods: We examined 40 cell lines and 45 tumor samples from patients with primary NSCLC, mostly adenocarcinoma. SNP and qPCR were used to detect HD. Methylation was determined by MSP analysis and mutation was identified by sequencing. We performed the meta-analysis by using Woolf's test to identify heterogeneity and followed by using a random-effect model. Results: The cell lines and tumor samples demonstrated similar results. No statistical differences were found between the two groups and the data were hence combined for analysis. p16 inactivation occurred at similar frequencies (54-57%) regardless of mutational status of EGFR, KRAS and LKB1 but the major mechanism of inactivation varied. Multivariate analysis showed that LKB1 inactivation was associated with p16 HD; p16 methylation was linked to KRAS mutation but was mutually exclusive with EGFR mutation. No significant association was established between any p16 inactivation mechanism and smoking status based on our data. HD was found to be the major mechanism of p16 inactivation among both smokers and never smokers although the rate of p16 methylation was higher in smokers. The result of our meta-analysis showed that p16 methylation was associated with smoking. The results from the literature were homogenous and the overall odds ratio from the meta-analysis was 2.01, which is significant at 0.05 level. Conclusions: p16 inactivation is a common event in lung adenocarcinoma and the inactivation mechanism of p16 is associated with other genetic changes and smoking status. Meta-analysis confirmed the association between p16 methylation and smoking. Our results indicate the presence of different pathways via p16 inactivation in the development of lung adenocarcinoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-146. doi:1538-7445.AM2012-LB-146

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)0.016
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.041
Bibliometrics0.0070.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.098
GPT teacher head0.416
Teacher spread0.318 · 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.

Study designMeta-analysis
DomainMethods
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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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