Abstract LB-346: A novel lung tumor suppressor implicated in somatic and familial cancers
Bibliographic record
Abstract
Abstract Background: Lung cancer (LC) is the most common cause of cancer death worldwide. Previous familial linkage studies have identified a tumor suppressor locus on 6q23-25. However, no single gene has yet been implicated within this 30 Mb region. Discovering the genetic and epigenetic events that affect LC risk and development will lead to better methods for risk assessment, early detection and treatment. Methods: Genome-wide genes disrupted by two-hit inactivation were identified by combining gene dosage, DNA methylation, and gene expression assays for a group of lung adenocarcinomas (AC) and adjacent non-malignant tissues. Gene expression, DNA hypermethylation and/or copy number aberrations were validated in data from AC, squamous cell carcinoma (SqCC), and pre-malignant lesions by querying other cohorts using gene-specific and whole-genome approaches. The role of DNA methylation in gene silencing was assessed using inhibition of DNMT by 5′-azacytidine. The association of allelic variants with LC risk was investigated in 193 familial LC cases and 213 controls collected by the Genetic Epidemiology of Lung Cancer Consortium (GELCC) using a Cochrane-Armitage trend test. The association of gene expression with prognosis was performed on public data using a Mantel-Cox log test. Stable mRNA knock-downs were generated using lentiviral delivery of a gene-specific shRNA, and apoptotic cells were counted using Annexin5/propidium iodide staining. Results: Integration of AC gene dosage, DNA methylation and mRNA expression showed EYA4 to be frequently affected by two-hits and significantly down-regulated. Quantitative PCR techniques confirmed that EYA4 was hypermethylated (46%) and down-regulated (72%), validating our microarray results. A direct link between EYA4 methylation and expression was verified by restoration of expression after 5′-azacytidine treatment in methylated cell lines. Congruent with EYA family member function, in vitro assays revealed that EYA4 knock-down cells displayed a decrease in the number of apoptotic cells - a hallmark of cancer. Further investigations led to the discovery of frequent EYA4 disruption in SqCC and pre-neoplastic tissue. The GELCC dataset was examined to assess EYA4 allelotype association with familial risk. Doing so revealed that numerous EYA4 variants are associated with increased risk. Finally, the association of EYA4 expression with survival was investigated along with other somatically altered genes at 6q23-25. Of these genes, low EYA4 expression was found to be the most significantly associated with poor prognosis. Conclusions: EYA4 is a frequently disrupted gene that maps to a locus previously associated with cancer risk. It is implicated in somatic as well as familial cancers, and is likely a tumor suppressor gene with apoptotic functions. The direct association of EYA4 with risk and survival underscores its relevance on a clinical level. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-346.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".