| 1. |
- Chen, Chao, et al.
(författare)
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Epigenome-wide gene-age interaction analysis reveals reversed effects of PRODH DNA methylation on survival between young and elderly early-stage NSCLC patients
- 2020
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Ingår i: Aging. - : Impact Journals, LLC. - 1945-4589. ; 12:11, s. 10642-10662
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Tidskriftsartikel (refereegranskat)abstract
- DNA methylation changes during aging, but it remains unclear whether the effect of DNA methylation on lung cancer survival varies with age. Such an effect could decrease prediction accuracy and treatment efficacy. We performed a methylation-age interaction analysis using 1,230 early-stage lung adenocarcinoma patients from five cohorts. A Cox proportional hazards model was used to investigate lung adenocarcinoma and squamous cell carcinoma patients for methylation-age interactions, which were further confirmed in a validation phase. We identified one adenocarcinoma-specific CpG probe, cg14326354PRODH, with effects significantly modified by age (HRinteraction = 0.989; 95% CI: 0.986-0.994; P = 9.18×10-7). The effect of low methylation was reversed for young and elderly patients categorized by the boundary of 95% CI standard (HRyoung = 2.44; 95% CI: 1.26-4.72; P = 8.34×10-3; HRelderly = 0.58; 95% CI: 0.42-0.82; P = 1.67×10-3). Moreover, there was an antagonistic interaction between low cg14326354PRODH methylation and elderly age (HRinteraction = 0.21; 95% CI: 0.11-0.40; P = 2.20×10-6). In summary, low methylation of cg14326354PRODH might benefit survival of elderly lung adenocarcinoma patients, providing new insight to age-specific prediction and potential drug targeting.
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| 2. |
- Dong, Xuesi, et al.
(författare)
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Trans-omics biomarker model improves prognostic prediction accuracy for early-stage lung adenocarcinoma
- 2019
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Ingår i: Aging. - : Impact Journals, LLC. - 1945-4589. ; 11:16, s. 6312-6335
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Tidskriftsartikel (refereegranskat)abstract
- Limited studies have focused on developing prognostic models with trans-omics biomarkers for early-stage lung adenocarcinoma (LUAD). We performed integrative analysis of clinical information, DNA methylation, and gene expression data using 825 early-stage LUAD patients from 5 cohorts. Ranger algorithm was used to screen prognosis-associated biomarkers, which were confirmed with a validation phase. Clinical and biomarker information was fused using an iCluster plus algorithm, which significantly distinguished patients into high- and low-mortality risk groups (Pdiscovery = 0.01 and Pvalidation = 2.71×10-3). Further, potential functional DNA methylation-gene expression-overall survival pathways were evaluated by causal mediation analysis. The effect of DNA methylation level on LUAD survival was significantly mediated through gene expression level. By adding DNA methylation and gene expression biomarkers to a model of only clinical data, the AUCs of the trans-omics model improved by 18.3% (to 87.2%) and 16.4% (to 85.3%) in discovery and validation phases, respectively. Further, concordance index of the nomogram was 0.81 and 0.77 in discovery and validation phases, respectively. Based on systematic review of published literatures, our model was superior to all existing models for early-stage LUAD. In summary, our trans-omics model may help physicians accurately identify patients with high mortality risk.
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| 3. |
- Ji, Xinyu, et al.
(författare)
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Epigenetic–smoking interaction reveals histologically heterogeneous effects of TRIM27 DNA methylation on overall survival among early-stage NSCLC patients
- 2020
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Ingår i: Molecular Oncology. - : Wiley. - 1574-7891 .- 1878-0261. ; 14:11, s. 2759-2774
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Tidskriftsartikel (refereegranskat)abstract
- Tripartite motif containing 27 (TRIM27) is highly expressed in lung cancer, including non-small-cell lung cancer (NSCLC). Here, we profiled DNA methylation of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tumours from 613 early-stage NSCLC patients and evaluated associations between CpG methylation of TRIM27 and overall survival. Significant CpG probes were confirmed in 617 samples from The Cancer Genome Atlas. The methylation of the CpG probe cg05293407TRIM27 was significantly associated with overall survival in patients with LUSC (HR = 1.65, 95% CI: 1.30–2.09, P = 4.52 × 10−5), but not in patients with LUAD (HR = 1.08, 95% CI: 0.87–1.33, P = 0.493). As incidence of LUSC is associated with higher smoking intensity compared to LUAD, we investigated whether smoking intensity impacted on the prognostic effect of cg05293407TRIM27 methylation in NSCLC. LUSC patients had a higher average pack-year of smoking (37.49LUAD vs 54.79LUSC, P = 1.03 × 10−19) and included a higher proportion of current smokers than LUAD patients (28.24%LUAD vs 34.09%LUSC, P = 0.037). cg05293407TRIM27 was significantly associated with overall survival only in NSCLC patients with medium–high pack-year of smoking (HR = 1.58, 95% CI: 1.26–1.96, P = 5.25 × 10−5). We conclude that cg05293407TRIM27 methylation is a potential predictor of LUSC prognosis, and smoking intensity may impact on its prognostic value across the various types of NSCLC.
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| 4. |
- Zhang, Ruyang, et al.
(författare)
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EGLN2 DNA methylation and expression interact with HIF1A to affect survival of early-stage NSCLC
- 2019
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Ingår i: Epigenetics. - : Informa UK Limited. - 1559-2294 .- 1559-2308. ; 14:2, s. 118-129
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Tidskriftsartikel (refereegranskat)abstract
- Hypoxia occurs frequently in human cancers and promotes stabilization and activation of hypoxia inducible factor (HIF). HIF-1α is specific for the hypoxia response, and its degradation mediated by three enzymes EGLN1, EGLN2 and EGLN3. Although EGLNs expression has been found to be related to prognosis of many cancers, few studies examined DNA methylation in EGLNs and its relationship to prognosis of early-stage non-small cell lung cancer (NSCLC). We analyzed EGLNs DNA methylation data from tumor tissue samples of 1,230 early-stage NSCLC patients, as well as gene expression data from The Cancer Genome Atlas. The sliding windows sequential forward feature selection method and weighted random forest were used to screen out the candidate CpG probes in lung adenocarcinomas (LUAD) and lung squamous cell carcinomas patients, respectively, in both discovery and validation phases. Then Cox regression was performed to evaluate the association between DNA methylation and overall survival. Among the 34 CpG probes in EGLNs, DNA methylation at cg25923056EGLN2 was identified to be significantly associated with LUAD survival (HR = 1.02, 95% CI: 1.01–1.03, P = 9.90 × 10–5), and correlated with EGLN2 expression (r =–0.36, P = 1.52 × 10–11). Meanwhile, EGLN2 expression was negatively correlated with HIF1A expression in tumor tissues (r =–0.30, P = 4.78 × 10–8) and significantly (P = 0.037) interacted with HIF1A expression on overall survival. Therefore, DNA methylation of EGLN2- HIF1A is a potential marker for LUAD prognosis and these genes are potential treatment targets for further development of HIF-1α inhibitors in lung cancer therapy.
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| 5. |
- Zhang, Ruyang, et al.
(författare)
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Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects
- 2020
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Ingår i: Chest. - : Elsevier BV. - 0012-3692. ; 158:2, s. 808-819
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Tidskriftsartikel (refereegranskat)abstract
- Background: DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions. Research Question: Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis? Study Design and Methods: Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated. Results: Twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10–17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10–18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC3 year, 0.88 [95% CI, 0.83-0.93]; and AUC5 year, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively. Interpretation: The integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.
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