A novel CpG‑based signature for survival prediction of lung adenocarcinoma patients

Zheng, Rongjiong; Xu, Haiqi; Mao, Wenjie; Du, Zhennan; Wang, Mingming; Hu, Meiling; Gu, Xiaolong

doi:10.3892/etm.2019.8200

Cited by 4 publications

(4 citation statements)

References 30 publications

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“…A special focus on DNA methylation alterations to develop the prognostic and predictive signatures for LUAD patients would be meaningful for survival prediction, guiding the personalized treatment decisions. Zheng et al [ 11 ] constructed a CpG-based signature for survival prediction of lung adenocarcinoma patients based on TCGA database. However, such studies were limited by either small sample size or lack of validation of the signature as an independent prognostic factor.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, researchers suggested an internal CpG-based signature for survival prediction of lung adenocarcinoma patients. These researches demonstrated that the methylation level is deemed a crucial molecular biomarker for the diagnosis and prognosis of LUAD patients [ 11 – 13 ]. However, limited by either the current expertise on the association between the epigenetic modifications and clinical outcomes or lack of independent validation as small sample size, the identification of a robust prognostic DNA methylation signature is of considerable importance for LUAD patients.…”

Section: Introductionmentioning

confidence: 99%

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A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

et al. 2021

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Background DNA methylation alteration is frequently observed in Lung adenocarcinoma (LUAD) and may play important roles in carcinogenesis, diagnosis, and prognosis. Thus, this study aimed to construct a reliable methylation-based nomogram, guiding prognostic classification screening and personalized medicine for LUAD patients. Method The DNA methylation data, gene expression data and corresponding clinical information of lung adenocarcinoma samples were extracted from The Cancer Genome Atlas (TCGA) database. Differentially methylated sites (DMSs) and differentially expressed genes (DEGs) were obtained and then calculated correlation by pearson correlation coefficient. Functional enrichment analysis and Protein-protein interaction network were used to explore the biological roles of aberrant methylation genes. A prognostic risk score model was constructed using univariate Cox and LASSO analysis and was assessed in an independent cohort. A methylation-based nomogram that included the risk score and the clinical risk factors was developed, which was evaluated by concordance index and calibration curves. Result We identified a total of 1362 DMSs corresponding to 471 DEGs with significant negative correlation, including 752 hypermethylation sites and 610 hypomethylation sites. Univariate cox regression analysis showed that 59 DMSs were significantly associated with overall survival. Using LASSO method, we constructed a three-DMSs signature that was independent predictive of prognosis in the training cohort. Patients in high-risk group had a significant shorter overall survival than patients in low-risk group classified by three-DMSs signature (log-rank p = 1.9E-04). Multivariate cox regression analysis proved that the three-DMSs signature was an independent prognostic factor for LUAD in TCGA-LUAD cohort (HR = 2.29, 95%CI: 1.47–3.57, P = 2.36E-04) and GSE56044 cohort (HR = 2.16, 95%CI: 1.19–3.91, P = 0.011). Furthermore, a nomogram, combining the risk score with clinical risk factors, was developed with C-indexes of 0.71 and 0.70 in TCGA-LUAD and GSE56044 respectively. Conclusions The present study established a robust three-DMSs signature for the prediction of overall survival and further developed a nomogram that could be a clinically available guide for personalized treatment of LUAD patients.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

et al. 2021

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“…DUSP26 contains a 600 bp CpG island situated 100bp of the transcriptional start site. Hypermethylation of this was observed in ovarian, neuroblastoma and brain cancer cell lines and is part of a CpG-based signature for lung adenocarcinoma and colorectal cancer [ 50 , 51 , 52 , 53 ]. Genome-wide single-nucleotide methylation profiling in HEK293 cells revealed that the DUSP26 promoter was methylated by TET dioxygenases [ 54 ].…”

Section: Regulation and Binding Partnersmentioning

confidence: 99%

A Review of DUSP26: Structure, Regulation and Relevance in Human Disease

Thompson

Stoker

2021

IJMS

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Dual specificity phosphatases (DUSPs) play a crucial role in the regulation of intracellular signalling pathways, which in turn influence a broad range of physiological processes. DUSP malfunction is increasingly observed in a broad range of human diseases due to deregulation of key pathways, most notably the MAP kinase (MAPK) cascades. Dual specificity phosphatase 26 (DUSP26) is an atypical DUSP with a range of physiological substrates including the MAPKs. The residues that govern DUSP26 substrate specificity are yet to be determined; however, recent evidence suggests that interactions with a binding partner may be required for DUSP26 catalytic activity. DUSP26 is heavily implicated in cancer where, akin to other DUSPs, it displays both tumour-suppressive and -promoting properties, depending on the context. Here we review DUSP26 by evaluating its transcriptional patterns, protein crystallographic structure and substrate binding, as well as its physiological role(s) and binding partners, its role in human disease and the development of DUSP26 inhibitors.

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“…Additionally, Zheng et al suggested an internal CpG-based signature for survival prediction of lung adenocarcinoma patients. Such researches demonstrate that the methylation level is deemed a crucial molecular biomarker for the diagnosis and prognosis of LUAD patients [11][12][13]. Despite these remarkable ndings, limited by either the current expertise on the association between the epigenetic modi cations and clinical outcomes or lack of independent validation as small sample size, there is a lack of a robust prognostic DNA methylation signature for LUAD.…”

Section: Introductionmentioning

confidence: 99%

A Methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

Wang

Zhou

Xia

et al. 2020

Preprint

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Background DNA methylation alteration is frequently observed in Lung adenocarcinoma (LUAD) and may play important roles in carcinogenesis, diagnosis, and prognosis. Thus, this study aimed to construct a reliable methylation-based nomogram, guiding prognostic classification screening and personalized medicine for LUAD patients. Method: The DNA methylation data, gene expression data and corresponding clinical information of lung adenocarcinoma samples were extracted from The Cancer Genome Atlas (TCGA) database. Differentially methylated sites (DMSs) and differentially expressed genes (DEGs) were obtained and then calculated expression correlation by pearson correlation coefficient. Functional enrichment analysis and Protein-protein interaction network were used to explore the biological roles of aberrant methylation genes. A prognostic risk score model was constructed using univariate Cox and LASSO analysis and was assessed in an independent cohort. A methylation-based nomogram that included the risk score and the clinical risk factors was developed, which was evaluated by concordance index and calibration curves. Result We identified a total of 1362 DMSs corresponding to 471 DEGs with significant negative correlation, including 752 hypermethylation sites and 610 hypomethylation sites. Univariate cox regression analysis showed that 59 DMSs were significantly associated with overall survival. Using LASSO method, we constructed a three-DMSs signature that was independent predictive of prognosis in the training cohort. Patients in high-risk group had a significant shorter overall survival than patients in low-risk group classified by three-DMSs signature (log-rank p = 1.9E-04). Multivariate cox regression analysis proved that the three-DMSs signature was an independent prognostic factor for LUAD in TCGA-LUAD cohort (HR = 2.29, 95%CI: 1.47–3.57, P = 2.36E-04) and GSE56044 cohort (HR = 2.16, 95%CI: 1.19–3.91, P = 0.011). Furthermore, a nomogram, combining the risk score with clinical risk factors, was developed with C-indexes of 0.71 and 0.70 in TCGA-LUAD and GSE56044 respectively. Conclusions The present study established a robust three-DMSs signature for the prediction of overall survival and further developed a nomogram that could be a clinically available guide for personalized treatment of LUAD patients.

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A novel CpG‑based signature for survival prediction of lung adenocarcinoma patients

Cited by 4 publications

References 30 publications

A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

A Review of DUSP26: Structure, Regulation and Relevance in Human Disease

A Methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

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