DNA methylation-driven genes for constructing diagnostic, prognostic, and recurrence models for hepatocellular carcinoma

Long, Junyu; Chen, Peipei; Lin, Jianzhen; Bai, Yi; Xu, Yang; Bian, Jin; Lin, Yu Hung; Wang, Dongxu; Yang, Xiaobo; Zheng, Yongchang; Sang, Xinting; Zhao, Hong

doi:10.7150/thno.31155

Cited by 112 publications

(92 citation statements)

References 66 publications

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“…Therefore, the methylation-driven genes could serve as attractive prognostic indicator in tumor patients. For example, Long et al used two DNA methylation-driven genes, SPP1 and LCAT, to construct two-gene signature which acted as an independent predictor for prognosis of liver cancer (Long et al, 2019). Methylated hub genes, including HOXD3, LAT, and NFE2L3, were proved to be a novel prognostic indicators in clear cell renal cell carcinoma (Wang et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Methylation-Driven Genes Identified as Novel Prognostic Indicators for Thyroid Carcinoma

Cao

et al. 2020

Front. Genet.

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Background: Aberrant DNA methylation plays an crucial role in tumorigenesis through regulating gene expression. Nevertheless, the exact role of methylation in the carcinogenesis of thyroid cancer and its association with prognosis remains unclear. The purpose of this study is to explore the DNA methylation-driven genes in thyroid cancer by integrative bioinformatics analysis. Methods: The transcriptome profiling data and DNA methylation data of thyroid cancer were downloaded from The Cancer Genome Atlas (TCGA) database. The methylmix R package was used to screen DNA methylation-driven genes in thyroid cancer. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted to annotate the function of methylation-driven genes. Univariate Cox regression analyses was performed to distinguish prognosis-related methylation-driven genes. Multivariate Cox regression analyses was utilized to build a prognostic multigene signature. A survival analysis was carried out to determine the individual prognostic significance of this multi-gene signature. Results: A total of 51 methylation-driven genes were identified. The functional analysis indicated that these genes were significantly enriched in diverse biological processes (BP) and pathways related to the malignancy processes. Four of these genes (RDH5, TREM1, BIRC7, and SLC26A7) were selected to construct the risk evaluation model. Patients in the low-risk group had an conspicuously better overall survival (OS) than those in high-risk group (p < 0.001). The area under the receiver operating characteristic (ROC) curve for this model was 0.836, suggesting a good specificity and sensitivity. Subsequent survival analysis revealed that this four-gene signature served as an independent indicator for the prognosis of thyroid cancer. Moreover, the prognostic signature was well validated in a external thyroid cancer cohort. Conclusion: We identified methylation-driven genes in thyroid cancer with independent prognostic value, which may offer new insight into molecular mechanisms of thyroid cancer and provide new possibility for individualized treatment of thyroid cancer patients.

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Section: Discussionmentioning

confidence: 99%

Methylation-Driven Genes Identified as Novel Prognostic Indicators for Thyroid Carcinoma

Cao

et al. 2020

Front. Genet.

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“…75, 0.77 and 0.77 for the 0.5-, 1-, 3-and 4-year survival times ( Figure 4D). Meanwhile, we attempted to compare the hypoxia-related signature with other prognostic models published previously [26,27]. For the hypoxia-related signature, methylation-driven prognostic model and three-gene prognostic model, the AUCs was 0.78, 0.67 and 0.67 in TCGA cohort and 0.75, 0.64 and 0.64 in ICGC cohort, respectively ( Figure S2).…”

Section: Construction and Validation Of A Hypoxia-related Prognosis Smentioning

confidence: 99%

A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients.

Zhang

Tang

Gao

et al. 2020

Preprint

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BackgroundHypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism.MethodsDifferentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival（OS）were identified using Cox regression and LASSO analysis. Then the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. The Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature. CIBERSORT was used for estimating the fractions of immune cell types.ResultsA total of 397 hypoxia-related DEGs in HCC were detected and three genes (PDSS1, CDCA8 and SLC7A11) among them were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response. Meanwhile, the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1.ConclusionsAltogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.

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“…The MethylMix R package was employed for analysis that integrated DNA methylation data for 117 LSCC samples and 16 normal samples and paired gene expression data for 111 LSCC samples to appraise DNA methylation events that have a significant impact on the expression of the corresponding gene, indicating that the gene is a DNA methylation-driven gene (MDG). A total of three procedures of MethylMix analysis were described as previous studies [9].In addition, the differential methylation value where gene with a positive differential methylation value signifies hypermethylation and gene with a negative differential methylation value signifies hypomethylation can be applied in subsequent analysis.…”

Section: Identification Of Dna Methylation-driven Genesmentioning

confidence: 99%

Development and validation of epigenetic signature predict survival for patients with laryngeal squamous cell carcinoma

Cui

Wang

Zhong

et al. 2020

Preprint

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Background: Epigenetic alterations, such as DNA methylation patterns, yield an important role in the initiation, progression and prognosis of laryngeal squamous cell carcinoma (LSCC). We performed a genome-wide integrated analysis of methylation and the transcriptome to establish epigenetic signature to improve the accuracy of survival prediction and optimize therapeutic strategies for LSCC.Methods: LSCC DNA methylation datasets and RNA sequencing (RNA-seq) datasets were acquired from the Cancer Genome Atlas (TCGA). MethylMix was applied to detect DNA methylation-driven genes (MDGs). By univariate and multivariate Cox regression analyses, five genes of DNA MDGs was developed an epigenetic signature. The predictive accuracy and clinical value of the epigenetic signature were evaluated by receiver operating characteristic (ROC) and decision curve analysis (DCA), and compared with TNM stage system. Additionally, prognostic value of the epigenetic signature was validated by external Gene Expression Omnibus (GEO) database. According to 5 MDGs of epigenetic signature, the candidate small molecules for LSCC were screen out by the CMap database.Results: A total of 88 DNA MDGs were identified, five of which (MAGEB2, SUSD1, ZNF382, ZNF418 and ZNF732) were chosen to construct an epigenetic signature. The epigenetic signature can effectively divide patients into high-risk and low-risk group, with the area under curve (AUC) of 0.8 (5-year OS) and AUC of 0.745 (3-year OS). Stratification analysis affirmed that the epigenetic signature was still a significant statistical prognostic model in subsets of patients with different clinical variables. Multivariate Cox regression analysis indicated the efficacy of epigenetic signature appears independent of other clinicopathological characteristics. In terms of predictive capacity and clinical usefulness, the epigenetic signature was superior to traditional TNM stage. Additionally, the epigenetic signature was confirmed in external LSCC cohorts from GEO. Finally, CMap matched the 10 most significant small molecules as promising therapeutic drugs to reverse the LSCC gene expression.Conclusion: An epigenetic signature, with five DNA MDGs, was identified and validated in LSCC patients by integrating multidimensional genomic data. Compared TNM stage alone, it generates more accurate estimations of the survival probability and maybe offer novel research directions and prospects for individualized treatment of patients with LSCC.

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DNA methylation-driven genes for constructing diagnostic, prognostic, and recurrence models for hepatocellular carcinoma

Cited by 112 publications

References 66 publications

Methylation-Driven Genes Identified as Novel Prognostic Indicators for Thyroid Carcinoma

Methylation-Driven Genes Identified as Novel Prognostic Indicators for Thyroid Carcinoma

A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients.

Development and validation of epigenetic signature predict survival for patients with laryngeal squamous cell carcinoma

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