Dataset Information

A DNA methylation signature to improve survival prediction of gastric cancer.

ABSTRACT: BACKGROUND:The current Union International Committee on Cancer or the American Joint Committee on Cancer TNM stage system has shown valuable but insufficient estimation for subsets of gastric cancer and prediction for prognosis patients. Thus, there is an urgent need to identify diagnostic, prognostic, and predictive biomarkers to improve patients' outcomes. Our aim was to perform an integrative analysis on publicly available datasets to identify epigenetic changes that may play key role in the initiation and progression of gastric cancer, based on which we set to develop a DNA methylation signature to improve survival prediction of gastric cancer. RESULTS:A total of 340 methylation-related differentially expression genes (mrDEGs) were screened in gastric cancer patients from The Cancer Genome Atlas (TCGA) project. Pathway enrichment analysis revealed that they were involved in the biological process related to initiation and progression of gastric cancer. Based on the mrDEGs identified, we developed a DNA methylation signature consisting of ten gene members (SCNN1B, NFE2L3, CLDN2, RBPMS2, JPH2, GBP6, COL4A5, SMKR1, PPP1R14A, and ARL4D) according to their methylation ? value. This innovative DNA methylation signature was associated with cancer recurrence, while it showed independence of cancer recurrence and TNM stage for survival prediction. Combination of this DNA methylation signature and TNM stage improved overall survival prediction in the receiver operating characteristic analysis. We also verified that two individual genes (PPP1R14A and SCNN1B) of the identified prognostic signature were regulated by promoter region methylation in a panel of gastric cell lines. CONCLUSIONS:This study presents a powerful DNA methylation signature by performing analyses integrating multi-source data including transcriptome, methylome, and clinical outcome of gastric cancer patients from TCGA. The identified DNA methylation signature may be used to refine the current prognostic model and facilitate further stratification of patients in the future clinical trials. Further experimental studies are warranted to unveil the regulatory mechanism and functional role of all the individual genes of the DNA methylation signature. Also, clinical investigations in large GC patient cohorts are greatly needed to validate our findings.

SUBMITTER: Peng Y

PROVIDER: S-EPMC6972030 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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A DNA methylation signature to improve survival prediction of gastric cancer.

Peng Yaojun Y Wu Qiyan Q Wang Lingxiong L Wang Huan H Yin Fan F

Clinical epigenetics 20200120 1

<h4>Background</h4>The current Union International Committee on Cancer or the American Joint Committee on Cancer TNM stage system has shown valuable but insufficient estimation for subsets of gastric cancer and prediction for prognosis patients. Thus, there is an urgent need to identify diagnostic, prognostic, and predictive biomarkers to improve patients' outcomes. Our aim was to perform an integrative analysis on publicly available datasets to identify epigenetic changes that may play key role ...[more]

PMID: 31959204

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Project description:BackgroundLong noncoding RNAs (lncRNAs) are versatile in functions and can regulate cancer development, including the modulation of cancer immunity. Immune-related lncRNA signatures predicting prognosis have been reported in multiple cancers, but relevant studies in gastric cancer (GC) are still lacking.MethodsWe performed a comprehensive analysis using TCGA and Immport databases and identified an immune-related lncRNA signature by univariate and multivariate Cox regression analysis. qRT-PCR and immunohistochemistry assays were used for further validation. KEGG and GO analysis and ceRNA network establishment were carried out to explore the regulatory functions.ResultsWe first identified an immune-related lncRNA signature, which can stratify gastric cancer patients into high- and low-risk subgroups and the high-risk cases frequently suffered from shorter overall survival time. Next, we validated the reliability of the lncRNA signature in an independent 75 gastric cancer samples and demonstrated that the three-year survival rate in high-risk patients was only 30.8% versus 66.5% in low-risk counterparts. Functional exploration indicated that the lncRNA signature might participate in multiple cancer-associated processes including cell adhesion and migration, cytokine-receptor interaction and immune evasion. Additionally, we observed that high-risk samples tended to form an immunosuppressive microenvironment, which had more M2-polarized macrophages and Tregs, but fewer CD8 effector T cells within tumors. Moreover, we found that PD-1 and PD-L1 were dramatically upregulated in a subset of high-risk patients with abundant M2 and Treg infiltration, implying these patients may benefit from anti-PD-1 and PD-L1 immunotherapy.ConclusionsThese results showed that the immune-related lncRNA signature had a prominent capacity to predict overall survival and the immune status of microenvironment in gastric cancer. Our findings may be useful for the risk-stratification management and provide a valuable clue to identify proper patients potentially benefit from immune checkpoint therapy in gastric cancer.

Project description:BackgroundA major challenge in stage II colorectal carcinoma is to identify patients with increased risk of recurrence. Biomarkers that distinguish patients with poor prognosis from patients without recurrence are currently lacking. This study aims to develop a robust DNA methylation classifier that allows the prediction of recurrence and chemotherapy benefit in patients with stage II colorectal cancer. We performed a genome-wide DNA methylation capture sequencing in 243 stage II colorectal carcinoma samples and identified a relapse-specific DNA methylation signature consisting of eight CpG sites.MethodsTwo hundred and forty-three patients with stage II CRC were enrolled in this study. In order to select differential methylation sites among recurrence and non-recurrence stage II CRC samples, DNA methylation profiles of 62 tumour samples including 31 recurrence and 31 nonrecurrence samples were analysed using the Agilent SureSelectXT Human Methyl-Seq, a comprehensive target enrichment system to analyse CpG methylation. Pyrosequencing was applied to quantify the methylation level of candidate DNA methylation sites in 243 patients. Least absolute shrinkage and selection operator (LASSO) method was employed to build the disease recurrence prediction classifier.ResultsWe identified a relapse-related DNA methylation signature consisting of eight CpG sites in stage II CRC by DNA methylation capture sequencing. The classifier showed significantly higher prognostic accuracy than any clinicopathological risk factors. The Kaplan-Meier survival curve showed an association of high-risk score with poor prognosis. In multivariate analysis, the signature was the most significant prognosis factor, with an HR of 2.80 (95% CI, 1.71-4.58, P < 0.001). The signature could identify patients who are suitable candidates for adjuvant chemotherapy.ConclusionsAn eight-CpG DNA methylation signature is a reliable prognostic and predictive tool for disease recurrence in patients with stage II CRC.

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A DNA methylation signature to improve survival prediction of gastric cancer.

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A DNA methylation signature to improve survival prediction of gastric cancer.

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