Identification of methylation-driven genes related to prognosis in clear-cell renal cell carcinoma

With the participation of the existing treatment methods, the prognosis of advanced clear-cell renal cell carcinoma (ccRCC) is poor. More evidence indicates the presence of methylation in ccRCC cancer cells, but there is a lack of studies on methylation-driven genes in ccRCC. We analyzed the open data of ccRCC in The Cancer Genome Atlas database to obtain ccRCC-related methylation-driven genes, and then carried out pathway enrichment, survival, and joint survival analyses. More important, we deeply explored the correlation between differential methylation sites and the expression of these driving genes. Finally, we screened 29 methylation-driven genes via MethylMix, of which six were significantly associated with the survival of ccRCC patients. This study demonstrated that the effect of hypermethylation or hypomethylation on prognosis is different, and the level of methylation of key methylation sites is associated with gene expression. We identified methylation-driven genes independently predicting prognosis in ccRCC, which offers theoretical support in bioinformatics for the study of methylation in ccRCC and a new perspective for the epigenetic study of ccRCC.     

Peripheral blood DNA methylation profiles are indicative of head and neck squamous cell carcinoma: An epigenome-wide association study

Head and neck cancer accounts for an estimated 47,560 new cases and 11,480 deaths annually in the United States, the majority of which are squamous cell carcinomas (HNSCC). The overall 5 year survival is approximately 60% and declines with increasing stage at diagnosis, indicating a need for non-invasive tests that facilitate the detection of early disease. DNA methylation is a stable epigenetic modification that is amenable to measurement and readily available in peripheral blood. We used a semi-supervised recursively partitioned mixture model (SS-RPMM) approach to identify novel blood DNA methylation markers of HNSCC using genome-wide methylation array data for peripheral blood samples from 92 HNSCC cases and 92 cancer-free control subjects. To assess the performance of the resultant markers, we constructed receiver operating characteristic (ROC) curves and calculated the corresponding area under the curve (AUC). Cases and controls were best differentiated by a methylation profile of six CpG loci (associated with FGD4, SERPINF1, WDR39, IL27, HYAL2 and PLEKHA6), with an AUC of 0.73 (95% CI: 0.62–0.82). After adjustment for subject age, gender, smoking, alcohol consumption and HPV16 serostatus, the AUC increased to 0.85 (95% CI: 0.76–0.92). We have identified a novel blood-based methylation profile that is indicative of HNSCC with a high degree of accuracy. This profile demonstrates the potential of DNA methylation measured in blood for development of non-invasive applications for detection of head and neck cancer.     

DNA methylation biomarkers for head and neck squamous cell carcinoma

DNA methylation plays an important role in the etiology and pathogenesis of head and neck squamous cell carcinoma (HNSCC). The current study aimed to identify aberrantly methylated-differentially expressed genes (DEGs) by a comprehensive bioinformatics analysis. In addition, we screened for DEGs affected by DNA methylation modification and further investigated their prognostic values for HNSCC. We included microarray data of DNA methylation (GSE25093 and GSE33202) and gene expression (GSE23036 and GSE58911) from Gene Expression Omnibus. Aberrantly methylated-DEGs were analyzed with R software. The Cancer Genome Atlas (TCGA) RNA sequencing and DNA methylation (Illumina HumanMethylation450) databases were utilized for validation. In total, 27 aberrantly methylated genes accompanied by altered expression were identified. After confirmation by The Cancer Genome Atlas (TCGA) database, 2 hypermethylated-low-expression genes (FAM135B and ZNF610) and 2 hypomethylated-high-expression genes (HOXA9 and DCC) were identified. A receiver operating characteristic (ROC) curve confirmed the diagnostic value of these four methylated genes for HNSCC. Multivariate Cox proportional hazards analysis showed that FAM135B methylation was a favorable independent prognostic biomarker for overall survival of HNSCC patients.     

Biomarkers for detection and prognosis of breast cancer identified by a functional hypermethylome screen

Breast cancer (BC) is a disease with diverse tumor heterogeneity, which challenges conventional approaches to develop biomarkers for early detection and prognosis. To identify effective biomarkers, we performed a genome-wide screen for functional methylation changes in BC, i.e., genes silenced by promoter hypermethylation, using a functionally proven gene expression approach. A subset of candidate hypermethylated genes were validated in primary BCs and tested as markers for detection and prognosis prediction of BC. We identified 33 cancer specific methylated genes and, among these, two categories of genes: (1) highly frequent methylated genes that detect early stages of BC. Within that category, we have identified the combination of NDRG2 and HOXD1 as the most sensitive (94%) and specific (90%) gene combination for detection of BC; (2) genes that show stage dependent methylation frequency pattern, which are candidates to help delineate BC prognostic signatures. For this category, we found that methylation of CDO1, CKM, CRIP1, KL and TAC1 correlated with clinical prognostic variables and was a significant prognosticator for poor overall survival in BC patients. CKM [Hazard ratio (HR) = 2.68] and TAC1 (HR = 7.73) were the strongest single markers and the combination of both (TAC1 and CKM) was associated with poor overall survival independent of age and stage in our training (HR = 1.92) and validation cohort (HR = 2.87). Our study demonstrates an efficient method to utilize functional methylation changes in BC for the development of effective biomarkers for detection and prognosis prediction of BC.     

Gene promoter methylation signature predicts survival of head and neck squamous cell carcinoma patients

Infection with high-risk types of human papilloma virus (HPV) is currently the best-established prognostic marker for head and neck squamous cell carcinoma (HNSCC), one of the most common and lethal human malignancies worldwide. Clinical trials have been launched to address the concept of treatment de-escalation for HPV-positive HNSCC with the final aim to reduce treatment related toxicity and debilitating long-term impacts on the quality of life. However, HPV-related tumors are mainly restricted to oropharyngeal SCC (OPSCC) and there is an urgent need to establish reliable biomarkers for all patients at high risk for treatment failure. A patient cohort (n = 295) with mainly non-OPSCC (72.9%) and a low prevalence of HPV16-related tumors (8.8%) was analyzed by MassARRAY to determine a previously established prognostic methylation score (MS). Kaplan-Meier revealed a highly significant correlation between a high MS and a favorable survival for OPSCC (P = 0.0004) and for non-OPSCC (P<0.0001), which was confirmed for all HNSCC by multivariate Cox regression models (HR: 9.67, 95% CI [4.61–20.30], P<0.0001). Next, we established a minimal methylation signature score (MMSS), which consists of ten most informative of the originally 62 CpG units used for the MS. The prognostic value of the MMSS was confirmed by Kaplan-Meier analysis for all HNSCC (P<0.0001) and non-OPSCC (P = 0.0002), and was supported by multivariate Cox regression models for all HNSCC (HR: 2.15, 95% CI [1.36–3.41], P = 0.001). In summary, the MS and the MMSS exhibit an excellent performance as prognosticators for survival, which is not limited by the anatomical site, and both could be implemented in future clinical trials.     

NDRG2 and TLR7 as novel DNA methylation prognostic signatures for acute myelocytic leukemia

Acute myelocytic leukemia (AML) is an aggressive malignant tumor and typically fatal without treatment. Identification and development of novel biomarkers could be beneficial for the diagnosis and prognosis of AML patients. Here, we aimed to identify the accurate DNA methylation prognostic signatures for AML patients. The DNA methylation data of AML patients and corresponding clinical information were retrieved from The Cancer Genome Atlas database. CPG sites that correlates closely with the survival of the AML patients were identified and further combined into CPG sites pairs to screen the survival-related pairs. The prognostic signatures were identified by the C-index and forward search algorithms and validated by the verification group. Finally, the functional enrichment analysis was performed on these CPG sites. As a result, a total of 498 CPG sites associated with the overall survival of AML patients was obtained. A prognostic signature composed of 10 CPG sites pairs was obtained and validated. The functional enrichment analysis showed prognostic genes were mainly enriched in tumor protein processing, cell differentiation, blood leukocyte immunity, and platelet growth factor pathways. In summary, we identified two accurate prognostic methylation signatures (NDRG2 and TLR7), which would be served as a novel therapy target for AML.     

Prognostic value of differentially methylated gene profiles in bladder cancer

DNA methylation can regulate gene expression and is pivotal in the occurrence and development of bladder cancer. In this study, we analyzed whole-genome DNA methylation on the basis of data from The Cancer Genome Atlas to select epigenetic biomarkers predictive of survival and further understand the molecular mechanisms underlying methylation patterns in bladder cancer. We identified 540 differentially methylated genes between tumor and normal tissues, including a number of independent prognostic factors based on univariate analysis. Genes (MIR6732, SOWAHC, SERPINI1, OR10W1, OR7G3, AIM1, and ZFAND5) were integrated to establish a risk model for prognostic assessment based on multivariate Cox analysis. The methylation of SOWAHC was negatively correlated with its messenger RNA expression, and together these were significantly correlated with prognosis. This study took advantage of high-throughput data mining to provide new bioinformatics evidence and ideas for further study into the pathogenesis and prognosis of bladder cancer.     

Systematic profiling identifies PDLIM2 as a novel prognostic predictor for oesophageal squamous cell carcinoma (ESCC)

Till now, no appropriate biomarkers for high‐risk population screening and prognosis prediction have been identified for patients with oesophageal squamous cell carcinoma (ESCC). In this study, by the combined use of data from the Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA)‐oesophageal carcinoma (ESCA), we aimed to screen dysregulated genes with prognostic value in ESCC and the genetic and epigenetic alterations underlying the dysregulation. About 222 genes that had at least fourfold change in ESCC compared with adjacent normal tissues were identified using the microarray data in GDS3838. Among these genes, only PDLIM2 was associated with nodal invasion and overall survival (OS) at the same time. The high PDLIM2 expression group had significantly longer OS and its expression was independently associated with better OS (HR: 0.64, 95% CI: 0.43‐0.95, P = 0.03), after adjustment for gender and pathologic stages. The expression of its exon 7/8/9/10 had the highest AUC value (0.724) and better prognostic value (HR: 0.43, 95% CI: 0.22‐0.83, P = 0.01) than total PDLIM2 expression. PDLIM2 DNA copy deletion was common in ESCC and was associated with decreased gene expression. The methylation status of two CpG sites (cg23696886 and cg20449614) in the proximal promoter region of PDLIM2 showed a moderate negative correlation with the gene expression in PDLIM2 copy neutral/amplification group. In conclusion, we infer that PDLIM2 expression might be a novel prognostic indicator for ESCC patients. Its exon 7/8/9/10 expression had the best prognostic value. Its down‐regulation might be associated with gene‐level copy deletion and promoter hypermethylation.     

Downregulation of the circadian Period family genes is positively correlated with poor head and neck squamous cell carcinoma prognosis

ABSTRACT

We investigated the relationship between head and neck squamous cell carcinoma (HNSCC) and the mRNA and protein expression levels of the circadian genes of the Period (Per) family, Per1, Per2 and Per3. Tissue sections of HNSCC and normal head and neck tissues from two patient cohorts from two different hospitals were collected to assess the mRNA and protein expressions of the three Per family genes using real-time quantitative PCR (RT-PCR) and immunohistochemistry (IHC). The clinicopathological features and disease prognosis for the latter cohort were analyzed through IHC and statistical methods. Protein positive expression levels of the three Per family genes in HNSCC tissues was found to be approximately two times lower than that in normal tissues (p < .01). Moreover, patients with locally advanced HNSCC showed significantly greater downregulation of Per1, Per2 and Per3 mRNA expression levels as compared to patients with early-stage cancer (p < .05). Immunohistochemical examination of HNSCC patient tissues revealed a positive correlation between the Per family protein expression and the clinical tumor staging (p < .05). In addition, the Per protein-positive expression group showed higher 3-year survival rates [overall survival (OS) and progression-free survival (PFS)] as assessed by Kaplan-Meier plots and statistical analysis (p < .05). Our findings confirm the positive correlation between Per family gene expression and survival outcomes and support their role as prognostic markers for HNSCC.     

Prognostic potential of <Emphasis Type="Italic">KLOTHO</Emphasis> and <Emphasis Type="Italic">SFRP1</Emphasis> promoter methylation in head and neck squamous cell carcinoma

Hypermethylation in the CpG island promoter regions of tumor suppressors is known to play a significant role in the development of HNSCC and the detection of which can aid the classification and prognosis of HNSCC. This study aims to profile the methylation patterns in a panel of key genes including CDKN2A, CDKN2B, KLOTHO (KL), RASSF1A, RARB, SLIT2, and SFRP1, in a group of HNSCC samples from Saudi Arabia. The extent of methylation in these genes is determined using the MethyLight assay and correlated with known clinicopathological parameters in our samples of 156 formalin-fixed and paraffin-embedded HNSCC tissues. SLIT2 methylation had the highest frequency (64.6%), followed by RASSF1A (41.3%), RARB (40.7%), SFRP1 (34.9), KL (30.7%), CKDN2B (29.6%), and CKDN2A (29.1%). KL and SFRP1 methylation were more predominant in nasopharyngeal tumors (P = 0.001 and P = 0.031 respectively). Kaplan Meier analysis showed that patients with moderately differentiated tumors who display SFRP1 methylation have significantly worse overall survival in comparison with other samples. In contrast, better clinical outcomes were seen in patients with KL methylation. In conclusion, our findings suggest that the detection of frequent methylation in SFRP1 and KL genes’ promoters could serve as prognostic biomarkers for HNSCC.     

Identification of a novel cell cycle-related gene signature predicting survival in patients with gastric cancer

Gastric cancer (GC) is one of the most fatal cancers in the world. Thousands of biomarkers have been explored that might be related to survival and prognosis via database mining. However, the prediction effect of single gene biomarkers is not specific enough. Increasing evidence suggests that gene signatures are emerging as a possible better alternative. We aimed to develop a novel gene signature to improve the prognosis prediction of GC. Using the messenger RNA (mRNA)-mining approach, we performed mRNA expression profiling in a large GC cohort (n = 375) from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed, and we recovered genes related to the G2/M checkpoint, which we identified with a Cox proportional regression model. We identified a set of five genes (MARCKS, CCNF, MAPK14, INCENP, and CHAF1A), which were significantly associated with overall survival (OS) in the test series. Based on this five-gene signature, the test series patients could be classified into high-risk or low-risk subgroups. Multivariate Cox regression analysis indicated that the prognostic power of this five-gene signature was independent of clinical features. In conclusion, we developed a five-gene signature related to the cell cycle that can predict survival for GC. Our findings provide novel insight that is useful for understanding cell cycle mechanisms and for identifying patients with GC with poor prognoses.     

Screening and verification of microRNA promoter methylation sites in hepatocellular carcinoma

The promoter methylation mode of microribonucleic acid (miRNA) plays a crucial role in the process of hepatocellular carcinoma (HCC). Therefore, the primary purpose of this study was to screen and verify the miRNA methylation sites associated with the overall survival (OS) and clinical characteristics of HCC patients. Methylation-related data were from the Cancer Genome Atlas (TCGA). R software was utilized to screen the methylation sites. The least absolute shrinkage and selection operator algorithm was utilized to develop the miRNA promoter methylation models. Then, methylation-specific polymerase chain reaction was performed with 146 HCC tissues to verify the accuracy of the vascular infiltration-related model. Additionally, we verified the functions of vascular infiltration-related miRNA by utilizing cells transfected with miR-199a-3p mimic. The model for predicting OS of HCC patients contained eight methylation sites. The Kaplan-Meier analysis suggested that the model could divide HCC patients into high- and low-risk groups (P < .0001). COX regression analysis suggested that the model (P < .001; 95% CI, 1.264-2.709) and T category (P < .001; 95% CI, 1.472-3.119) were independent risk factors for affecting OS of HCC patients. The model for predicting vascular infiltration, pathological grade, and clinical stage contained 7, 10, and 9 methylation sites respectively, with their area under the receiver operating characteristic curve (AUC) values 0.667, 0.745, and 0.725, respectively. The functional analysis suggested that miRNA methylation is involved in various biological processes such as WNT, MAPK, and mTOR signaling pathways. The accuracy of the vascular infiltration-related model was consistent with our previous bioinformatics assay. And upregulation of miR-199a-3p decreased migration and invasion abilities. The screened miRNA promoter methylation sites can be served as biomarkers for judging OS, vascular infiltration, pathology grade, and clinical stage. It can also provide new targets for improving the treatment and prognosis of HCC patients.     

Prognostic Value of Tumor-Infiltrating Lymphocytes for Patients With Head and Neck Squamous Cell Carcinoma

BACKGROUND: The prognostic value of tumor-infiltrating lymphocytes (TILs) in head and neck squamous cell carcinoma (HNSCC) remains controversial. Additionally, there is no standardized approach or cutoff value for evaluating TIL levels. The aim of this study was to establish a feasible method and criterion to assess TIL levels for future clinical practice and research use and to explore the relationship between TIL levels and prognosis. PATIENTS AND METHODS: This retrospective cohort study reviewed the records and pathological sections of 202 patients with HNSCC who were surgically treated at Beijing Stomatological Hospital, Capital Medical University, from January 1998 to January 2011. The predictor variable was the TIL level. The main outcome assessment parameters were disease-free survival (DFS) and disease-specific survival (DSS). RESULT: The T stage (P = .008), smoking history (P = .042), alcohol history (P = .048), need for radiotherapy (P = .012) and microscopic extracapsular spread (ECS) (P = .012) were associated with the TIL level. A cutoff value equal to 70% could be taken as a threshold for TIL assessment, with a TIL level higher than 70% associated with a better prognosis (DFS rate: 51.9%, P = .018; DSS rate: 59.3%, P = .049). The Cox regression model showed that the TIL level was an independent prognostic factor for DFS (hazard ratio (HR): 0.786, 95% CI: 0.618-0.999, P = .049). CONCLUSION: The TIL level is closely related to the prognosis of patients with HNSCC. A threshold value of 70% is appropriate for TIL assessment, as patients with a TIL level higher than 70% show a better prognosis. Thus, the TIL level might serve as an independent predictor for HNSCC recurrence.     

Clinical and prognostic effects of CDKN2A,CDKN2B and CDH13 promoter methylation in ovarian cancer: a study using meta-analysis and TCGA data

Abstract

Background: Promoter methylation of tumour suppressor genes (TSGs) CDKN2A, CDKN2B and CDH13 has been reported in ovarian cancer. However, the clinicopathological characteristics and prognostic role of CDKN2A, CDKN2B and CDH13 promoter methylation in ovarian carcinoma remained unclear.

Methods: The pooled odds ratio (OR) or hazard ratios (HRs) with their 95% confidence intervals (95% CIs) were calculated in this meta-analysis. The Cancer Genome Atlas data were obtained to confirm the role of CDKN2A, CDKN2B and CDH13 methylation in ovarian cancer.

Results: CDKN2A, CDKN2B and CDH13 promoter methylation was higher in ovarian cancer than in normal ovarian tissues. CDH13 promoter methylation was correlated with tumour histology (serous vs. non-serous type: OR?=?0.33, p?=?0.031). CDKN2A promoter methylation was not linked to overall survival (OS), but it was correlated with a poor prognosis in progression-free survival (HR?=?1.55, p?=?0.004). TCGA data showed no correlation between CDKN2A, CDKN2B and CDH13 methylation and OS as well as disease-free survival (DFS).

Conclusions: CDKN2A, CDKN2B and CDH13 promoter methylation may correlate with the increased risk of ovarian cancer. CDKN2A promoter methylation may be an independent prognostic biomarker for predicting progression-free survival.     

Decitabine Rescues Cisplatin Resistance in Head and Neck Squamous Cell Carcinoma

Cisplatin resistance in head and neck squamous cell carcinoma (HNSCC) reduces survival. In this study we hypothesized that methylation of key genes mediates cisplatin resistance. We determined whether a demethylating drug, decitabine, could augment the anti-proliferative and apoptotic effects of cisplatin on SCC-25/CP, a cisplatin-resistant tongue SCC cell line. We showed that decitabine treatment restored cisplatin sensitivity in SCC-25/CP and significantly reduced the cisplatin dose required to induce apoptosis. We then created a xenograft model with SCC-25/CP and determined that decitabine and cisplatin combination treatment resulted in significantly reduced tumor growth and mechanical allodynia compared to control. To establish a gene classifier we quantified methylation in cancer tissue of cisplatin-sensitive and cisplatin-resistant HNSCC patients. Cisplatin-sensitive and cisplatin-resistant patient tumors had distinct methylation profiles. When we quantified methylation and expression of genes in the classifier in HNSCC cells in vitro, we showed that decitabine treatment of cisplatin-resistant HNSCC cells reversed methylation and gene expression toward a cisplatin-sensitive profile. The study provides direct evidence that decitabine restores cisplatin sensitivity in in vitro and in vivo models of HNSCC. Combination treatment of cisplatin and decitabine significantly reduces HNSCC growth and HNSCC pain. Furthermore, gene methylation could be used as a biomarker of cisplatin-resistance.     

Novel prognostic model established for patients with head and neck squamous cell carcinoma based on pyroptosis-related genes

We aimed at establishing a risk – score model using pyroptosis-related genes to predict the prognosis of patients with head and neck squamous cell carcinoma (HNSCC). A total of 33 pyroptosis-related genes were selected. We then evaluated the data of 502 HNSCC patients and 44 normal patients from TCGA database. Gene expression was then profiled to detect differentially expressed genes (DEGs). Using the univariate, the least absolute shrinkage and selection operator (LASSO) Cox regression analyses, we generated a risk – score model. Tissue samples from neoplastic and normal sites of 44 HNSCC patients were collected. qRT-PCR were employed to analyze the mRNA level of the samples. Kaplan-Meier method was used to evaluate the overall survival rate (OS). Enrichment analysis was performed to elucidate the underlying mechanism of HNSCC patient's differentially survival status from the perspective of tumor immunology. 17 genes were categorized as DEGs. GSDME, IL-6, CASP8, CASP6, NLRP1 and NLRP6 were used to establish the risk – score model. Each patient's risk score in the TCGA cohort was calculated using the risk – score formula. The risk score was able to independently predict the OS of the HNSCC patients (P = 0.02). The OS analysis showed that the risk score model (P < 0.0001) was more reliable than single gene, a phenomenon verified by practical patient cohort. Additionally, enrichment analysis indicated more active immune activities in low-risk group than high-risk group. In conclusion, our risk – score model has provided novel strategy for the prediction of HNSCC patients’ prognosis.     

Peripheral blood DNA methylation profiles are indicative of head and neck squamous cell carcinoma: An epigenome-wide association study

Head and neck cancer accounts for an estimated 47,560 new cases and 11,480 deaths annually in the United States, the majority of which are squamous cell carcinomas (HNSCC). The overall 5 year survival is approximately 60% and declines with increasing stage at diagnosis, indicating a need for non-invasive tests that facilitate the detection of early disease. DNA methylation is a stable epigenetic modification that is amenable to measurement and readily available in peripheral blood. We used a semi-supervised recursively partitioned mixture model (SS-RPMM) approach to identify novel blood DNA methylation markers of HNSCC using genome-wide methylation array data for peripheral blood samples from 92 HNSCC cases and 92 cancer-free control subjects. To assess the performance of the resultant markers, we constructed receiver operating characteristic (RJC) curves and calculated the corresponding area under the curve (AUC). Cases and controls were best differentiated by a methylation profile of six CpG loci (associated with FGD4, SERPINF1, WDR39, IL27, HYAL2 and PLEKHA6), with an AUC of 0.73 (95% CI: 0.62–0.82). After adjustment for subject age, gender, smoking, alcohol consumption and HPV16 serostatus, the AUC increased to 0.85 (95% CI: 0.76–0.92). We have identified a novel blood-based methylation profile that is indicative of HNSCC with a high degree of accuracy. This profile demonstrates the potential of DNA methylation measured in blood for development of non-invasive applications for detection of head and neck cancer.Key words: semi-supervised RPMM, HNSCC, epigenetics, biomarkers, Infinium, methylation array     

Identification of DNA methylation signature to predict prognosis in gastric adenocarcinoma

Gastric adenocarcinoma is an important death-related cancer. To find factors related to survival and prognosis, and thus improve recovery prospects, a powerful signature is needed. DNA methylation plays an important role in gastric adenocarcinoma processes and development, and here we report on the search for a significant DNA methylation gene to aid with the earlier diagnosis of gastric adenocarcinoma patients. A Cox proportional risk regression analysis and random survival forest algorithm were used to analyze gastric adenocarcinoma patients’ DNA methylation data from The Cancer Genome Atlas, a public database. DNA methylation gene signature consisting of five genes (SERPINA3, AP000357.4, GZMA, AC004702.2, and GREB1L) were selected. As the most accurate predictor, the area under the curve in the training and test group were 0.72 and 0.61, respectively. The signature was able to sort patients into high- and low-risk groups with meaningful overall survival rates (median: 18.36 vs 72.23 months, log-rank test, P < 0.001) in the training group, which predictive ability was validated in a test data set (median: 25.56 vs 58.80 months, log-rank test, P < 0.016). A multivariate Cox regression analysis showed the significant DNA methylation was an independent prediction prognostic factor for gastric adenocarcinoma patients. Functional analysis suggests that these signature genes may be related to pathways and biological processes associated with tumorigenesis. The significant DNA methylation gene could be a novel prediction and prognostic biomarker that both aids in the treatment and predicts the overall survival likelihoods of gastric adenocarcinoma patients.