Role of RASSF1A promoter methylation in the pathogenesis of hepatocellular carcinoma: a meta-analysis of 21 cohort studies

Identification of Prognostic Markers in Cholangiocarcinoma Using Altered DNA Methylation and Gene Expression Profiles

Background

Cholangiocarcinoma (CCA) is a rare disease, but it is amongst the most lethal cancers with a median survival under 1 year. Variations in DNA methylation and gene expression have been extensively studied in other cancers for their role in pathogenesis and disease prognosis, but these studies are very limited in CCA. This study focusses on the identification of DNA methylation and gene expression prognostic biomarkers using multi-omics data of CCA tumors from The Cancer Genome Atlas (TCGA).

Method

We have conducted a genome-wide analysis of differential DNA methylation and gene/miRNA expression using data from 36 CCA tumor and 9 normal samples from TCGA. The impact of DNA methylation in promoters and long-range distal enhancers on the regulation and expression of CCA-associated genes was examined using linear regression. Next, we conducted network analyses on genes which are regulated by DNA methylation as well as by miRNA. Finally, we performed Kaplan–Meier and Cox proportional hazards regression analyses in order to identify the role of selected methylation sites and specific genes and miRNAs in patient survival. We also performed real-time quantitative PCR (qPCR) to confirm the change in gene expression in CCA patients’ tumor and adjacent normal samples.

Results

Altered DNA methylation was observed on 12,259 CpGs across all chromosomes, of which 78% were hypermethylated. We observed a strong negative relationship between promoter hypermethylation and corresponding gene expression in 92% of the CpGs. Differential expression analyses revealed altered expression patterns in 3,305 genes and 101 miRNAs. Finally, we identified 17 differentially methylated promoter CpGs, 72 differentially expressed genes, and two miRNAs that are likely associated with patient survival. Pathway analysis suggested that cell division, bile secretion, amino acid metabolism, PPAR signaling, hippo signaling were highly affected by gene expression and DNA methylation alterations. The qPCR analysis further confirmed that MDK, HNF1B, PACS1, and GLUD1 are differentially expressed in CCA.

Conclusion

Based on the survival analysis, we conclude that DEPDC1, FUT4, MDK, PACS1, PIWIL4 genes, miR-22, miR-551b microRNAs, and cg27362525 and cg26597242 CpGs can strongly support their use as prognostic markers of CCA.

Genome-wide DNA methylation analysis reveals molecular subtypes of pancreatic cancer

Pancreatic cancer (PC) is the fourth leading cause of cancer deaths in the United States with a five-year patient survival rate of only 6%. Early detection and treatment of this disease is hampered due to lack of reliable diagnostic and prognostic markers. Recent studies have shown that dynamic changes in the global DNA methylation and gene expression patterns play key roles in the PC development; hence, provide valuable insights for better understanding the initiation and progression of PC. In the current study, we used DNA methylation, gene expression, copy number, mutational and clinical data from pancreatic patients. We independently investigated the DNA methylation and differential gene expression profiles between normal and tumor samples and correlated methylation levels with gene expression patterns. We observed a total of ~23-thousand differentially methylated CpG sites (Δβ≥0.1) between normal and tumor samples, where majority of the CpG sites are hypermethylated in PC, and this phenomenon is more prominent in the 5′UTRs and promoter regions compared to the gene bodies. Differential methylation is observed in genes associated with the homeobox domain, cell division and differentiation, cytoskeleton, epigenetic regulation and development, pancreatic development and pancreatic signaling and pancreatic cancer core signaling pathways. Correlation analysis suggests that methylation in the promoter region and 5′UTR has mostly negative correlations with gene expression while gene body and 3′UTR associated methylation has positive correlations. Regulatory element analysis suggests that HOX cluster and histone core proteins are upstream regulators of hypomethylation, while SMAD4, STAT4, STAT5B and zinc finger proteins (ZNF) are upstream regulators of hypermethylation. Non-negative matrix factorization (NMF) clustering of differentially methylated sites generated three clusters in PCs suggesting the existence of distinct molecular subtypes. Cluster 1 and cluster 2 showed samples enriched with clinical phenotypes like neoplasm histological grade and pathologic T-stage T3, respectively, while cluster 3 showed the enrichment of samples with neoplasm histological grade G1. To the best of our knowledge, this is the first genome-scale methylome analysis of PC data from TCGA. Our clustering analysis provides a strong basis for future work on the molecular subtyping of epigenetic regulation in pancreatic cancer.

The relationship between RASSF1A promoter methylation and thyroid carcinoma: A meta-analysis of 14 articles and a bioinformatics of 2 databases (PRISMA)

BACKGROUND

DNA promoter methylation can suppresses gene expression and shows an important role in the biological functions of Ras association domain family 1A (RASSF1A). Many studies have performed to elucidate the role of RASSF1A promoter methylation in thyroid carcinoma, while the results were conflicting and heterogeneous. Here, we analyzed the data of databases to determine the relationship between RASSF1A promoter methylation and thyroid carcinoma.

METHODS

We used the data from 14 cancer-normal studies and Gene Expression Omnibus (GEO) database to analyze RASSF1A promoter methylation in thyroid carcinoma susceptibility. The data from the Cancer Genome Atlas project (TCGA) database was used to analyze the relationship between RASSF1A promoter methylation and thyroid carcinoma susceptibility, clinical characteristics, prognosis. Odds ratios were estimated for thyroid carcinoma susceptibility and hazard ratios were estimated for thyroid carcinoma prognosis. The heterogeneity between studies of meta-analysis was explored using H, I values, and meta-regression. We adopted quality criteria to classify the studies of meta-analysis. Subgroup analyses were done for thyroid carcinoma susceptibility according to ethnicity, methods, and primers.

RESULTS

Result of meta-analysis indicated that RASSF1A promoter methylation is associated with higher susceptibility to thyroid carcinoma with small heterogeneity. Similarly, the result from GEO database also showed that a significant association between RASSF1A gene promoter methylation and thyroid carcinoma susceptibility. For the results of TCGA database, we found that RASSF1A promoter methylation is associated with susceptibility and poor disease-free survival (DFS) of thyroid carcinoma. In addition, we also found a close association between RASSF1A promoter methylation and patient tumor stage and age, but not in patients of different genders.

CONCLUSIONS

The methylation status of RASSF1A promoter is strongly associated with thyroid carcinoma susceptibility and DFS. The RASSF1A promoter methylation test can be applied in the clinical diagnosis of thyroid carcinoma.

The relationship between RASSF1A gene promoter methylation and the susceptibility and prognosis of melanoma: A meta-analysis and bioinformatics

Background

The function of the tumor suppressor gene RASSF1A in cancer cells has been detailed in many studies. However, due to the methylation of its promoter, the expression of RASSF1A is missing in most cancers. In the literature, we found that the conclusion regarding the relationship between RASSF1A gene promoter methylation and the susceptibility and prognosis of melanoma was not unified. This study adopts the use of a meta-analysis and bioinformatics to explore the relationship between RASSF1A gene promoter methylation and the susceptibility and prognosis of melanoma.

Methods

Data on melanoma susceptibility were downloaded from the PubMed, Cochrane Library, Web of Science and Google Scholar databases, which were analyzed via a meta-analysis. The effect sizes were estimated by measuring an odds ratio (OR) with a 95% confidence interval (CI). We also used a chi-squared-based Q test to examine the between-study heterogeneity, and used funnel plots to evaluate publication bias. The data on melanoma prognosis, which were analyzed by bioinformatics methods, were downloaded from The Cancer Genome Atlas (TCGA) project. The effect sizes were estimated by measuring the hazard ratios (HRs) with a 95% confidence interval (CI).

Results

Our meta-analysis included 10 articles. We found that RASSF1A gene promoter methylation was closely related to melanoma susceptibility (OR = 12.67, 95% CI: 6.16 ∼ 26.05, z = 6.90, P<0.0001 according to a fixed effects model and OR = 9.25, 95% CI: 4.37 ∼ 19.54, z = 5.82, P<0.0001 according to a random effects model). The results of the meta-analysis did not reveal any heterogeneity (tau² = 0.00; H = 1 [1; 1.55]; I² = 0% [0%; 58.6%], P = 0.5158) or publication bias (t = 0.87, P = 0.4073 by Egger’s test; Z = 0.45, P = 0.6547 by Begg’s test); therefore, we believe that the results of our meta-analysis were more reliable. To explore the relationship between RASSF1A gene methylation, the prognosis of melanoma and the clinical features of this cancer type, we used the melanoma DNA methylation data and clinical data from TCGA project. We found that RASSF1A gene promoter methylation and melanoma prognosis did not demonstrate any relationship (HR was 0.94 (95% CI = [0.69; 1.27], P = 0.694) with disease-free survival and 0.74 (95% CI = [0.53; 1.05], P = 0.106) for overall survival), and no significant difference was observed between RASSF1A gene promoter methylation and the clinical-pathological features of melanoma.

Conclusions

In conclusion, the meta-analysis of the data in these articles provides strong evidence that the methylation status of the RASSF1A gene promoter was strongly related to melanoma susceptibility. Our bioinformatics analysis revealed no significant difference between RASSF1A gene promoter methylation and the prognosis and clinical-pathological features of melanoma.

Quantitative assessment of the relationship between RASSF1A gene promoter methylation and bladder cancer (PRISMA)

BACKGROUND

Methylation of the Ras-association domain family 1 isoform A (RASSF1A) gene promoter region is thought to participate in the initiation and development of many different cancers. However, in bladder cancer the role of RASSF1A methylation was unclear. To evaluate the relationship between RASSF1A methylation and bladder cancer, a quantitative assessment of an independent meta-analysis was performed. In addition, a DNA methylation microarray database from the cancer genome atlas (TCGA) project was used to validate the results of the meta-analysis.

METHODS

We searched published articles from computerized databases, and DNA methylation data were extracted from TCGA project. All data were analyzed by R software.

RESULTS

The results of the meta-analysis indicated that the frequency of RASSF1A gene methylation in bladder cancer patients is significantly higher than in healthy controls. The hazard ratio (HR) was 2.24 (95% CI = [1.45; 3.48], P = 0.0003) for overall survival (OS), and the RASSF1A gene promoter methylation status was strongly associated with the TNM stage and differentiation grade of the tumor. The similar results were also found by the data from TCGA project.

CONCLUSION

There was a significant relationship between the methylation of the RASSF1A gene promoter and bladder cancer. Therefore, RASSF1A gene promoter methylation will be a potential biomarker for the clinical diagnosis of bladder cancer.

RASSF1A promoter methylation is associated with increased risk of thyroid cancer: a meta-analysis

Objective

Previous studies have reported that Ras-associated domain family 1A (RASSF1A), the most commonly silenced tumor suppressor via promoter methylation, played vital roles in the development of carcinogenesis. The purpose of this meta-analysis was to determine whether RASSF1A promoter methylation increased the risk of thyroid cancer.

Methods

PubMed, Embase, ISI Web of Knowledge, and Chinese National Knowledge Infrastructure databases were searched to obtain eligible studies. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the strength of the associations, using Stata 12.0 software. The methodological quality of included studies was evaluated using Newcastle–Ottawa scale table. Egger’s test and Begg’s test were applied to detect publication biases. TSA 0.9 software was used to calculate the required information size and whether the result was conclusive.

Results

A total of 10 articles with 12 studies that included 422 thyroid cancer patients, identifying the association of RASSF1A promoter methylation with thyroid cancer risk, were collected in this meta-analysis. Overall, RASSF1A promoter methylation significantly increased the risk of thyroid cancer (total, OR=8.27, CI=4.38–15.62, P<0.05; Caucasian, OR=9.25, CI=3.97–21.56, P<0.05; Asian, OR=7.01, CI=2.68–18.38, P<0.05). In the subgroup analysis based on sample type, a significant association between thyroid cancer group and control group was found (normal tissue, OR=9.55, CI=4.21–21.67, P<0.05; adjacent tissue, OR=6.80, CI=2.49–18.56, P<0.05). The frequency of RASSF1A promoter methylation in follicular thyroid carcinoma was higher than in control group (OR=11.88, CI=5.80–24.32, P<0.05). In addition, the results indicated that the RASSF1A promoter methylation was correlated with papillary thyroid carcinoma in Caucasians and Asians (total, OR=8.07, CI=3.54–18.41, P<0.05; Caucasian, OR=11.35, CI=2.39–53.98, P<0.05; Asian, OR=6.67, CI=2.53–17.64, P<0.05). On the basis of the trial sequential analysis, the significant association of RASSF1A promoter methylation with thyroid cancer risk was found, and there was no need to perform further studies.

Conclusion

This meta-analysis confirms that RASSF1A promoter methylation is a risk factor for thyroid tumor.

Asialoglycoprotein receptor-magnetic dual targeting nanoparticles for delivery of RASSF1A to hepatocellular carcinoma

We developed a nanovector with double targeting properties for efficiently delivering the tumor suppressor gene RASSF1A specifically into hepatocellular carcinoma (HCC) cells by preparing galactosylated-carboxymethyl chitosan-magnetic iron oxide nanoparticles (Gal-CMCS-Fe₃O₄-NPs). After conjugating galactose and CMCS to the surface of Fe₃O₄-NPs, we observed that Gal-CMCS-Fe₃O₄-NPs were round with a relatively stable zeta potential of +6.5 mV and an mean hydrodynamic size of 40.1 ± 5.3 nm. Gal-CMCS-Fe₃O₄-NPs had strong DNA condensing power in pH 7 solution and were largely nontoxic. In vitro experiments demonstrated that Gal-CMCS-Fe₃O₄-NPs were highly selective for HCC cells and liver cells. In vivo experiments showed the specific accumulation of Gal-CMCS-Fe₃O₄-NPs in HCC tissue, especially with the aid of an external magnetic field. Nude mice with orthotopically transplanted HCC received an intravenous injection of the Gal-CMCS-Fe₃O₄-NPs/pcDNA3.1(+)RASSF1A compound and intraperitoneal injection of mitomycin and had an external magnetic field applied to the tumor area. These mice had the smallest tumors, largest percentage of TUNEL-positive cells, and highest caspase-3 expression levels in tumor tissue compared to other groups of treated mice. These results suggest the potential application of Gal-CMCS-Fe₃O₄-NPs for RASSF1A gene delivery for the treatment of HCC.

Clinical utility of RASSF1A methylation in human malignancies

The high frequency of RASSF1A methylation has been noted in a vast number of patients in a broad spectrum of malignancies, suggesting that RASSF1A inactivation is associated with cancer pathogenesis. However, whether this recurrent incidence of RASSF1A hypermethylation in human malignancies and its association with more aggressive tumour phenotype is a frequent event across different cancer types has not yet been discussed. In this review, we interrogated existing evidence for association of RASSF1A hypermethylation with clinicopathological characteristics that can indicate more invasive lesions.

DNA methylation biomarkers: cancer and beyond

Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient's response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.