Methylation status of IGF2 DMR and LINE1 in leukocyte DNA provides distinct clinicopathological features of gastric cancer patients

DNA Methylation: An Important Biomarker and Therapeutic Target for Gastric Cancer

Gastric cancer (GC) is a very common malignancy with a poor prognosis, and its occurrence and development are closely related to epigenetic modifications. Methylation of DNA before or during gastric cancer is an interesting research topic. This article reviews the studies on DNA methylation related to the cause, diagnosis, treatment, and prognosis of gastric cancer and aims to find cancer biomarkers to solve major human health problems.

Invasive and Noninvasive Nonfunctioning Gonadotroph Pituitary Tumors Differ in DNA Methylation Level of LINE-1 Repetitive Elements

PURPOSE

Epigenetic dysregulation plays a role in pituitary tumor pathogenesis. Some differences in DNA methylation were observed between invasive and noninvasive nonfunctioning gonadotroph tumors. This study sought to determine the role of DNA methylation changes in repetitive LINE-1 elements in nonfunctioning gonadotroph pituitary tumors.

METHODS

We investigated LINE-1 methylation levels in 80 tumors and normal pituitary glands with bisulfite-pyrosequencing. Expression of two LINE-1 open reading frames (L1-ORF1 and L1-ORF2) was analyzed with qRT-PCR in tumor samples and mouse gonadotroph pituitary cells treated with DNA methyltransferase inhibitor. Immunohistochemical staining against L1-ORF1p was also performed in normal pituitary glands and tumors.

RESULTS

Hypomethylation of LINE-1 was observed in pituitary tumors. Tumors characterized by invasive growth revealed lower LINE-1 methylation level than noninvasive ones. LINE-1 methylation correlated with overall DNA methylation assessed with HM450K arrays and negatively correlated with L1-ORF1 and L1-ORF2 expression. Treatment of αT3-1 gonadotroph cells with 5-Azacytidine clearly increased the level of L1-ORF1 and L1-ORF2 mRNA; however, its effect on LβT2 cells was less pronounced. Immunoreactivity against L1-ORF1p was higher in tumors than normal tissue. No difference in L1-ORF1p expression was observed in invasive and noninvasive tumors.

CONCLUSION

Hypomethylation of LINE-1 is related to invasive growth and influences transcriptional activity of transposable elements.

Differentially methylated regions (DMRs) in PON3 gene between responders and non-responders to a weight loss dietary intervention: a new tool for precision management of obesity

Differentially methylated regions (DMR) are genomic regions with different methylation status. The aim of this research was to identify DMRs in subjects with obesity that predict the response to a weight-loss dietary intervention and its association with metabolic variables. Based on the change in body mass index (BMI), 201 subjects with overweight and obesity were categorized in tertiles according to their response to a hypocaloric diet: Responders (R; n = 64) and Non-Responders (NR; n = 63). The R group lost 4.55 ± 0.91 BMI units (kg/m²) and the NR group lost 1.95 ± 0.73 kg/m² (p < 0.001). DNA methylation was analysed in buffy coat through a methylation array at baseline. DMRs were analysed using a function of ChAMP (Chip Analysis Methylation Pipeline) in R software. Baseline DNA methylation analysis between R and NR exhibited a DMR located at paraoxonase 3 gene (PON3) consisting of 13 CpG sites, eleven of them significantly hypermethylated in R. To analyse the implication of these 11 CpGs on weight loss, a z-score was performed as a measure of DMR methylation. This analysis showed a correlation between PON3 DNA methylation and BMI loss. This z-score negatively correlated with PON3 protein serum levels. Total paraoxonase activity in serum was not different between groups, but PON enzymatic activity positively correlated with oxidized LDL levels. The present study identified a DMR within PON3 gene that is related to PON3 protein levels in serum, and that could be used as a potential biomarker to predict the response to weight-loss dietary interventions.

A predictive model for assessing prognostic risks in gastric cancer patients using gene expression and methylation data

BACKGROUND

The role(s) of epigenetic reprogramming in gastric cancer (GC) remain obscure. This study was designed to identify methylated gene markers with prognostic potential for GC.

METHODS

Five datasets containing gene expression and methylation profiles from GC samples were collected from the GEO database, and subjected to meta-analysis. All five datasets were subjected to quality control and then differentially expressed genes (DEGs) and differentially expressed methylation genes (DEMGs) were selected using MetaDE. Correlations between gene expression and methylation status were analysed using Pearson coefficient correlation. Then, enrichment analyses were conducted to identify signature genes that were significantly different at both the gene expression and methylation levels. Cox regression analyses were performed to identify clinical factors and these were combined with the signature genes to create a prognosis-related predictive model. This model was then evaluated for predictive accuracy and then validated using a validation dataset.

RESULTS

This study identified 1565 DEGs and 3754 DEMGs in total. Of these, 369 were differentially expressed at both the gene and methylation levels. We identified 12 signature genes including VEGFC, FBP1, NR3C1, NFE2L2, and DFNA5 which were combined with the clinical data to produce a novel prognostic model for GC. This model could effectively split GC patients into two groups, high- and low-risk with these observations being confirmed in the validation dataset.

CONCLUSION

The differential methylation of the 12 signature genes, including VEGFC, FBP1, NR3C1, NFE2L2, and DFNA5, identified in this study may help to produce a functional predictive model for evaluating GC prognosis in clinical samples.

Magnesium-dependent Phosphatase (MDP) 1 is a Potential Suppressor of Gastric Cancer

BACKGROUND

Recurrence is the leading cause of treatment failure and death in patients with gastric cancer (GC). However, the mechanism underlying GC recurrence remains unclear, and prognostic markers are still lacking.

METHODS

We analyzed DNA methylation profiles in gastric cancer cases with shorter survival (<1 year) or longer survival (> 3 years), and identified candidate genes associated with GC recurrence. Then, the biological effects of these genes on gastric cancer were studied.

RESULTS

A novel gene, magnesium-dependent phosphatase 1 (mdp1), was identified as a candidate gene whose DNA methylation was higher in GC samples from patients with shorter survival and lower in patients with longer survival. MDP1 protein was highly expressed in GC tissues with longer survival time, and also had a tendency to be expressed in highly differentiated GC samples. Forced expression of MDP1 in GC cell line BGC-823 inhibited cell proliferation, whereas the knockdown of MDP1 protein promoted cell growth. Overexpression of MDP1 in BGC-823 cells also enhanced cell senescence and apoptosis. Cytoplasmic kinase protein c-Jun N-terminal kinase (JNK) and signal transducer and activator of transcription 3 (Stat3) were found to mediate the biological function of MDP1.

CONCLUSION

These results suggest that MDP1 protein suppresses the survival of gastric cancer cells and loss of MDP expression may benefit the recurrence of gastric cancer.

Role of DNA Methylation in the Resistance to Therapy in Solid Tumors

Despite the recent advances in chemotherapeutic treatments against cancer, some types of highly aggressive and invasive cancer develop drug resistance against conventional therapies, which continues to be a major problem in the fight against cancer. In recent years, studies of alterations of DNA methylome have given us a better understanding of the role of DNA methylation in the development of tumors. DNA methylation (DNAm) is an epigenetic change that promotes the covalent transfer of methyl groups to DNA. This process suppresses gene expression through the modulation of the transcription machinery access to the chromatin or through the recruitment of methyl binding proteins. DNAm is regulated mainly by DNA methyltransferases. Aberrant DNAm contributes to tumor progression, metastasis, and resistance to current anti-tumoral therapies. Aberrant DNAm may occur through hypermethylation in the promoter regions of tumor suppressor genes, which leads to their silencing, while hypomethylation in the promoter regions of oncogenes can activate them. In this review, we discuss the impact of dysregulated methylation in certain genes, which impact signaling pathways associated with apoptosis avoidance, metastasis, and resistance to therapy. The analysis of methylome has revealed patterns of global methylation, which regulate important signaling pathways involved in therapy resistance in different cancer types, such as breast, colon, and lung cancer, among other solid tumors. This analysis has provided gene-expression signatures of methylated region-specific DNA that can be used to predict the treatment outcome in response to anti-cancer therapy. Additionally, changes in cancer methylome have been associated with the acquisition of drug resistance. We also review treatments with demethylating agents that, in combination with standard therapies, seem to be encouraging, as tumors that are in early stages can be successfully treated. On the other hand, tumors that are in advanced stages can be treated with these combination schemes, which could sensitize tumor cells that are resistant to the therapy. We propose that rational strategies, which combine specific demethylating agents with conventional treatment, may improve overall survival in cancer patients.

DNA methylation profiling to predict overall survival risk in gastric cancer: development and validation of a nomogram to optimize clinical management

DNA methylation has been reported to serve an important role in the carcinogenesis and development of gastric cancer. Our aim was to systematically develop an individualized prediction model of the survival risk combing clinical and methylation factors in gastric cancer. A univariate Cox proportional risk regression analysis was used to identify the prognosis-associated methylation sites based on the differentially expressed methylation sites between early and advanced gastric cancer group, then we applied least absolute shrinkage and selection operator (LASSO) Cox regression model to screen candidate methylation sites. Subsequently, multivariate Cox proportional risk regression analysis was conducted to identify predictive signature according to the candidate sites. Relative operating characteristic curve (ROC) analysis manifested that an 11-methylation signature exhibited great predictive efficiency for 1-, 3-, 5-year survival events. Patients in the low-risk group classified according to 11-methylation signature-based risk score yield significantly better survival than that in high-risk group. Moreover, Cox regression analysis combing methylation-based risk score and other clinical factors indicated that 11-methylation signature served as an independent risk factor. The predictive value of risk score was validated in the testing dataset. In addition, a nomogram was constructed and the ROC as well as calibration plots analysis demonstrated the good performance and clinical application of the nomogram. In conclusion, the result suggested the 11-DNA methylation signature may be potentially independent prognostic marker and functioned as a significant tool for guiding the clinical prediction of gastric cancer patients' overall survival.

The Neglected Insulin: IGF-II, a Metabolic Regulator with Implications for Diabetes, Obesity, and Cancer

When originally discovered, one of the initial observations was that, when all of the insulin peptide was depleted from serum, the vast majority of the insulin activity remained and this was due to a single additional peptide, IGF-II. The IGF-II gene is adjacent to the insulin gene, which is a result of gene duplication, but has evolved to be considerably more complicated. It was one of the first genes recognised to be imprinted and expressed in a parent-of-origin specific manner. The gene codes for IGF-II mRNA, but, in addition, also codes for antisense RNA, long non-coding RNA, and several micro RNA. Recent evidence suggests that each of these have important independent roles in metabolic regulation. It has also become clear that an alternatively spliced form of the insulin receptor may be the principle IGF-II receptor. These recent discoveries have important implications for metabolic disorders and also for cancer, for which there is renewed acknowledgement of the importance of metabolic reprogramming.

Incorporating molecular biomarkers into clinical practice for gastric cancer

Introduction: Gastric cancer is one of the most common causes of cancer-related mortality worldwide. To improve clinical outcomes, it is critical to develop appropriate approaches to diagnosis and treatment. Biomarkers have numerous potential clinical applications, including screening, assessing risk, determining prognosis, monitoring recurrence, and predicting response to treatment. Furthermore, biomarkers may contribute to the development of effective therapies. Areas covered: Here we review recent progress in exploiting GC-specific biomarkers such as protein-coding genes, microRNAs, long noncoding RNAs, and methylated gene promoters. Expert opinion: The development of biomarkers for diagnosing and monitoring gastric cancer and for individualizing therapeutic targets shows great promise for improving gastric cancer management.