Discovery and validation of DNA hypomethylation biomarkers for liver cancer using HRM-specific probes

Fc receptor-like A promotes malignant behavior in renal cell carcinoma and correlates with tumor immune infiltration

BACKGROUND

Our study aims to investigate the mechanisms through which Fc receptor-like A (FCRLA) promotes renal cell carcinoma (RCC) and to examine its significance in relation to tumor immune infiltration.

MATERIALS AND METHODS

The correlation between FCRLA and data clinically related to RCC was explored using The Cancer Genome Atlas (TCGA), then validated using Gene Expression Omnibus (GEO) gene chip data. Enrichment and protein-protein interaction (PPI) network analyses were performed for FCRLA and its co-expressed genes. FCRLA was knocked down in RCC cell lines to evaluate its impact on biological behavior. Then the potential downstream regulators of FCRLA were determined by western blotting, and rescue experiments were performed for verification. The relevance between FCRLA and various immune cells was analyzed through GSEA, TIMER, and GEPIA tools. TIDE and ESTIMATE algorithms were used to predict the effect of FCRLA in immunotherapy.

RESULTS

Fc receptor-like A was associated with clinical and T stages and could predict the M stage (AUC = 0.692) and 1-3- and 5-year survival rates (AUC = 0.823, 0.834, and 0.862) of RCC patients. Higher expression of FCLRA predicted an unfavorable overall survival (OS) in TCGA-RCC and GSE167573 datasets (p = 0.03, p = 0.04). FCRLA promoted the malignant biological behavior of RCC cells through the pERK1/2/-MMP2 pathway and was associated with tumor immune microenvironment in RCC.

CONCLUSION

Fc receptor-like A is positively correlated with poor outcomes in RCC patients and plays an oncogenic role in RCC through the pERK1/2-MMP2 pathway. Patients with RCC might benefit from immunotherapy targeting FCRLA.

Epigenetic aberrations of gene expression in a rat model of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is mostly triggered by environmental and life-style factors and may involve epigenetic aberrations. However, a comprehensive documentation of the link between the dysregulated epigenome, transcriptome, and liver carcinogenesis is lacking. In the present study, Fischer-344 rats were fed a choline-deficient (CDAA, cancer group) or choline-sufficient (CSAA, healthy group) L-amino acid-defined diet. At the end of 52 weeks, transcriptomic alterations in livers of rats with HCC tumours and healthy livers were investigated by RNA sequencing. DNA methylation and gene expression were assessed by pyrosequencing and quantitative reverse-transcription PCR (qRT-PCR), respectively. We discovered 1,848 genes that were significantly differentially expressed in livers of rats with HCC tumours (CDAA) as compared with healthy livers (CSAA). Upregulated genes in the CDAA group were associated with cancer-related functions, whereas macronutrient metabolic processes were enriched by downregulated genes. Changes of highest magnitude were detected in numerous upregulated genes that govern key oncogenic signalling pathways, including Notch, Wnt, Hedgehog, and extracellular matrix degradation. We further detected perturbations in DNA methylating and demethylating enzymes, which was reflected in decreased global DNA methylation and increased global DNA hydroxymethylation. Four selected upregulated candidates, Mmp12, Jag1, Wnt4, and Smo, demonstrated promoter hypomethylation with the most profound decrease in Mmp12. MMP12 was also strongly overexpressed and hypomethylated in human HCC HepG2 cells as compared with primary hepatocytes, which coincided with binding of Ten-eleven translocation 1 (TET1). Our findings provide comprehensive evidence for gene expression changes and dysregulated epigenome in HCC pathogenesis, potentially revealing novel targets for HCC prevention/treatment.

A Prognostic Model Based on Nine DNA Methylation-Driven Genes Predicts Overall Survival for Colorectal Cancer

Background: Colorectal cancer (CRC) is the third most frequently diagnosed malignancy and the fourth leading cause of cancer-related death among common tumors in the world. We aimed to establish and validate a risk assessment model to predict overall survival (OS) for the CRC patients.

Methods: DNA methylation-driven genes were identified by integrating DNA methylation profile and transcriptome data from The Cancer Genome Atlas (TCGA) CRC cohort. Then, a risk score model was built based on LASSO, univariable Cox and multivariable Cox regression analysis. After analyzing the clinicopathological factors, a nomogram was constructed and assessed. Another cohort from GEO was used for external validation. Afterward, the molecular and immune characteristics in the two risk score groups were analyzed.

Results: In total, 705 methylation-driven genes were identified. Based on the LASSO and Cox regression analyses, nine genes, i.e., LINC01555, GSTM1, HSPA1A, VWDE, MAGEA12, ARHGAP, PTPRD, ABHD12B and TMEM88, were selected for the development of a risk score model. The Kaplan–Meier curve indicated that patients in the low-risk group had considerably better OS (P = 2e-08). The verification performed in subgroups demonstrated the validity of the model. Then, we established an OS-associated nomogram that included the risk score and significant clinicopathological factors. The concordance index of the nomogram was 0.81. A comprehensive molecular and immune characteristics analysis showed that the high-risk group was associated with tumor invasion, infiltration of immune cells executing pro-tumor suppression (such as myeloid-derived suppressor cells, regulatory T cells, immature dendritic cells) and higher expression of common inhibitory checkpoint molecules (ICPs).

Conclusion: Our nine-gene associated risk assessment model is a promising signature to distinguish the prognosis for CRC patients. It is expected to serve as a predictive tool with high sensitivity and specificity for individualized prediction of OS in the patients with CRC.

The ability of arsenic metabolism affected the expression of lncRNA PANDAR, DNA damage, or DNA methylation in peripheral blood lymphocytes of laborers

Arsenic has been associated with significant effects on human health. Exposure to inorganic arsenic has been associated with the changes in gene expression. Promoter of CDKN1A antisense DNA damage activated RNA (PANDAR) expression is induced by p53 protein and DNA damage response. Here, we investigated whether the ability of arsenic metabolism in individuals affected the expression of PANDAR, DNA damage, and DNA methylation. Levels of gene expression and DNA damage were examined by the quantitative polymerase chain reaction and DNA methylation was measured by the methylation-sensitive high-resolution melting curve. In our study, we demonstrated that arsenic exposure increased PANDAR expression and DNA damage among arsenic smelting plant laborers. The PANDAR expression and DNA damage were positively linked to monomethylarsonic acid % (R = 0.25, p < 0.05 and R = 0.32, p < 0.01) and negatively linked to dimethylarsinic acid % (R = -0.21, p < 0.05 and R = -0.31, p < 0.01). Subjects with low primary methylation index had increased levels of DNA damage (51.62 ± 2.96 vs. 60.93 ± 3.10, p < 0.05) and methylation (17.14 (15.88-18.51) vs. 15.83 (14.82-18.00), p < 0.05). Subjects with low secondary methylation index had increased levels of PANDAR expression (4.88 ± 0.29 vs. 4.07 ± 0.23, p < 0.01) and DNA damage (17.38 (15.88-19.29) vs. 15.83 (14.82-17.26), p < 0.01). DNA methylation of PANDAR gene was linked to the regulation of its expression in peripheral blood lymphocytes among laborers (Y = -2.08 × X + 5.64, p < 0.05). These findings suggested arsenic metabolism ability and exposure affected the expression of PANDAR, DNA damage, and DNA methylation.

Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is growing in incidence but treatment options remain limited, particularly for late stage disease. As liver cirrhosis is the principal risk state for HCC development, markers to detect early HCC within this patient population are urgently needed. Perturbation of epigenetic marks, such as DNA methylation (5mC), is a hallmark of human cancers, including HCC. Identification of regions with consistently altered 5mC levels in circulating cell free DNA (cfDNA) during progression from cirrhosis to HCC could therefore serve as markers for development of minimally-invasive screens of early HCC diagnosis and surveillance. Methods: To discover DNA methylation derived biomarkers of HCC in the background of liver cirrhosis, we profiled genome-wide 5mC landscapes in patient cfDNA using the Infinium HumanMethylation450k BeadChip Array. We further linked these findings to primary tissue data available from TCGA and other public sources. Using biological and statistical frameworks, we selected CpGs that robustly differentiated cirrhosis from HCC in primary tissue and cfDNA followed by validation in an additional independent cohort. Results: We identified CpGs that segregate patients with cirrhosis, from patients with HCC within a cirrhotic liver background, through genome-wide analysis of cfDNA 5mC landscapes. Lasso regression analysis pinpointed a panel of probes in our discovery cohort that were validated in two independent datasets. A panel of five CpGs (cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777) yielded area under the receiver operating characteristic (AUROC) curves of 0.9525, 0.9714, and 0.9528 in cfDNA discovery and tissue validation cohorts 1 and 2, respectively. Validation of a 5-marker panel created from combining hypermethylated and hypomethylated CpGs in an independent cfDNA set by bisulfite pyrosequencing yielded an AUROC of 0.956, compared to the discovery AUROC of 0.996. Conclusion: Our finding that 5mC markers derived from primary tissue did not perform well in cfDNA, compared to those identified directly from cfDNA, reveals potential advantages of starting with cfDNA to discover high performing markers for liquid biopsy development.

ZCCHC13-mediated induction of human liver cancer is associated with the modulation of DNA methylation and the AKT/ERK signaling pathway

BACKGROUND

Previous studies have shown that zinc-finger CCHC-type containing 13 (ZCCHC13) is located in an imprinted gene cluster in the X-inactivation centre, but few published studies have provided evidence of its expression in cancers. The CCHC-type zinc finger motif has numerous biological activities (such as DNA binding and RNA binding) and mediates protein-protein interactions. In an effort to examine the clinical utility of ZCCHC13 in oncology, we investigated the expression of the ZCCHC13 mRNA and protein in hepatocellular carcinoma (HCC).

METHODS

The expression of the ZCCHC13 mRNA and protein was evaluated using real-time reverse transcriptase-PCR, Western blotting and immunochemistry. DNA methylation was measured by methylation-specific PCR and bisulfite sequencing. The role of ZCCHC13 methylation was further evaluated using the demethylating agent, 5-aza-2'-deoxycytidine. The presence of anti-ZCCHC13 antibodies was determined by an ELISA.

RESULTS

ZCCHC13 expression was frequently upregulated in human liver cancer cells and tissues. Compared with heathy individuals, sera from patients with HCC displayed a significant response to the recombinant ZCCHC13 protein. The overexpression of ZCCHC13 in HCC was attributed to DNA hypomethylation in the promoter region. Moreover, overexpression of ZCCHC13 in liver cancer cells promoted cell cycle progression by facilitating the G1-S transition, which was related to aberrant activation of the ATK/ERK/c-MYC/CDK pathway.

CONCLUSIONS

Based on our findings, ZCCHC13 functions an oncogene for HCC, and DNA hypomethylation is a driving factor in carcinogenesis.

Loci-specific differences in blood DNA methylation in HBV-negative populations at risk for hepatocellular carcinoma development

Late onset of clinical symptoms in hepatocellular carcinoma (HCC) results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable tools that would distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed. We used the Illumina HumanMethylation450 BeadChip microarray to test whether white blood cell DNA, an easily accessible source of DNA, exhibits site-specific changes in DNA methylation in blood of diagnosed HCC patients (post-diagnostic, 24 cases, 24 controls) and in prospectively collected blood specimens of HCC patients who were cancer-free at blood collection (pre-diagnostic, 21 cases, 21 controls). Out of 22 differentially methylated loci selected for validation by pyrosequencing, 19 loci with neighbouring CpG sites (probes) were confirmed in the pre-diagnostic study group and subjected to verification in a prospective cirrhotic cohort (13 cases, 23 controls). We established for the first time 9 probes that could distinguish HBV-negative cirrhotic patients who subsequently developed HCC from those who stayed cancer-free. These probes were identified within regulatory regions of BARD1, MAGEB3, BRUNOL5, FXYD6, TET1, TSPAN5, DPPA5, KIAA1210, and LSP1. Methylation levels within DPPA5, KIAA1210, and LSP1 were higher in prospective samples from HCC cases vs. cirrhotic controls. The remaining probes were hypomethylated in cases compared with controls. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established probes have potential to be developed into a routine clinical test after validation in larger cohorts.

Aberrant promoter methylation profiles and association with survival in patients with hepatocellular carcinoma

The aim of this study was to investigate the prognostic and diagnostic value of genes with promoter methylation in hepatocellular carcinoma (HCC) patients. On the basis of The Cancer Genome Atlas data, we identified genes with differentially methylated promoters in HCC tissues and adjacent non-tumor tissues, using the linear models for microarray data approach. Cox proportional hazard regression analysis was applied to access the prognostic value of identified differentially methylated genes. The diagnostic value of the genes was evaluated through receiver operating characteristic. Pathway analyses were performed to illustrate biological functions of the identified genes. Compared to adjacent tissues, 77 genes with hypermethylated promoters and 2,412 genes with hypomethylated promoters were identified in HCC. The promoter hypomethylations of RNA5SP38, IL21, SDC4P, and MIR4439 were found to be associated with HCC patient survival (P=0.035, 0.040, 0.004, and 0.024, respectively). Hypomethylated SDC4P was associated with a better prognosis (hazard ratio, 0.482; 95% confidence interval [CI], −0.147–1.110; P=0.007). The combination of the promoter hypomethylations with RNA5SP38, IL21, and SDC4P showed an area under receiver operating characteristic curves of 0.975 (95% CI, 0.962–0.989; P=4.811E-25). Several pathways, including olfactory transduction, cytokine–cytokine receptor interaction, natural killer cell–mediated cytotoxicity, as well as inflammation mediated by chemokine and cytokine signaling pathway, were annotated with the hypomethylated promoter genes. SDC4P promoter hypomethylation may be a potential prognosis biomarker. A panel of promoter methylations in RNA5SP38, IL21, and SDC4P was proven a novel approach to diagnosis HCC. The pathway analysis defined the extensive functional role of DNA hypomethylation in cancer.

Stilbenoids remodel the DNA methylation patterns in breast cancer cells and inhibit oncogenic NOTCH signaling through epigenetic regulation of MAML2 transcriptional activity

DNA hypomethylation was previously implicated in cancer progression and metastasis. The purpose of this study was to examine whether stilbenoids, resveratrol and pterostilbene thought to exert anticancer effects, target genes with oncogenic function for de novo methylation and silencing, leading to inactivation of related signaling pathways. Following Illumina 450K, genome-wide DNA methylation analysis reveals that stilbenoids alter DNA methylation patterns in breast cancer cells. On average, 75% of differentially methylated genes have increased methylation, and these genes are enriched for oncogenic functions, including NOTCH signaling pathway. MAML2, a coactivator of NOTCH targets, is methylated at the enhancer region and transcriptionally silenced in response to stilbenoids, possibly explaining the downregulation of NOTCH target genes. The increased DNA methylation at MAML2 enhancer coincides with increased occupancy of repressive histone marks and decrease in activating marks. This condensed chromatin structure is associated with binding of DNMT3B and decreased occupancy of OCT1 transcription factor at MAML2 enhancer, suggesting a role of DNMT3B in increasing methylation of MAML2 after stilbenoid treatment. Our results deliver a novel insight into epigenetic regulation of oncogenic signals in cancer and provide support for epigenetic-targeting strategies as an effective anticancer approach.

Recursive Random Lasso (RRLasso) for Identifying Anti-Cancer Drug Targets

Uncovering driver genes is crucial for understanding heterogeneity in cancer. L1-type regularization approaches have been widely used for uncovering cancer driver genes based on genome-scale data. Although the existing methods have been widely applied in the field of bioinformatics, they possess several drawbacks: subset size limitations, erroneous estimation results, multicollinearity, and heavy time consumption. We introduce a novel statistical strategy, called a Recursive Random Lasso (RRLasso), for high dimensional genomic data analysis and investigation of driver genes. For time-effective analysis, we consider a recursive bootstrap procedure in line with the random lasso. Furthermore, we introduce a parametric statistical test for driver gene selection based on bootstrap regression modeling results. The proposed RRLasso is not only rapid but performs well for high dimensional genomic data analysis. Monte Carlo simulations and analysis of the "Sanger Genomics of Drug Sensitivity in Cancer dataset from the Cancer Genome Project" show that the proposed RRLasso is an effective tool for high dimensional genomic data analysis. The proposed methods provide reliable and biologically relevant results for cancer driver gene selection.

Obesity and ischemic stroke modulate the methylation levels of KCNQ1 in white blood cells

Obesity and stroke are multifactorial diseases in which genetic, epigenetic and lifestyle factors are involved. The research aims were, first, the description of genes with differential epigenetic regulation obtained by an 'omics' approach in patients with ischemic stroke and, second, to determine the importance of some regions of these selected genes in biological processes depending on the body mass index. A case-control study using two populations was designed. The first population consisted of 24 volunteers according to stroke/non-stroke and normal weight/obesity conditions. The second population included 60 stroke patients and 55 controls classified by adiposity. DNA from the first population was analyzed with a methylation microarray, showing 80 cytosine-guanine dinucleotides (CpG) sites differentially methylated in stroke and 96 CpGs in obesity, whereas 59 CpGs showed interaction. After validating these data by MassArray Epityper, the promoter region of peptidase M20 domain containing 1 (PM20D1) gene was significantly hypermethylated in stroke patients. One CpG site at Caldesmon 1 (CALD1) gene showed an interaction between stroke and obesity. Two CpGs located in the genes Wilms' tumor 1 (WT1) and potassium voltage-gated channel, KQT-like subfamily, member 1 (KCNQ1) were significantly hypermethylated in obese patients. In the second population, KCNQ1 was also hypermethylated in the obese subjects. Two CpGs of this gene were subsequently validated by methylation-sensitive high-resolution melting. Moreover, KCNQ1 methylation levels were associated with plasma KCNQ1 protein concentrations. In conclusion, obesity induced changes in the KCNQ1 methylation pattern which were also dependent on stroke. Furthermore, the epigenetic marks differentially methylated in the stroke patients were dependent on the previous obese state. These DNA methylation patterns could be used as future potential stroke biomarkers.

SH2B1 CpG-SNP is associated with body weight reduction in obese subjects following a dietary restriction program

The objective of this study was to examine whether 7 SNPs previously associated with obesity-related traits that add or remove potential sites of DNA methylation are accompanied by differential DNA methylation and subsequently affect adiposity variables or body weight reduction in WBC from obese subjects under an energy-restricted program.

MATERIAL AND METHODS

Anthropometric measurements were assessed in 47 volunteers recruited within the RESMENA study (Spain). At baseline, DNA from white blood cells was isolated and 7 obesity-related trait CpG-SNPs were genotyped by TaqMan-PCR. Then, methylation levels of CpG-SNP sites were quantified by MassArray® EpiTyper™ or MS-HRM approaches.

RESULTS

Differential DNA methylation levels were observed by genotypes in all of the CpG-SNPs analyzed. The FTO and BDNF methylation levels were further correlated with baseline body weight and, BDNF mRNA levels and body weight change, respectively. Moreover, the rs7359397 (SH2B1) was associated with the body weight, body mass index, and truncal fat mass reduction.

CONCLUSIONS

Our results reveal the interaction of epigenetic and genetic variations in CpG-SNPs, especially in BDNF and SH2B1 genes, and how allele-specific methylation may contribute to elucidate the possible molecular mechanisms as these SNPs are affecting the decrease of mRNA levels and contributing to a lower body weight reduction.