Do age-associated DNA methylation changes increase the risk of malignant transformation?

How to Translate DNA Methylation Biomarkers Into Clinical Practice

Recent advances in sequencing technologies provide unprecedented opportunities for epigenetic biomarker development. Particularly the DNA methylation pattern-which is modified at specific sites in the genome during cellular differentiation, aging, and disease-holds high hopes for a wide variety of diagnostic applications. While many epigenetic biomarkers have been described, only very few of them have so far been successfully translated into clinical practice and almost exclusively in the field of oncology. This discrepancy might be attributed to the different demands of either publishing a new finding or establishing a standardized and approved diagnostic procedure. This is exemplified for epigenetic leukocyte counts and epigenetic age-predictions. To ease later clinical translation, the following hallmarks should already be taken into consideration when designing epigenetic biomarkers: 1) Identification of best genomic regions, 2) pre-analytical processing, 3) accuracy of DNA methylation measurements, 4) identification of confounding parameters, 5) accreditation as diagnostic procedure, 6) standardized data analysis, 7) turnaround time, and 8) costs and customer requirements. While the initial selection of relevant genomic regions is usually performed on genome wide DNA methylation profiles, it might be advantageous to subsequently establish targeted assays that focus on specific genomic regions. Development of an epigenetic biomarker for clinical application is a long and cumbersome process that is only initiated with the identification of an epigenetic signature.

Do microenvironmental changes disrupt multicellular organisation with ageing, enacting and favouring the cancer cell phenotype?

Cancer is a singular cellular state, the emergence of which destabilises the homeostasis reached through the evolution to multicellularity. We present the idea that the onset of the cellular disobedience to the metazoan functional and structural architecture, known as the cancer phenotype, is triggered by changes in the cell's external environment that occur with ageing: what ensues is a breach of the social contract of multicellular life characteristic of metazoans. By integrating old ideas with new evidence, we propose that with ageing the environmental information that maintains a multicellular organisation is eroded, rewiring internal processes of the cell, and resulting in an internal shift towards an ancestral condition resulting in the pseudo-multicellular cancer phenotype. Once that phenotype emerges, a new local social contract is built, different from the homeostatic one, leading to tumour formation and the foundation of a novel local ecosystem.

RNAAgeCalc: A multi-tissue transcriptional age calculator

Biological aging reflects decline in physiological functions and is an effective indicator of morbidity and mortality. Numerous epigenetic age calculators are available, however biological aging calculators based on transcription remain scarce. Here, we introduce RNAAgeCalc, a versatile across-tissue and tissue-specific transcriptional age calculator. By performing a meta-analysis of transcriptional age signature across multi-tissues using the GTEx database, we identify 1,616 common age-related genes, as well as tissue-specific age-related genes. Based on these genes, we develop new across-tissue and tissue-specific age predictors. We show that our transcriptional age calculator outperforms other prior age related gene signatures as indicated by the higher correlation with chronological age as well as lower median and median error. Our results also indicate that both racial and tissue differences are associated with transcriptional age. Furthermore, we demonstrate that the transcriptional age acceleration computed from our within-tissue predictor is significantly correlated with mutation burden, mortality risk and cancer stage in several types of cancer from the TCGA database, and offers complementary information to DNA methylation age. RNAAgeCalc is available at http://www.ams.sunysb.edu/~pfkuan/softwares.html#RNAAgeCalc, both as Bioconductor and Python packages, accompanied by a user-friendly interactive Shiny app.

DNA Methylation Age Is More Closely Associated With Infection Risk Than Chronological Age in Kidney Transplant Recipients

Older kidney transplant recipients demonstrate increased rates of infection but decreased rates of rejection compared with younger recipients, suggesting that older transplant patients are functionally overimmunosuppressed. We hypothesized that this is a consequence of reduction in immunological activity due to biological aging and that an immune biological age, as determined by DNA methylation (DNAm), would be associated more strongly with incidence of infection than chronological age.

Methods

DNAm analysis was performed on peripheral blood mononuclear cell collected from 60 kidney transplant recipients representing older (≥age 60 y) and younger (aged 30-59 y) patients 3 months after transplantation. DNAm age was calculated based on methylation status of a panel of CpG sites, which have been previously identified as indicative of biological age.

Results

Correlation was seen between chronological and DNAm age; however, there were many patients with significant differences (either acceleration or slowing) between DNAm age and chronological age. A statistically significant association was seen between increased DNAm age and incidence of infection in the first year after kidney transplantation, whereas no significant association was seen between chronological age and infection.

Conclusions

Assessment of DNAm age holds promise as an approach for patient evaluation and individualization of immune suppression regimens. This analysis may provide insights into the immunological mechanism behind increased incidence of infection observed in older transplant patients. The ability to measure biological age would allow for patient risk stratification and individualization of immunosuppression, improving outcomes for the growing numbers of older patients undergoing kidney transplantation.

Small extracellular vesicles deliver miR-21 and miR-217 as pro-senescence effectors to endothelial cells

The role of epigenetics in endothelial cell senescence is a cutting-edge topic in ageing research. However, little is known of the relative contribution to pro-senescence signal propagation provided by microRNAs shuttled by extracellular vesicles (EVs) released from senescent cells. Analysis of microRNA and DNA methylation profiles in non-senescent (control) and senescent (SEN) human umbilical vein endothelial cells (HUVECs), and microRNA profiling of their cognate small EVs (sEVs) and large EVs demonstrated that SEN cells released a significantly greater sEV number than control cells. sEVs were enriched in miR-21-5p and miR-217, which target DNMT1 and SIRT1. Treatment of control cells with SEN sEVs induced a miR-21/miR-217-related impairment of DNMT1-SIRT1 expression, the reduction of proliferation markers, the acquisition of a senescent phenotype and a partial demethylation of the locus encoding for miR-21. MicroRNA profiling of sEVs from plasma of healthy subjects aged 40-100 years showed an inverse U-shaped age-related trend for miR-21-5p, consistent with senescence-associated biomarker profiles. Our findings suggest that miR-21-5p/miR-217 carried by SEN sEVs spread pro-senescence signals, affecting DNA methylation and cell replication.

Chicken or Egg: Is Clonal Hematopoiesis Primarily Caused by Genetic or Epigenetic Aberrations?

Hematopoietic malignancies, including multiple myeloma, are associated with characteristic mutations and genetic instabilities that drive malignant transformation. On the other hand, tumor formation is also associated with drastic epigenetic aberrations, which can impact the genetic sequence. Therefore, the question arises if malignant transformation is primarily caused by genetic or epigenetic events. The tight connection of these processes becomes obvious by the fact that in several malignancies, as well as in age-related clonal hematopoiesis, mutations are particularly observed in epigenetic writers such as DNMT3A and TET2. On the other hand, specific epigenetic aberrations, so-called “epimutations,” can mimic genomic mutations. In contrast to the genetic sequence, which remains relatively stable throughout life, the epigenome notoriously undergoes drastic changes in normal hematopoietic development and aging. It is conceivable that such epigenetic reorganization, e.g., in 3D chromatin conformation, paves the way for secondary chromosomal instabilities, which then result in tumor-specific genomic changes that further trigger disease progression. This scenario might explain the occurrence of tumor-specific mutations particularly in the elderly. Taken together, the causality dilemma is difficult to solve because genetic and epigenetic aberrations are interlinked during disease development. A better understanding of how the chromatin structure or 3D nuclear organization can evoke specific mutations might provide new perspectives for prevention, early diagnostics, and targeted therapy.

The Link Between Epigenetic Clocks for Aging and Senescence

Replicative senescence of cells in vitro is often considered as counterpart for aging of the organism in vivo. In fact, both processes are associated with functional decay and similar molecular modifications. On epigenetic level, replicative senescence and aging evoke characteristic modifications in the DNA methylation (DNAm) pattern, but at different sites in the genome. Various epigenetic signatures, which are often referred to as epigenetic clocks, provide useful biomarkers: Senescence-associated epigenetic modifications can be used for quality control of cell preparations or to elucidate effects of culture conditions on the state of cellular aging. Age-associated epigenetic modifications hold high expectations to determine chronological age in forensics or to identify parameters that impact on biological aging. Despite these differences, there are some striking similarities between senescence- and age-associated DNAm, such as complete rejuvenation during reprogramming into induced pluripotent stem cells (iPSCs). It is yet unclear what makes epigenetic clocks tick, but there is evidence that the underlying mechanisms of both processes are related to similar modifications in the histone code or higher order chromatin. Replicative senescence therefore appears to be a suitable model system to gain better insight into how organismal aging might be governed epigenetically.

CDKN2A promoter methylation and hepatocellular carcinoma risk: A meta-analysis

AIM

Lots of studies have explored cyclin-dependent kinase inhibitor 2A (CDKN2A) promoter methylation in hepatocellular carcinoma (HCC), but the established results were controversial. Hence, we conducted the meta-analysis to comprehensively investigate the association between CDKN2A promoter methylation and HCC risk.

METHODS

A comprehensive search was implemented through searching PubMed, Web of Science and Embase. Associations of CDKN2A promoter methylation with HCC risk, clinicopathological features, and CDKN2A expression were assessed by the pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Subgroup analyses and meta-regression were served for exploring the potential sources of heterogeneity.

RESULTS

A total of 59 articles including 3067 cases and 2951 controls were incorporated in this meta-analysis. Overall, we observed a high CDKN2A promoter methylation rate (58.18%) in HCC and a significant association between the methylation and HCC risk (OR, 7.07; 95% CI, 5.67-8.80). Furthermore, CDKN2A promoter methylation was robustly associated with decreased mRNA (OR, 13.89; 95% CI, 5.44-35.45) and protein (OR, 48.19; 95% CI, 5.56-417.29). In addition, we found the methylation was related with HBV infection (OR, 3.31; 95% CI, 1.47-7.47), HCV infection (OR, 2.76; 95% CI, 1.80-4.23), cirrhosis status (OR, 1.57; 95% CI, 1.01-2.44) and older age (OR, 1.83; 95% CI, 1.14-2.94).

CONCLUSIONS

Our results indicated that CDKN2A promoter methylation was associated with an enhancive HCC risk and played a crucial role in the process of HCC with a potential value to being a triage marker for HCC.

Valproic acid enforces the priming effect of sphingosine-1 phosphate on human mesenchymal stem cells

Engraftment and homing of mesenchymal stem cells (MSCs) are modulated by priming factors including the bioactive lipid sphingosine-1-phosphate (S1P), by stimulating CXCR4 receptor signaling cascades. However, limited in vivo efficacy and the remaining priming molecules prior to administration of MSCs can provoke concerns regarding the efficiency and safety of MSC priming. Here, we showed that valproic acid (VPA), a histone deacetylase inhibitor, enforced the priming effect of S1P at a low dosage for human umbilical cord-derived MSCs (UC-MSCs). A DNA-methylation inhibitor, 5-azacytidine (5-Aza), and VPA increased the expression of CXCR4 in UC-MSCs. In particular, UC-MSCs primed with a suboptimal dose (50 nM) of S1P in combination with 0.5 mM VPA (VPA+S1P priming), but not 1 µM 5-Aza, significantly improved the migration activity in response to stromal cell-derived factor 1 (SDF-1) concomitant with the activation of both MAPKp42/44 and AKT signaling cascades. Both epigenetic regulatory compounds had little influence on cell surface marker phenotypes and the multi-potency of UC-MSCs. In contrast, VPA+S1P priming of UC-MSCs potentiated the proliferation, colony forming unit-fibroblast, and anti-inflammatory activities, which were severely inhibited in the case of 5-Aza treatment. Accordingly, the VPA+S1P-primed UC-MSCs exhibited upregulation of a subset of genes related to stem cell migration and anti-inflammation response. Thus, the present study demonstrated that VPA enables MSC priming with S1P at a low dosage by enhancing their migration and other therapeutic beneficial activities. This priming strategy for MSCs may provide a more efficient and safe application of MSCs for treating a variety of intractable disorders.

Novel regional age-associated DNA methylation changes within human common disease-associated loci

Background

Advancing age progressively impacts on risk and severity of chronic disease. It also modifies the epigenome, with changes in DNA methylation, due to both random drift and variation within specific functional loci.

Results

In a discovery set of 2238 peripheral-blood genome-wide DNA methylomes aged 19–82 years, we identify 71 age-associated differentially methylated regions within the linkage disequilibrium blocks of the single nucleotide polymorphisms from the NIH genome-wide association study catalogue. This included 52 novel regions, 29 within loci not covered by 450 k or 27 k Illumina array, and with enrichment for DNase-I Hypersensitivity sites across the full range of tissues. These age-associated differentially methylated regions also show marked enrichment for enhancers and poised promoters across multiple cell types. In a replication set of 2084 DNA methylomes, 95.7 % of the age-associated differentially methylated regions showed the same direction of ageing effect, with 80.3 % and 53.5 % replicated to p < 0.05 and p < 1.85 × 10^–8, respectively.

Conclusion

By analysing the functionally enriched disease and trait-associated regions of the human genome, we identify novel epigenetic ageing changes, which could be useful biomarkers or provide mechanistic insights into age-related common diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-1051-8) contains supplementary material, which is available to authorized users.

DNA methylation status defines clinicopathological parameters including survival for patients with clear cell renal cell carcinoma (ccRCC)

Epigenetic alterations in the methylome have been associated with tumor development and progression in renal cell carcinoma (RCC). In this study, 45 tumor samples, 12 tumor-free kidney cortex tissues, and 24 peripheral blood samples from patients with clear cell RCC (ccRCC) were analyzed by genome-wide promoter-directed methylation arrays and related to clinicopathological parameters. Unsupervised hierarchical clustering separated the tumors into two distinct methylation groups (clusters A and B), where cluster B had higher average methylation and increased number of hypermethylated CpG sites (CpGs). Furthermore, tumors in cluster B had, compared with cluster A, a larger tumor diameter (p = 0.033), a higher morphologic grade (p < 0.001), a higher tumor-node-metastasis (TNM) stage (p < 0.001), and a worse prognosis (p = 0.005). Higher TNM stage was correlated to an increase in average methylation level (p = 0.003) and number of hypermethylated CpGs (p = 0.003), whereas a number of hypomethylated CpGs were mainly unchanged. However, the predicted age of the tumors based on methylation profile did not correlate with TNM stage, morphological grade, or methylation cluster. Differently methylated (DM) genes (n = 840) in ccRCC samples compared with tumor-free kidney cortex samples were predominantly hypermethylated and a high proportion were identified as polycomb target genes. The DM genes were overrepresented by transcription factors, ligands, and receptors, indicating functional alterations of significance for ccRCC progression. To conclude, increased number of hypermethylated genes was associated with increased TNM stage of the tumors. DNA methylation classification of ccRCC tumor samples at diagnosis can serve as a clinically applicable prognostic marker in ccRCC.

DNA-methylation in C1R is a prognostic biomarker for acute myeloid leukemia

Background

Epigenetic aberrations play a central role in the pathophysiology of acute myeloid leukemia (AML). It has been shown that molecular signatures based on DNA-methylation (DNAm) patterns can be used for classification of the disease. In this study, we followed the hypothesis that DNAm at a single CpG site might support risk stratification in AML.

Findings

Using DNAm profiles of 194 patients from The Cancer Genome Atlas (TCGA), we identified a CpG site in complement component 1 subcomponent R (C1R) as best suited biomarker: patients with higher methylation at this CpG site (>27 % DNAm) reveal significantly longer overall survival (53 versus 11 months; P < 0.0001). This finding was validated in an independent set of 62 DNAm profiles of cytogenetically normal AML patients (P = 0.009) and with a region-specific pyrosequencing assay in 84 AML samples (P = 0.012). DNAm of C1R correlated with genomic DNAm and gene expression patterns, whereas there was only moderate association with gene expression levels of C1R. These results indicate that DNAm of C1R is a biomarker reflecting chromatin reorganization rather than being of pathophysiological relevance per se. Notably, DNAm of C1R was associated with occurrence of specific genomic mutations that are traditionally used for risk stratification in AML. Furthermore, DNAm of C1R correlates also with overall survival in several other types of cancer, but the prognostic relevance was less pronounced than in AML.

Conclusions

Analysis of DNAm at C1R provides a simple, robust, and cost-effective biomarker to further complement risk assessment in AML.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-015-0153-6) contains supplementary material, which is available to authorized users.

Differences in oral habit and lymphocyte subpopulation affect malignant transformation of patients with oral precancer

BACKGROUND/PURPOSE

In Taiwan, the combination of betel quid chewing, alcohol consumption, and smoking habits increases oral cancer risk by 123-fold compared to persons without these habits. Lymphocyte populations in patients may potentially affect the malignant transformation of oral precancer.

METHODS

A total of 28 patients with oral precancer from our previous cohort were enrolled in this study, and their personal information and oral habits were documented. Their lymphocyte populations (CD4+, CD8+, CD19+, and CD56+) and activation markers (CD25 and CD69) were determined by flow cytometry from 1999 to 2004. After follow up till December 2014, data of patients with/without malignant transformation were recorded, and the relation between oral habits and percentage of initial lymphocyte markers was evaluated using the Student t test and Fisher's exact test.

RESULTS

Ten precancer patients developed oral squamous cell carcinoma with a mean period of malignant transformation of 6.8 ± 2.1 years. Patients with malignant transformation had a mean age of 48.4 ± 5.0 years (n = 10), relatively more than that of patients without malignant transformation (41.6 ± 6.3 years, n = 18) (p < 0.05). An increase was noted in the population of peripheral blood mononuclear cells expressing CD4+CD69+, CD19+CD69+, and CD56+CD69+ (p < 0.05) in precancer patients with malignant transformation. Alcohol consumption showed an association with the malignant transformation of patients with precancer (p = 0.030), whereas betel quid and smoking showed little effect.

CONCLUSION

These results suggest that age, alcohol consumption, and early activation of T cells, B cells, and natural killer cells are crucial in the malignant transformation of oral precancer. Analysis of patient's lymphocyte populations may help predict the malignant transformation of oral precancer.

Epigenetic Aging Signatures Are Coherently Modified in Cancer

Aging is associated with highly reproducible DNA methylation (DNAm) changes, which may contribute to higher prevalence of malignant diseases in the elderly. In this study, we analyzed epigenetic aging signatures in 5,621 DNAm profiles of 25 cancer types from The Cancer Genome Atlas (TCGA). Overall, age-associated DNAm patterns hardly reflect chronological age of cancer patients, but they are coherently modified in a non-stochastic manner, particularly at CpGs that become hypermethylated upon aging in non-malignant tissues. This coordinated regulation in epigenetic aging signatures can therefore be used for aberrant epigenetic age-predictions, which facilitate disease stratification. For example, in acute myeloid leukemia (AML) higher epigenetic age-predictions are associated with increased incidence of mutations in RUNX1, WT1, and IDH2, whereas mutations in TET2, TP53, and PML-PARA translocation are more frequent in younger age-predictions. Furthermore, epigenetic aging signatures correlate with overall survival in several types of cancer (such as lower grade glioma, glioblastoma multiforme, esophageal carcinoma, chromophobe renal cell carcinoma, cutaneous melanoma, lung squamous cell carcinoma, and neuroendocrine neoplasms). In conclusion, age-associated DNAm patterns in cancer are not related to chronological age of the patient, but they are coordinately regulated, particularly at CpGs that become hypermethylated in normal aging. Furthermore, the apparent epigenetic age-predictions correlate with clinical parameters and overall survival in several types of cancer, indicating that regulation of DNAm patterns in age-associated CpGs is relevant for cancer development.

Our genome harbors epigenetic marks, such as DNA methylation (DNAm) at cytosine residues, which govern cellular differentiation. Some epigenetic modifications accumulate throughout life in a highly reproducible manner–they may contribute to the aging process and facilitate reliable age-predictions. So far, little is known how these “epigenetic aging signatures” are modified in cancer tissue and whether or not they are accelerated as compared to normal tissue. In this study, we systematically analyzed age-associated DNAm patterns in many types of cancer. In contrast to non-malignant tissue the epigenetic aging signatures hardly reflect chronological age of cancer patients. This may at least partially be attributed to the fact that cancer is a clonal disease capturing only the epigenetic make-up of the tumor-initiating cell. Notably, the aberrant DNAm patterns are not randomly distributed but reveal co-regulation at regions that become methylated upon aging in non-malignant tissue. Furthermore, we demonstrate that deviations of epigenetic age-predictions correlate with clinical parameters. In fact, they are clearly associated with overall survival in many types of cancer. These findings are particularly important, as they indicate relevance of age-associated DNA methylation patterns for malignant transformation, cancer development and prognosis.

How The Genome Got a Life Span

In the space of little more than a decade, ideas of the human genome have shifted significantly, with the emergence of the notion that the genome an individual changes with development, age, disease, environmental inputs, and time. This paper examines the emergence of the genome with a life span, one that experiences drift, instability and mutability, and a host of other temporal changes. We argue that developments in chromatin biology have provided the basis for this genomic embodiment of experience and exposure. We analyze how time has come to matter for the genome through chromatin, providing analysis of examples in which the human life course is being explored as a set of material changes to chromatin. A genome with a lifespan aligns the molecular and the experiential in new ways, shifting ideas of life stages, their interrelation, and the temporality of health and disease.