The polymorphic variant rs1800734 influences methylation acquisition and allele-specific TFAP4 binding in the MLH1 promoter leading to differential mRNA expression

CpG Island Methylator Phenotype-A Hope for the Future or a Road to Nowhere?

The CpG island methylator phenotype (CIMP) can be regarded as the most notable emanation of epigenetic instability in cancer. Since its discovery in the late 1990s, CIMP has been extensively studied, mainly in colorectal cancers (CRC) and gliomas. Consequently, knowledge on molecular and pathological characteristics of CIMP in CRC and other tumour types has rapidly expanded. Concordant and widespread hypermethylation of multiple CpG islands observed in CIMP in multiple cancers raised hopes for future epigenetically based diagnostics and treatments of solid tumours. However, studies on CIMP in solid tumours were hampered by a lack of generalisability and reproducibility of epigenetic markers. Moreover, CIMP was not a satisfactory marker in predicting clinical outcomes. The idea of targeting epigenetic abnormalities such as CIMP for cancer therapy has not been implemented for solid tumours, either. Twenty-one years after its discovery, we aim to cover both the fundamental and new aspects of CIMP and its future application as a diagnostic marker and target in anticancer therapies.

ramr: an R/Bioconductor package for detection of rare aberrantly methylated regions

MOTIVATION

With recent advances in the field of epigenetics, the focus is widening from large and frequent disease- or phenotype-related methylation signatures to rare alterations transmitted mitotically or transgenerationally (constitutional epimutations). Merging evidence indicate that such constitutional alterations, albeit occurring at a low mosaic level, may confer risk of disease later in life. Given their inherently low incidence rate and mosaic nature, there is a need for bioinformatic tools specifically designed to analyze such events.

RESULTS

We have developed a method (ramr) to identify aberrantly methylated DNA regions (AMRs). ramr can be applied to methylation data obtained by array or next-generation sequencing techniques to discover AMRs being associated with elevated risk of cancer as well as other diseases. We assessed accuracy and performance metrics of ramr and confirmed its applicability for analysis of large public datasets. Using ramr we identified aberrantly methylated regions that are known or may potentially be associated with development of colorectal cancer and provided functional annotation of AMRs that arise at early developmental stages.

AVAILABILITY AND IMPLEMENTATION

The R package is freely available at https://github.com/BBCG/ramr and https://bioconductor.org/packages/ramr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.

Genetic impacts on DNA methylation: research findings and future perspectives

Multiple recent studies highlight that genetic variants can have strong impacts on a significant proportion of the human DNA methylome. Methylation quantitative trait loci, or meQTLs, allow for the exploration of biological mechanisms that underlie complex human phenotypes, with potential insights for human disease onset and progression. In this review, we summarize recent milestones in characterizing the human genetic basis of DNA methylation variation over the last decade, including heritability findings and genome-wide identification of meQTLs. We also discuss challenges in this field and future areas of research geared to generate insights into molecular processes underlying human complex traits.

Transcription Factor AP4 Mediates Cell Fate Decisions: To Divide, Age, or Die

Simple Summary

Here, we review the literature on Activating Enhancer-Binding Protein 4 (AP4)/transcription factor AP4 (TFAP4) function and regulation and its role in cancer. Elevated expression of AP4 was detected in tumors of various organs and is associated with poor patient survival. AP4 is encoded by a Myc target gene and mediates cell fate decisions by regulating multiple processes, such as cell proliferation, epithelial-mesenchymal transition, stemness, apoptosis, and cellular senescence. Thereby, AP4 may be critical for tumor initiation and progression. In this review article, we summarize published evidence showing how AP4 functions as a transcriptional activator and repressor of a plethora of direct target genes in various physiological and pathological conditions. We also highlight the complex interactions of AP4 with c-Myc, N-Myc, p53, lncRNAs, and miRNAs in feed-back loops, which control AP4 levels and mediate AP4 functions. In the future, a better understanding of AP4 may contribute to improved prognosis and therapy of cancer.

Abstract

Activating Enhancer-Binding Protein 4 (AP4)/transcription factor AP4 (TFAP4) is a basic-helix-loop-helix-leucine-zipper transcription factor that was first identified as a protein bound to SV40 promoters more than 30 years ago. Almost 15 years later, AP4 was characterized as a target of the c-Myc transcription factor, which is the product of a prototypic oncogene that is activated in the majority of tumors. Interestingly, AP4 seems to represent a central hub downstream of c-Myc and N-Myc that mediates some of their functions, such as proliferation and epithelial-mesenchymal transition (EMT). Elevated AP4 expression is associated with progression of cancer and poor patient prognosis in multiple tumor types. Deletion of AP4 in mice points to roles of AP4 in the control of stemness, tumor initiation and adaptive immunity. Interestingly, ex vivo AP4 inactivation results in increased DNA damage, senescence, and apoptosis, which may be caused by defective cell cycle progression. Here, we will summarize the roles of AP4 as a transcriptional repressor and activator of target genes and the contribution of protein and non-coding RNAs encoded by these genes, in regulating the above mentioned processes. In addition, proteins interacting with or regulating AP4 and the cellular signaling pathways altered after AP4 dysregulation in tumor cells will be discussed.

The MLH1 polymorphism rs1800734 and risk of endometrial cancer with microsatellite instability

Both colorectal (CRC, 15%) and endometrial cancers (EC, 30%) exhibit microsatellite instability (MSI) due to MLH1 hypermethylation and silencing. The MLH1 promoter polymorphism, rs1800734 is associated with MSI CRC risk, increased methylation and reduced MLH1 expression. In EC samples, we investigated rs1800734 risk using MSI and MSS cases and controls. We found no evidence that rs1800734 or other MLH1 SNPs were associated with the risk of MSI EC. We found the rs1800734 risk allele had no effect on MLH1 methylation or expression in ECs. We propose that MLH1 hypermethylation occurs by different mechanisms in CRC and EC.