Conserved methylation signatures associate with the tumor immune microenvironment and immunotherapy response.

BACKGROUND: Aberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes. METHODS: We performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts. RESULTS: We identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment. CONCLUSIONS: Our findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.

Sixteen Cellular Senescence-associated DNA Methylation Signature Predicts Overall Survival in Patients with Head and Neck Squamous Cell Carcinoma.

OBJECTIVE: To construct a cellular senescence-related DNA methylation model to act as an independent prognosis predictor for patients with head and neck squamous cell carcinoma (HNSCC). METHODS: Methylome, transcriptome and clinical information for 499 HNSCC patients were received from The Cancer Genome Atlas (TCGA) as a training set. An extra independent methylation dataset of 54 patients with oral squamous cell carcinoma (OSCC) was downloaded from the NCBI Gene Expression Omnibus (GEO) database as the validation set. To assess the cellular senescence level of each sample, the senescence score (SS) of each patient was calculated using the transcriptome data via single-sample gene set enrichment analysis (ssGSEA). Least absolute shrinkage and selection operator (LASSO) Cox regression analyses were conducted to confirm Cytosine, phosphoric acid and Guanine (CpG) sites for the development of a cellular senescence-related DNA methylation signature. RESULTS: Based on the SS of each HNSCC patient in the TCGA cohort, the patients were divided into high- and low-SS subgroups. The high-SS group showed a better prognosis than the low-SS group. Moreover, 3,261 differentially methylated CpG sites (DMCs) were confirmed between the two groups. Among them, 16 DMCs were included to develop a 16-DNA methylation signature for evaluation of HNSCC prognosis using LASSO and multivariate Cox regression analysis. CONCLUSION: A novel cellular senescence-related 16-DNA methylation signature was determined, which can be used as an independent index to evaluate the prognosis of HNSCC patients and select appropriate treatment strategies.

An HNRNPK-specific DNA methylation signature makes sense of missense variants and expands the phenotypic spectrum of Au-Kline syndrome.

Au-Kline syndrome (AKS) is a neurodevelopmental disorder associated with multiple malformations and a characteristic facial gestalt. The first individuals ascertained carried de novo loss-of-function (LoF) variants in HNRNPK. Here, we report 32 individuals with AKS (26 previously unpublished), including 13 with de novo missense variants. We propose new clinical diagnostic criteria for AKS that differentiate it from the clinically overlapping Kabuki syndrome and describe a significant phenotypic expansion to include individuals with missense variants who present with subtle facial features and few or no malformations. Many gene-specific DNA methylation (DNAm) signatures have been identified for neurodevelopmental syndromes. Because HNRNPK has roles in chromatin and epigenetic regulation, we hypothesized that pathogenic variants in HNRNPK may be associated with a specific DNAm signature. Here, we report a unique DNAm signature for AKS due to LoF HNRNPK variants, distinct from controls and Kabuki syndrome. This DNAm signature is also identified in some individuals with de novo HNRNPK missense variants, confirming their pathogenicity and the phenotypic expansion of AKS to include more subtle phenotypes. Furthermore, we report that some individuals with missense variants have an "intermediate" DNAm signature that parallels their milder clinical presentation, suggesting the presence of an epi-genotype phenotype correlation. In summary, the AKS DNAm signature may help elucidate the underlying pathophysiology of AKS. This DNAm signature also effectively supported clinical syndrome delineation and is a valuable aid for variant interpretation in individuals where a clinical diagnosis of AKS is unclear, particularly for mild presentations.

Identification of DNA Methylation Signature and Rules for SARS-CoV-2 Associated with Age.

BACKGROUND: COVID-19 displays an increased mortality rate and higher risk of severe symptoms with increasing age, which is thought to be a result of the compromised immunity of elderly patients. However, the underlying mechanisms of aging-associated immunodeficiency against Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains unclear. Epigenetic modifications show considerable changes with age, causing altered gene regulations and cell functions during the aging process. The DNA methylation patterns among patients with coronavirus 2019 disease (COVID-19) who had different ages were compared to explore the effect of aging-associated methylation modifications in SARS-CoV-2 infection. METHODS: Patients with COVID-19 were divided into three groups according to age. Boruta was used on the DNA methylation profiles of the patients to remove irrelevant features and retain essential signature sites to identify substantial aging-associated DNA methylation changes in COVID-19. Next, these features were ranked using the minimum redundancy maximum relevance (mRMR) method, and the feature list generated by mRMR was processed into the incremental feature selection method with decision tree (DT), random forest, k-nearest neighbor, and support vector machine to obtain the key methylation sites, optimal classifier, and decision rules. RESULTS: Several key methylation sites that showed distinct patterns among the patients with COVID-19 who had different ages were identified, and these methylation modifications may play crucial roles in regulating immune cell functions. An optimal classifier was built based on selected methylation signatures, which can be useful to predict the aging-associated disease risk of COVID-19. CONCLUSIONS: Existing works and our predictions suggest that the methylation modifications of genes, such as NHLH2, ZEB2, NWD1, ELOVL2, FGGY, and FHL2, are closely associated with age in patients with COVID-19, and the 39 decision rules extracted with the optimal DT classifier provides quantitative context to the methylation modifications in elderly patients with COVID-19. Our findings contribute to the understanding of the epigenetic regulations of aging-associated COVID-19 symptoms and provide the potential methylation targets for intervention strategies in elderly patients.

The utility of DNA methylation signatures in directing genome sequencing workflow: Kabuki syndrome and CDK13-related disorder.

Kabuki syndrome (KS) is a neurodevelopmental disorder characterized by hypotonia, intellectual disability, skeletal anomalies, and postnatal growth restriction. The characteristic facial appearance is not pathognomonic for KS as several other conditions demonstrate overlapping features. For 20-30% of children with a clinical diagnosis of KS, no causal variant is identified by conventional genetic testing of the two associated genes, KMT2D and KDM6A. Here, we describe two cases of suspected KS that met clinical diagnostic criteria and had a high gestalt match on the artificial intelligence platform Face2Gene. Although initial KS testing was negative, genome-wide DNA methylation (DNAm) was instrumental in guiding genome sequencing workflow to establish definitive molecular diagnoses. In one case, a positive DNAm signature for KMT2D led to the identification of a cryptic variant in KDM6A by genome sequencing; for the other case, a DNAm signature different from KS led to the detection of another diagnosis in the KS differential, CDK13-related disorder. This approach illustrates the clinical utility of DNAm signatures in the diagnostic workflow for the genome analyst or clinical geneticist-especially for disorders with overlapping clinical phenotypes.

Ferroptosis-associated DNA methylation signature predicts overall survival in patients with head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is a common cancer characterized by late diagnosis and poor prognosis. The aim of this study was to identify a novel ferroptosis-related DNA methylation signature as an alternative diagnosis index for patients with HNSCC. METHODS: Methylome and transcriptome data of 499 HNSCC patients, including 275 oral squamous cell carcinoma (OSCC) samples, were obtained from The Cancer Genome Atlas (TCGA). An additional independent methylation dataset of 50 OSCC patients from the NCBI Gene Expression Omnibus (GEO) database was used for validation. As an index of ferroptosis activity, the ferroptosis score (FS) of each patient was inferred from the transcriptome data using single-sample gene set enrichment analysis. Univariate, multivariate, and LASSO Cox regression analyses were used to select CpG sites for the construction of a ferroptosis-related DNA methylation signature for diagnosis of patients. RESULTS: We initially inferred the FS of each TCGA HNSCC patient and divided the samples into high- and low-FS subgroups. Results showed that the high-FS subgroup displayed poor overall survival. Moreover, 378 differentially methylated CpG sites (DMCs) were identified between the two HNSCC subgroups, with 16 selected to construct a 16-DNA methylation signature for risk prediction in HNSCC patients using the LASSO and multivariate Cox regression models. Relative operating characteristic (ROC) curve analysis showed great predictive efficiency for 1-, 3-, and 5-year HNSCC survival using the 16-DNA methylation signature. Its predictive efficiency was also observed in OSCC patients from the TCGA and GEO databases. In addition, we found that the signature was associated with the fractions of immune types in the tumor immune microenvironment (TIME), suggesting potential interactions between ferroptosis and TIME in HNSCC progression. CONCLUSIONS: We established a novel ferroptosis-related 16-DNA methylation signature that could be applied as an alternative tool to predict prognosis outcome in patients with HNSCC, including OSCC.

The diagnostic potential of the epigenome in autism spectrum disorders.

Tweetable abstract The diagnostic application of genome-wide methylation signatures is increasing in various syndromic forms of autism, but further studies are warranted to clarify whether epigenetic biomarkers can be of diagnostic utility in idiopathic ASD.

CpGmotifs: a tool to discover DNA motifs associated to CpG methylation events.

BACKGROUND: The investigation of molecular alterations associated with the conservation and variation of DNA methylation in eukaryotes is gaining interest in the biomedical research community. Among the different determinants of methylation stability, the DNA composition of the CpG surrounding regions has been shown to have a crucial role in the maintenance and establishment of methylation statuses. This aspect has been previously characterized in a quantitative manner by inspecting the nucleotidic composition in the region. Research in this field still lacks a qualitative perspective, linked to the identification of certain sequences (or DNA motifs) related to particular DNA methylation phenomena. RESULTS: Here we present a novel computational strategy based on short DNA motif discovery in order to characterize sequence patterns related to aberrant CpG methylation events. We provide our framework as a user-friendly, shiny-based application, CpGmotifs, to easily retrieve and characterize DNA patterns related to CpG methylation in the human genome. Our tool supports the functional interpretation of deregulated methylation events by predicting transcription factors binding sites (TFBS) encompassing the identified motifs. CONCLUSIONS: CpGmotifs is an open source software. Its source code is available on GitHub https://github.com/Greco-Lab/CpGmotifs and a ready-to-use docker image is provided on DockerHub at https://hub.docker.com/r/grecolab/cpgmotifs .

Truncating SRCAP variants outside the Floating-Harbor syndrome locus cause a distinct neurodevelopmental disorder with a specific DNA methylation signature.

Truncating variants in exons 33 and 34 of the SNF2-related CREBBP activator protein (SRCAP) gene cause the neurodevelopmental disorder (NDD) Floating-Harbor syndrome (FLHS), characterized by short stature, speech delay, and facial dysmorphism. Here, we present a cohort of 33 individuals with clinical features distinct from FLHS and truncating (mostly de novo) SRCAP variants either proximal (n = 28) or distal (n = 5) to the FLHS locus. Detailed clinical characterization of the proximal SRCAP individuals identified shared characteristics: developmental delay with or without intellectual disability, behavioral and psychiatric problems, non-specific facial features, musculoskeletal issues, and hypotonia. Because FLHS is known to be associated with a unique set of DNA methylation (DNAm) changes in blood, a DNAm signature, we investigated whether there was a distinct signature associated with our affected individuals. A machine-learning model, based on the FLHS DNAm signature, negatively classified all our tested subjects. Comparing proximal variants with typically developing controls, we identified a DNAm signature distinct from the FLHS signature. Based on the DNAm and clinical data, we refer to the condition as "non-FLHS SRCAP-related NDD." All five distal variants classified negatively using the FLHS DNAm model while two classified positively using the proximal model. This suggests divergent pathogenicity of these variants, though clinically the distal group presented with NDD, similar to the proximal SRCAP group. In summary, for SRCAP, there is a clear relationship between variant location, DNAm profile, and clinical phenotype. These results highlight the power of combined epigenetic, molecular, and clinical studies to identify and characterize genotype-epigenotype-phenotype correlations.

DNA Methylation Signature for EZH2 Functionally Classifies Sequence Variants in Three PRC2 Complex Genes.

Weaver syndrome (WS), an overgrowth/intellectual disability syndrome (OGID), is caused by pathogenic variants in the histone methyltransferase EZH2, which encodes a core component of the Polycomb repressive complex-2 (PRC2). Using genome-wide DNA methylation (DNAm) data for 187 individuals with OGID and 969 control subjects, we show that pathogenic variants in EZH2 generate a highly specific and sensitive DNAm signature reflecting the phenotype of WS. This signature can be used to distinguish loss-of-function from gain-of-function missense variants and to detect somatic mosaicism. We also show that the signature can accurately classify sequence variants in EED and SUZ12, which encode two other core components of PRC2, and predict the presence of pathogenic variants in undiagnosed individuals with OGID. The discovery of a functionally relevant signature with utility for diagnostic classification of sequence variants in EZH2, EED, and SUZ12 supports the emerging paradigm shift for implementation of DNAm signatures into diagnostics and translational research.

Combined assessment of 3q26 amplification and promoter methylation in patients with high grade cervical lesions show age specific differences.

A considerable proportion of high grade cervical intraepithelial lesions (CIN2/3) are known to resolve on their own especially among young women. However, since reliable prognostic markers are still lacking, the diagnosis "CIN3" is still an indication for surgery which may result in overtreatment. It is conceivable that a combination of different, ideally independent molecular markers may provide more reliable results. In the present cross-sectional study two established triage markers, 3q26 amplification and a methylation signature, were evaluated in an age-dependent manner. The patient cohort comprised 60 patients with histologically confirmed CIN2/3 in two equally sized age groups (<30 years, ≥30 years). Cervical scrapes were analyzed by interphase fluorescence in situ hybridization for 3q26 amplification and methylation specific PCR (GynTect®) for six different genome regions. Both assays showed a significantly different pattern of test outcome independent of age (P = .001). Moreover, the combination of both assays differed significantly for double positive and double negative cases when comparing the two age groups: In patients <30 years there were clearly less cases with positive methylation signature and amplification of 3q26 as in women ≥30 years (23% vs 63%, Bonferroni adjusted P = .016). Of particular interest is the finding that double negative results were exclusive for the young age group (0% vs 27%, Bonferroni adjusted P = .020). Since regression of CIN2/3 characteristically occurs among young women it is tempting to speculate that a double negative test result could be prognostic for regression of CIN2/3. This will have to be investigated further in a prospective longitudinal intervention study.

A five-CpG signature of microRNA methylation in non-G-CIMP glioblastoma.

AIMS: DNA methylation has been found to regulate microRNAs (miRNAs) expression, but the prognostic value of miRNA-related DNA methylation aberration remained largely elusive in cancers including glioblastomas (GBMs). This study aimed to investigate the clinical and biological feature of miRNA methylation in GBMs of non-glioma-CpG island methylator phenotype (non-G-CIMP). METHODS: Prognostic miRNA methylation loci were analyzed, with TCGA and Rennes cohort as training sets, and independent datasets of GBMs and low-grade gliomas (LGGs) were obtained as validation sets. Different statistical and bioinformatic analysis and experimental validations were performed to clinically and biologically characterize the signature. RESULTS: We identified and validated a risk score based on methylation status of five miRNA-associated CpGs which could predict survival of GBM patients in a series of training and validation sets. This signature was independent of age and O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. The risk subgroup was associated with angiogenesis and accordingly differential responses to bevacizumab-contained therapy. MiRNA target analysis and in vitro experiments further confirmed the accuracy of this signature. CONCLUSION: The five-CpG signature of miRNA methylation was biologically relevant and was of potential prognostic and predictive value for GBMs. It might be of help for improving individualized treatment.

Epipolymorphisms associated with the clinical outcome of autoimmune arthritis affect CD4+ T cell activation pathways.

Multifactorial diseases, including autoimmune juvenile idiopathic arthritis (JIA), result from a complex interplay between genetics and environment. Epigenetic mechanisms are believed to integrate such gene-environment interactions, fine-tuning gene expression, and possibly contributing to immune system dysregulation. Although anti-TNF therapy has strongly increased JIA remission rates, it is not curative and up to 80% of patients flare upon treatment withdrawal. Thus, a crucial unmet medical and scientific need is to understand the immunological mechanisms associated with remission or flare to inform clinical decisions. Here, we explored the CD4+ T-cell DNA methylome of 68 poly-articular and extended oligo-articular JIA patients, before and after anti-TNF therapy withdrawal, to identify features associated with maintenance of inactive disease. Individual CpG sites were clustered in coherent modules without a priori knowledge of their function through network analysis. The methylation level of several CpG modules, specifically those enriched in CpG sites belonging to genes that mediate T-cell activation, uniquely correlated with clinical activity. Differences in DNA methylation were already detectable at the time of therapy discontinuation, suggesting epigenetic predisposition. RNA profiling also detected differences in T-cell activation markers (including HLA-DR) but, overall, its sensitivity was lower than epigenetic profiling. Changes to the T-cell activation signature at the protein level were detectable by flow cytometry, confirming the biological relevance of the observed alterations in methylation. Our work proposes epigenetic discrimination between clinical activity states, and reveals T-cell-related biological functions tied to, and possibly predicting or causing, clinical outcome.