Use Of DNA Methylation Research Articles

Exploring the use of immunomethylomics in the characterization of depressed patients: A proof-of-concept study

Alterations in DNA methylation and inflammation could represent valid biomarkers for the stratification of patients with major depressive disorder (MDD). This study explored the use of DNA-methylation based immunological cell-type profiles in the context of MDD and symptom severity over time.In 119 individuals with MDD, DNA-methylation was assessed on whole blood using the Illumina Infinium MethylationEPIC 850 k BeadChip. Quality control and data processing, as well as cell type estimation was conducted using the RnBeads package. The cell type composition was estimated using epigenome-wide DNA methylation signatures, applying the Houseman method, considering six cell types (neutrophils, natural killer cells (NK), B cells, CD4+ T cells, CD8+ T cells and monocytes). Two cytokines (IL-6 and IL-1β) and hsCRP were quantified in serum. We performed a hierarchical cluster analysis on the six estimated cell-types and tested the differences between these clusters in relation to the two cytokines and hsCRP, depression severity at baseline, and after 6 weeks of treatment (celecoxib/placebo + vortioxetine). We performed a second cluster analysis with cell-types and cytokines combined. ANCOVA was used to test for differences across clusters. We applied the Bonferroni correction.After quality control, we included 113 participants. Two clusters were identified, cluster 1 was high in CD4+ cells and NK, cluster 2 was high in CD8+ T-cells and B-cells, with similar fractions of neutrophils and monocytes. The clusters were not associated with either of the two cytokines and hsCRP, or depression severity at baseline, but cluster 1 showed higher depression severity after 6 weeks, corrected for baseline (p = 0.0060). The second cluster analysis found similar results: cluster 1 was low in CD8+ T-cells, B-cells, and IL-1β. Cluster 2 was low in CD4+ cells and natural killer cells. Neutrophils, monocytes, IL-6 and hsCRP were not different between the clusters. Participants in cluster 1 showed higher depression severity at baseline than cluster 2 (p = 0.034), but no difference in depression severity after 6 weeks.DNA-methylation based cell-type profiles may be valuable in the immunological characterization and stratification of patients with MDD. Future models should consider the inclusion of more cell-types and cytokines for better a prediction of treatment outcomes.

DNA methylation risk scores for depression, not today

IntroductionAfter the success of polygenic risk scores (PRS) that embed a useful summary of genomic information in a comprehensive score, the wish to develop summary statistics for DNA methylation had become more pressing. Developing such a score faces challenges, as the score has to be specific and sensitive as well. Epidemiological research on DNA methylation and depression would benefit from such score.Objectives Here, we test a score trained on incident depression (case-control), i.e., a list of published weights for particular CpGs, for its validity in the context of depression severity as measured using MADRS in our sample with depressed patients only.MethodsDNA methylation was assessed using the Illumina Infinium MethylationEPIC 850k BeadChip on a sample of 119 patients with a diagnosis of MDD. After data cleaning, 113 participants were included in the analysis (Mage= 47 years, 57.98% women, MMADRS=27.7). Data processing was conducted using the RnBeads package. From the published reference for the overall sample, a list of 196 CpGs was provided, 170 of these were present in our dataset and used for the score. The list of non-smokers comprised 144 CpGs, of which 124 were available. The score per individual was built using M-values, using the formula: S(weight*DNA methylation value). The score was tested in association with depression and other typical confounders using multiple regression in R. Confounders included ancestry, BMI, age, sex, and 6 cell types. We tested both scores in our sample: smokers and non-smokers.ResultsIn contrast to our expectations, none of the regression analyses showed a significant association with depression (MADRS-score). Nonetheless, a significant association was seen with biological sex for both analysis (overall: p=0.036, non-smokers: p=0.026). A reduced model with only this predictor explained 5% and 4% of the variance of the summary score calculated (R2), respectively (overall: p=0.013; non-smokers: p=0.019). One of the ancestry components was marginally significant too in the non-smoker summary score (p=0.065). This was not the case anymore in the reduced model.Conclusions Our results show that caution is still in place when using methylation risk scores as specificity and sensitivity might not yet be optimized. The score built for depression incidence does not seem fitting for depression severity at this moment. The use of DNA methylation, a marker that is generally sensitive to confounding factors, for a risk score, might pose more challenges in the context of reliable summary statistics, in particular also for cross-trait examination, which is currently a typical use of polygenic risk scores.Disclosure of InterestNone Declared

DNA methylation-based age prediction with bloodstains using pyrosequencing and random forest regression.

The use of DNA methylation to predict chronological age has shown promising potential for obtaining additional information in forensic investigations. To date, several studies have reported age prediction models based on DNA methylation in body fluids with high DNA content. However, it is often difficult to apply these existing methods in practice due to the low amount of DNA present in stains of body fluids that are part of a trace material. In this study, we present a sensitive and rapid test for age prediction with bloodstains based on pyrosequencing and random forest regression. This assay requires only 0.1ng of genomic DNA and the entire procedure can be completed within 10h, making it practical for forensic investigations that require a short turnaround time. We examined the methylation levels of 46 CpG sites from six genes using bloodstain samples from 128 males and 113 females aged 10-79 years. A random forest regression model was then used to construct an age prediction model for males and females separately. The final age prediction models were developed with seven CpG sites (three for males and four for females) based on the performance of the random forest regression. The mean absolute deviation was less than 3 years for each model. Our results demonstrate that DNA methylation-based age prediction using pyrosequencing and random forest regression has potential applications in forensics to accurately predict the biological age of a bloodstain donor.

CpG Site-Based Signature Predicts Survival of Colorectal Cancer.

A critical unmet medical need in clinical management of colorectal cancer (CRC) pivots around lack of noninvasive and or minimally invasive techniques for early diagnosis and prognostic prediction of clinical outcomes. Because DNA methylation can capture the regulatory landscape of tumors and can be measured in body fluids, it provides unparalleled opportunities for the discovery of early diagnostic and prognostics markers predictive of clinical outcomes. Here we investigated use of DNA methylation for the discovery of potential clinically actionable diagnostic and prognostic markers for predicting survival in CRC. We analyzed DNA methylation patterns between tumor and control samples to discover signatures of CpG sites and genes associated with CRC and predictive of survival. We conducted functional analysis to identify molecular networks and signaling pathways driving clinical outcomes. We discovered a signature of aberrantly methylated genes associated with CRC and a signature of thirteen (13) CpG sites predictive of survival. We discovered molecular networks and signaling pathways enriched for CpG sites likely to drive clinical outcomes. The investigation revealed that CpG sites can predict survival in CRC and that DNA methylation can capture the regulatory state of tumors through aberrantly methylated molecular networks and signaling pathways.

Can we integrate method-specific age-predictive models?: Analysis method-induced differences in detected DNA methylation status

Forensic research surrounding the use of DNA methylation (DNAm) markers to predict age suggests that accurate prediction of chronological age can be achieved with just several DNAm markers. Several age-prediction models are based on DNAm levels that are detectable by a diverse range of DNAm analysis methods. Among the many DNAm analysis methods, targeted amplicon-based massively parallel sequencing (MPS) and single-base extension (SBE) methods have been widely studied owing to their practicality, including their multiplex capabilities. Since these two DNAm analysis methods share an identical amplification step during their experimental processes, several studies have compared the differences between the methods to construct integrated age-prediction models based on both MPS and SBE data. In this study, we compared the specific differences in DNAm levels between these two commonly exploited analysis methods by analyzing the identical PCR amplicons from the same samples and quantifying the actual bisulfite-converted DNA amount involved in the PCR step. The DNAm levels of five well-studied age-associated markers—CpGs on the ELOVL2, FHL2, KLF14, MIR29B2CHG, and TRIM59 genes—were obtained from blood samples of 250 Koreans using both DNAm analysis methods. The results showed that only ELOVL2 is interchangeable between the MPS and SBE methods, while the rest of the markers showed significant differences in DNAm values. These differences may result in high errors and consequential lowered accuracy in age estimates. Therefore, a DNAm analysis method-specific approach that considers method-induced DNAm differences is recommended to improve the overall accuracy and reliability of age-prediction methods.

DNA methylation levels of RELN promoter region in ultra-high risk, first episode and chronic schizophrenia cohorts of schizophrenia

The essential role of the Reelin gene (RELN) during brain development makes it a prominent candidate in human epigenetic studies of Schizophrenia. Previous literature has reported differing levels of DNA methylation (DNAm) in patients with psychosis. Therefore, this study aimed to (1) examine and compare RELN DNAm levels in subjects at different stages of psychosis cross-sectionally, (2) analyse the effect of antipsychotics (AP) on DNAm, and (3) evaluate the effectiveness and applicability of RELN promoter DNAm as a possible biological-based marker for symptom severity in psychosis.. The study cohort consisted of 56 healthy controls, 87 ultra-high risk (UHR) individuals, 26 first-episode (FE) psychosis individuals and 30 chronic schizophrenia (CS) individuals. The Positive and Negative Syndrome Scale (PANSS) was used to assess Schizophrenia severity. After pyrosequencing selected CpG sites of peripheral blood, the Average mean DNAm levels were compared amongst the 4 subgroups. Our results showed differing levels of DNAm, with UHR having the lowest (7.72 ± 0.19) while the CS had the highest levels (HC: 8.78 ± 0.35; FE: 7.75 ± 0.37; CS: 8.82 ± 0.48). Significantly higher Average mean DNAm levels were found in CS subjects on AP (9.12 ± 0.61) compared to UHR without medication (UHR(−)) (7.39 ± 0.18). A significant association was also observed between the Average mean DNAm of FE and PANSS Negative symptom factor (R2 = 0.237, ß = −0.401, *p = 0.033). In conclusion, our findings suggested different levels of DNAm for subjects at different stages of psychosis. Those subjects that took AP have different DNAm levels. There were significant associations between FE DNAm and Negative PANSS scores. With more future experiments and on larger cohorts, there may be potential use of DNAm of the RELN gene as one of the genes for the biological-based marker for symptom severity in psychosis.

DNA methylation-based epigenetic signatures predict somatic genomic alterations in gliomas

Molecular classification has improved diagnosis and treatment for patients with malignant gliomas. However, classification has relied on individual assays that are both costly and slow, leading to frequent delays in treatment. Here, we propose the use of DNA methylation, as an emerging clinical diagnostic platform, to classify gliomas based on major genomic alterations and provide insight into subtype characteristics. We show that using machine learning models, DNA methylation signatures can accurately predict somatic alterations and show improvement over existing classifiers. The established Unified Diagnostic Pipeline (UniD) we develop is rapid and cost-effective for genomic alterations and gene expression subtypes diagnostic at early clinical phase and improves over individual assays currently in clinical use. The significant relationship between genetic alteration and epigenetic signature indicates broad applicability of our approach to other malignancies.

Abstract 3473: Use of DNA methylation from tumor and plasma to identify four major small cell lung cancer subtypes with distinct biology and therapeutic vulnerabilities

Abstract Small cell lung cancer (SCLC) is a highly aggressive cancer with limited treatment options and generally poor prognosis. Treatment of SCLC has not considerably changed over the last decades with therapeutic options focusing on unselected populations. Although in the past SCLC was thought to be a relatively homogenous malignancy, recent reports from our group and others identified four major distinct subgroups of SCLC, each with different therapeutic vulnerabilities. Three of the subtypes are defined by the expression of a specific transcription factor, ASCL1 (SCLC-A), NEUROD1 (SCLC-N) and POU2F3 (SCLC-P) while the fourth subtype is defined by an inflamed phenotype (SCLC-I). While our initial subtyping of SCLC is based on a gene expression signature comprised of ~1300 genes, which makes routine implementation challenging, we hypothesized that DNA methylation as a proxy to gene expression might be a more suitable approach for biomarker development in SCLC. We assembled a cohort of 105 SCLC formalin-fixed paraffin embedded (FFPE) samples (82/105 Stage > IIIb) and performed matched RNA-Sequencing (RNAseq) and methylation profiling using reduced-representation bisulfite sequencing (RRBS). To validate our findings and expand our analysis across different sample types, we profiled a panel of 59 fully characterized SCLC cell lines as well as 68 patient-derived xenograft models. We found that methylation levels differ markedly between the four subtypes, with the SCLC-N presenting with a hypermethylated phenotype and the SCLC-P with a hypomethylated phenotype across the genome, highlighting the profound differences in the underlying epigenetic regulation among the SCLC subtypes and supporting DNA methylation analysis as a potential readout for identifying SCLC subtypes. Furthermore, in order to subtype the clinical SCLC samples, we developed a predictive model using an extreme gradient boost model using RNA expression and DNA methylation, respectively, to allow the classification with 94.5% accuracy in the tissue testing cohort. Using a cohort of matched plasma samples, we further demonstrated that the DNA methylation differences were indeed preserved in cell-free DNA (cfDNA) allowing subtype classification with an accuracy of 87.5%. These data indicate that DNA methylation can be used for reliable subtyping of SCLC in tissue and in liquid biopsy samples. In summary, using a large cohort of predominantly extensive stage SCLC clinical samples, we were able to identify profound differences in DNA methylation that can be exploited as a novel biomarker for the classification of SCLC into four distinct subtypes with both tissue biopsy and non-invasive using plasma. Considering the previously shown therapeutic vulnerabilities of the four subtypes, these findings will enable the rapid initiation of personalized clinical trials in SCLC. Citation Format: Simon Heeke, Carl M. Gay, Marcos R. Estecio, Allison Stewart, Hai Tran, Bingnan Zhang, Ximing Tang, Gabriela Raso, Kyle Concannon, Luana Guimaraes De Sousa, Whitney E. Lewis, Monique Nilsson, Yuanxin Xi, Lixia Diao, Qi Wang, Jianjun Zhang, Jing Wang, Ignacio I. Wistuba, Lauren A. Byers, John V. Heymach. Use of DNA methylation from tumor and plasma to identify four major small cell lung cancer subtypes with distinct biology and therapeutic vulnerabilities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3473.

The relationship of smoking to cg05575921 methylation in blood and saliva DNA samples from several studies

Numerous studies have shown that cg05575921 methylation decreases in response to smoking. However, secondary to methodological issues, the magnitude and dose dependency of that response is as of yet unclear. This lack of certainty is a barrier to the use of DNA methylation clinically to assess and monitor smoking status. To better define this relationship, we conducted a joint analysis of methylation sensitive PCR digital (MSdPCR) assessments of cg05575921 methylation in whole blood and/or saliva DNA to smoking using samples from 421 smokers and 423 biochemically confirmed non-smokers from 4 previously published studies. We found that cg05575921 methylation manifested a curvilinear dose dependent decrease in response to increasing cigarette consumption. In whole blood DNA, the Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) of cg05575921 methylation for predicting daily smoking status was 0.98. In saliva DNA, the gross AUC was 0.91 with correction for cellular heterogeneity improving the AUC to 0.94. Methylation status was significantly associated with the Fagerstrom Test for Nicotine Dependence score, but with significant sampling heterogeneity. We conclude that MSdPCR assessments of cg05575921 methylation are a potentially powerful, clinically implementable tool for the assessment and management of smoking.

Outcomes Stratification of Head and Neck Cancer Using Pre- and Post-Treatment DNA Methylation in Peripheral Blood

<h3>Purpose/Objective(s)</h3> Established risk factors for head and neck cancer recurrence include clinical and tumor features assessed prior to treatment. We report the first use of DNA methylation in peripheral blood before and after radiotherapy (RT) to further improve risk stratification. <h3>Materials/Methods</h3> Peripheral blood samples were obtained from patients with non-metastatic squamous cell carcinoma (SCC) of the head and neck for methylation analysis, 1 week before initiation and 1 month after completion of RT. Patients were randomized to a discovery cohort or validation cohort. In the discovery cohort, associations between methylation change at 807,100 genomic sites (post-treatment minus pre-treatment) and progression-free survival (PFS) as well as overall survival (OS) were evaluated using Cox regression, adjusted for clinicopathologic covariates. A risk score (RS) was then constructed from methylation levels at the top associated sites, filtered for residing within regulatory elements of genes that are predominantly expressed in bone marrow, lymphoid tissue, or blood cells. The prognostic value of RS was separately assessed in the discovery cohort and validation cohort. <h3>Results</h3> Between December 2013 and September 2018, 115 patients enrolled in this study (Table) and consist of mostly males (72%) with locally advanced disease (91%). HPV negative status, oral cavity cancer, PEG tube insertion, and higher neutrophil count before RT were associated with shorter PFS and OS (<b>P</b> < 0.05). Genes near the methylation sites comprising RS are SF1, HIF1A, LGALS9,and CRIP2, involved in hematopoietic proliferation, tumor angiogenesis, and antigen presentation. High RS, defined as having a RS in the top third, was significantly associated with worse PFS (HR > 10, <b>P</b> = 0.016) and OS (HR > 10, <b>P</b> = 0.017) in the discovery cohort, independent of the aforementioned risk factors. These findings were further replicated in the validation cohort where high RS also independently conferred poorer PFS (HR > 10, <b>P</b> = 0.002) and OS (HR 6.3, <b>P</b> = 0.015). <h3>Conclusion</h3> We successfully trained and validated a signature of DNA methylation in peripheral blood before and after RT that stratified outcomes among patients with head and neck SCC, implicating the potential for genomics-tailored consolidation treatment and surveillance. Efforts toward methylation analysis at additional post-treatment time points are ongoing.

Bridging the Gaps between Circulating Tumor Cells and DNA Methylation in Prostate Cancer

Prostate cancer is the second most common male malignancy, with a highly variable clinical presentation and outcome. Therefore, diagnosis, prognostication, and management remain a challenge, as available clinical, imaging, and pathological parameters provide limited risk assessment. Thus, many biomarkers are under study to fill this critical gap, some of them based on epigenetic aberrations that might be detected in liquid biopsies. Herein, we provide a critical review of published data on the usefulness of DNA methylation and circulating tumor cells in diagnosis and treatment decisions in cases of prostate cancer, underlining key aspects and discussing the importance of these advances to the improvement of the management of prostate cancer patients. Using minimally invasive blood tests, the detection of highly specific biomarkers might be crucial for making therapeutic decisions, determining response to specific treatments, and allowing early diagnosis.

Diagnostic power of DNA methylation markers suggestive of cholangiocarcinoma in ERCP-based brush cytology

Accurate differentiation between cholangiocarcinoma (CCA) and benign biliary stricture is of paramount importance. Biliary brush cytology is a simple and safe diagnostic approach that provides relatively high specificity; however, sensitivity is limited. Previous reports indicated the aberrations of DNA methylation in CCA. This study aimed to investigate the diagnostic performance of the methylation index (MI) of HOXA1 and NEUROG1 gene promoters in CCA. Patients with biliary stricture who underwent ERCP with brush cytology in Siriraj Hospital from September 2016 to December 2019 were prospectively enrolled. The MI of HOXA1 (MI_H) and MI of NEUROG1 (MI_N) were determined by quantitative methylation-specific polymerase chain reaction. The diagnostic power for CCA was tested for MI from both genes and serum carbohydrate antigen 19-9 (CA19-9). Sixty-seven patients were included in the study; 41 patients had a final diagnosis of CCA, and 26 patients were determined to have a benign biliary stricture. The results showed that both MI_H and MI_N had higher sensitivity and accuracy (95.1% and 82.3% and 90.2% and 89.5%, respectively) than brush cytology (61.5% and 78.1%) and CA19-9 (69.4% and 77.8%). The combination of brush cytology, both methylation markers, and CA19-9 increased the sensitivity and accuracy to 97.4% and 91.0%. Methylation markers were positive in 5 of 6 patients with confirmed CCA whose cytology and CA19-9 were negative. DNA methylation increased the sensitivity for the diagnosis of CCA; therefore, the use of DNA methylation is promising for diagnosis of CCA in patients with biliary strictures. A future validation study is warranted to assess its role in clinical practice. (Clinical trial registration number: NCT04568512.).

Discovering multiple types of DNA methylation from bacteria and microbiome using nanopore sequencing.

Bacterial DNA methylation occurs at diverse sequence contexts and plays important functional roles in cellular defense and gene regulation. Existing methods for detecting DNA modification from nanopore sequencing data do not effectively support de novo study of unknown bacterial methylomes. In this work, we observed that nanopore sequencing signal displays complex heterogeneity across methylation events of the same type. To enable nanopore sequencing for broadly applicable methylation discovery, we generated a training dataset from an assortment of bacterial species and developed a method, named nanodisco (https://github.com/fanglab/nanodisco), that couples the identification and fine mapping of the three forms of methylation into a multi-label classification framework. We applied it to individual bacteria and mouse gut microbiome for reliable methylation discovery. In addition, we demonstrated the use of DNA methylation for binning metagenomic contigs, associating mobile genetic elements with their host genomes, and identifying misassembled metagenomic contigs.

The Implementation of DNA Methylation Profiling into a Multistep Diagnostic Process in Pediatric Neuropathology: A 2-Year Real-World Experience by the French Neuropathology Network.

Simple SummarySupported by the “easy-to-use” and free DKFZ central nervous system (CNS) tumor classification web tool, DNA methylation profiling is a method changing the routine diagnostic practice in neuro-oncology. This work depicts a real-world practice experience by the French neuropathology network of incorporating DNA methylation profiling into the diagnostic process of challenging pediatric CNS tumors. After two rounds of histopathological review by neuropathology experts—including morphology, neuroimaging, immunohistochemistry, panel sequencing and FISH—62 tumors still presenting diagnostic uncertainty were selected for DNA methylation profiling. Using the DKFZ “classifier” and combining all additional information obtained from DNA methylation array, we observed significant diagnostic refinements and amendments. DNA methylation was successful in a significant number of cases (71%) despite the complex specificities of the cohort. Our study evaluates how DNA methylation testing would impact diagnosis and presents illustrative and representative cases.DNA methylation profiling has recently emerged as a powerful tool to help establish diagnosis in neuro-oncology. Here we present our national diagnostic strategy as the French neuropathology network (RENOCLIP-LOC) and our current approach of integrating DNA methylation profiling into our multistep diagnostic process for challenging pediatric CNS tumors. The tumors with diagnostic uncertainty were prospectively selected for DNA methylation after two rounds of review by neuropathology experts. We first integrated the classifier score into the histopathological findings. Subsequent analyses using t-SNE (t-Distributed Stochastic Neighbor Embedding) representation were performed. An additional step consisted of analyzing copy-number variation data (CNV). Finally, we combined all data to establish diagnoses and evaluated the impact of DNA methylation profiling on diagnostic and grading changes that would affect patient management. Over two years, 62 pediatric tumors were profiled. (1) Integrating the classifier score to the histopathological findings impacted the diagnosis in 33 cases (53%). (2) t-SNE analysis provided arguments for diagnosis in 26/35 cases with calibrated scores <0.84 (74.3%). (3) CNV investigations also evidenced alterations used for diagnosis and prognostication. (4) A diagnosis was finally established for 44 tumors (71%). Our results support the use of DNA methylation for challenging pediatric tumors. We demonstrated how additional methylation-based analyses complement the classifier score to support conventional histopathological diagnosis.

Circulating cell-free DNA as potential diagnostic tools for amyotrophic lateral sclerosis

DNA methylation has garnered much attention in recent years for its diagnostic potential in multiple conditions including cancer and neurodegenerative diseases. Conversely, advances regarding the potential diagnostic relevance of DNA methylation status have been sparse in the field of amyotrophic lateral sclerosis (ALS) even though patients diagnosed with this condition would significantly benefit from improved molecular assays aimed at furthering the current diagnostic and therapeutic options available. This review will provide an overview of the current diagnostic approaches available for ALS diagnosis and discuss the potential clinical usefulness of DNA methylation. We will also present examples of DNA methylation as a diagnostic tool in various types of cancer and neurodegenerative conditions and expand on how circulating cfDNA methylation may be leveraged for the early detection of ALS. In general, this article will reinforce the importance of cfDNA methylation as diagnostic tools and will further highlight its clinical relevance for persons diagnosed with ALS.

A DNA methylation age predictor for zebrafish.

Changes in DNA methylation at specific CpG sites have been used to build predictive models to estimate animal age, predominantly in mammals. Little testing for this effect has been conducted in other vertebrate groups, such as bony fish, the largest vertebrate class. The development of most age-predictive models has relied on a genome-wide sequencing method to obtain a DNA methylation level, which makes it costly to deploy as an assay to estimate age in many samples. Here, we have generated a reduced representation bisulfite sequencing data set of caudal fin tissue from a model fish species, zebrafish (Danio rerio), aged from 11.9-60.1 weeks. We identified changes in methylation at specific CpG sites that correlated strongly with increasing age. Using an optimised unique set of 26 CpG sites we developed a multiplex PCR assay that predicts age with an average median absolute error rate of 3.2 weeks in zebrafish between 10.9-78.1 weeks of age. We also demonstrate the use of multiplex PCR as an efficient quantitative approach to measure DNA methylation for the use of age estimation. This study highlights the potential further use of DNA methylation as an age estimation method in non-mammalian vertebrate species.

ANK2 Hypermethylation in Canine Mammary Tumors and Human Breast Cancer.

Canine mammary tumors (CMT) constitute the most common tumor types found in female dogs. Understanding this cancer through extensive research is important not only for clinical veterinary applications, but also in the scope of comparative oncology. The use of DNA methylation as a biomarker has been noted for numerous cancers in the form of both tissue and liquid biopsies, yet the study of methylation in CMT has been limited. By analyzing our canine methyl-binding domain sequencing (MBD-seq) data, we identified intron regions of canine ANK2 and EPAS1 as differentially methylated regions (DMGs) in CMT. Subsequently, we established quantitative methylation specific PCR (qMSP) of ANK2 and EPAS1 to validate the target hypermethylation in CMT tissue, as well as cell free DNA (cfDNA) from CMT plasma. Both ANK2 and EPAS1 were hypermethylated in CMT and highlighted as potential tissue biomarkers in CMT. ANK2 additionally showed significant hypermethylation in the plasma cfDNA of CMT, indicating that it could be a potential liquid biopsy biomarker as well. A similar trend towards hypermethylation was indicated in HBC at a specific CpG of the ANK2 target on the orthologous human region, which validates the comparative approach using aberrant methylation in CMT.

Proposed Additions to the NCCN Guidelines for Adult Medulloblastoma.

Medulloblastoma is a rare brain tumor that occurs in both children and adults, with patients aged 15 to 39 years accounting for 30% of all cases. In adults, guidelines for diagnosis and treatment are often based on retrospective data and extrapolated from the pediatric experience due to limited availability of prospective trials or registries involving adults. Importantly, adult patients differ from pediatric patients in many aspects, including the molecular features of the tumor and tolerance to treatment. In 2017, the NCI was granted support from the Cancer Moonshot initiative to address the challenges and unmet needs of adults with rare central nervous system (CNS) tumors through the NCI Comprehensive Oncology Network for Evaluating Rare CNS Tumors (NCI-CONNECT). On November 25, 2019, NCI-CONNECT convened a multidisciplinary workshop on adult medulloblastoma. Working groups identified unmet needs in clinical care and research and developed specific action items, including a proposal for inclusion of new items in the NCCN Guidelines for Adult Medulloblastoma, delineated in this review along with the evidence supporting their incorporation. Recommendations included facilitating referral of patients to centers of excellence; promoting patient participation in clinical trials or registries; encouraging use of DNA methylation for confirmation of diagnosis and subgrouping; offering counseling on contraception and fertility preservation; evaluating patients for symptoms and medical management of endocrine, vision, hearing, and neurocognitive deficits; providing psychosocial support and referral to neurorehabilitation; minimizing delays in therapy; and incorporating imaging standards and criteria for progression.

Use of DNA methylation to distinguish gallbladder carcinoma.

e15605 Background: Gallbladder cancer (GBC), an uncommon malignancy with a high mortality rate, is often diagnosed late due to lack of early symptoms and the relative hidden nature of the gallbladder. Despite the advancements in imaging technologies, there is no reliable screening test for GBC. The role of aberrant DNA methylation in the process of tumorigenesis both at individual genes and a genome-wide scale has been well elucidated. It occurs very early in cancer development, thus capable of serving as a screening marker. Methods: Panel Design: Methylation data of tumor samples (12 types, n = 4,772), adjacent normal (8 types, n = 411), and normal white blood cells (n = 656) from TCGA and GSE were compared. Differentially methylated sites were derived using a Bayesian hierarchical model-DSS with an adjusted p-value &lt; 0.05. Our panel covers 80,672 CpG sites, spanning 1.05Mb of human genome. This panel contains 12,196 GBC relevant CpG sites. We performed targeted bisulfite sequencing on 23 GBC patients (6 stage II-III, 17 stage IV) and 13 patients with non-malignant gallbladder diseases (cholecystitis and gallstones). Of the 23 GBC patients, we obtained adjacent normal tissue from 7 of them. Basic clinical features such as age, gender, of patients with GBC and patients with non-malignant gallbladder diseases were comparable. Results: Among the 12,196 GBC relevant CpG sites, 10,216 sites were statistically significantly hypermethylated and 275 sites were statistically significantly hypomethylated comparing to patients with non-malignant gallbladder disease as well as adjacent normal gallbladder tissues. Subsequently, we used the derived differentially methylated CpG sites to construct a linear regression model, achieving an area under curve of 99%. Collectively, the methylation levels were comparable between tissues with non-malignant disease and adjacent normal. Interestingly, when considering the 275 hypomethylated markers alone, we observed that the methylation level of adjacent normal tissues is significantly higher than tissues with non-malignant disease. Conclusions: Collectively, our panel can effectively distinguish GBC samples from non-cancerous samples, demonstrating the potential of DNA methylation in GBC screening. Furthermore, hypomethylation markers can be used to distinguish non-malignant disease from the healthy.

Application of a novel molecular method to age free-living wild Bechstein's bats.

The age profile of populations fundamentally affects their conservation status. Yet, age is frequently difficult to assess in wild animals. Here, we assessed the use of DNA methylation of homologous genes to establish the age structure of a rare and elusive wild mammal: the Bechstein's bat (Myotis bechsteinii). We collected 62 wing punches from individuals whose ages were known as a result of a long-term banding study. DNA methylation was measured at seven CpG sites from three genes, which have previously shown age-associated changes in humans and laboratory mice. All CpG sites from the tested genes showed a significant relationship between DNA methylation and age, both individually and in combination (multiple linear regression R2 =0.58, p<0.001). Despite slight approximation around estimates, the approach is sufficiently precise to place animals into practically useful age cohorts. This method is of considerable practical benefit as it can reliably age individual bats. It is also much faster than traditional capture-mark-recapture techniques, with the potential to collect information on the age structure of an entire colony from a single sampling session to better inform conservation actions for Bechstein's bats. By identifying three genes where DNA methylation correlates with age across distantly related species, this study also suggests that the technique can potentially be applied across a wide range of mammals.