Methylation Sites Research Articles

Abstract 974: DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation

Abstract Cell-free DNA (cfDNA) in the bloodstream is increasingly gaining attention as a diagnostic tool for the early detection of cancer. Nevertheless, the characteristics and sources of cfDNA fragmentation in the blood remain poorly understood. In this study, we sought to unravel the impact of DNA methylation and gene expression on the naturally occurring genome-wide fragmentation of cfDNA. We performed a comprehensive analysis of plasma samples from 969 individuals, including 182 individuals diagnosed with cancer (pancreatic, colorectal, ovarian, lung and breast cancer). In healthy individual cfDNA fragmentation patterns like DNA motifs at cfDNA fraqgments ends, recurrent cfDNA fragment start sites, cfDNA coverage and cfDNA fragment size were compared to publicly available data on cfDNA methylation and gene expression from myeloid cells. We discovered that the ends of cfDNA fragments, particularly those containing CGs or CCGs, displayed a distinct pattern of enrichment or depletion, respectively, at methylated CpG positions throughout the genome. This phenomenon is consistent with structural models suggesting an increased interaction of CG fragment ends with nucleosomes. cfDNA fragments were more prevalent (up to 3.7 fold) and of larger sizes (up to 4-5 base larger) when derived from regions of methylated CpGs or transcriptional start sites of genes that were not actively expressed. Differences in cfDNA fragmentation reflected specific biological pathways associated with their tissue of origin (like E2f transcription factors and blood cell metabolism genes in cfDNA from healthy individuals). Through analyses of cfDNA from patients with cancer, we identified a connection between tumor-related hypomethylation, increased gene expression, and a global reduction in cfDNA fragment size. This connection may offer an explanation for the generally smaller cfDNA fragments found in individuals with cancer. We found that cancer-specific methylation at CpG sites from pancreatic cancers were associated with widespread changes in cfDNA fragment ends, particularly for patients with pancreatic (test statistic = Welch two sample t-test; p<2.2e-16) and other cancers. These findings establish a direct link between epigenetic modifications and cfDNA fragmentation that may have implications for non-invasive detection of cancer. Citation Format: Michaël Noë, Akshaya V. Annapragada, Zachariah H. Foda, Jamie E. Medina, Dimitrios Mathios, Stephen Cristiano, Christopher Cherry, Daniel C. Bruhm, Noushin Niknafs, Vilmos Adleff, Leonardo Ferreira, Hari Easwaran, Stephen Baylin, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu. DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 974.

Abstract 2163: Socioeconomic status associates with epigenetic modulation of TET2: An emerging pathway in cardio-oncology

Abstract Introduction: Adverse social determinants of health (SDOH) are known to accelerate poor outcomes in cardiovascular disease (CVD) and cancer. Clonal Hematopoiesis (CH) is a mechanism implicated in these disease states, partially driven by epigenetic regulatory genes, including TET2. Yet, there is not much known about how epigenetic modulations of TET2 itself may relate to the immune system and subsequent disease development. Hypothesis: We hypothesize that socioeconomic status (SES), as a SDOH marker, relates to epigenetic modulation of TET2. Methods: 60 African American adults (93.3% female, mean age 61) with CVD risk, living in the Washington, D.C. area self-reported their SES as household income. Immune system activity was assessed via splenic activity (SpleenA) by 18FDG PET/CT. Serum cytokine levels were measured by ELISA and DNA methylation analysis evaluated the epigenetic modulations of TET2. Multivariable regression analysis adjusted for ASCVD 10-year risk score and BMI was used to examine associations. Results: Out of 33 TET2 methylation sites, we found 3 sites that were significantly related to SES. Notably, only Tet2cg09666717 (SES β=0.310, p=0.038) was also associated with SpleenA (β=-0.453, p=0.036) and several cytokines: IL-17A, IL-1β and TNFα along with trending to significance with IFN-γ (Table). Conclusion: Thus, we found that SES associates with hypomethylation of Tet2cg09666717, which further related to SpleenA and inflammatory markers. Our findings are hypothesis generating and suggest that lower SES may relate to inflammation and immune system dysregulation by the way of epigenetic modulation of TET2. These results should be examined in larger, functional studies with diverse population-based cohorts to determine the potential relationships of both SDOH and epigenetic markers in CH and cardio-oncology outcomes. Associations between TET2 methylation sites, SpleenA, SES and Cytokines in DCCNHA cohort, 2014-17 Tet2cg09666717 Tet2cg05094833 Tet2cg10594473 SES 0.310 (0.038) -0.405 (0.006) -0.283 (0.060) Splenic Activity -0.453 (0.036) 0.004 (0.985) 0.097 (0.654) IL-6 -0.078 (0.558) -0.211 (0.108) -0.222 (0.084) IL-8 -0.199 (0.153) 0.024 (0.865) -0.004 (0.979) IL-17A -0.373 (0.010) 0.134 (0.370) -0.434 (0.017) IL-1β -0.382 (0.003) 0.042 (0.757) -0.143 (0.275) TNFα -0.456 (0.000) -0.157 (0.244) 0.005 (0.969) IFN-γ -0.258 (0.062) -0.037 (0.790) 0.022 (0.876) Data are presented as standardized β coefficient (p-value). All data are adjusted for 10-year predicted ASCVD risk and BMI; ASCVD = atherosclerotic cardiovascular disease; BMI = body mass index; IL-6 = interleukin 6; IL-8 = interleukin 8; IL-17A = interleukin 17A; IL-1β = interleukin 1 beta; TNFα = tumor necrosis factor; IFN-γ = interferon gamma Citation Format: Sonal Sharda, Yvonne Baumer, Alina P. Pang, Abhinav Saurabh, Billy S. Collins, Valerie M. Mitchell, Michael J. Corley, Tiffany M. Powell-Wiley. Socioeconomic status associates with epigenetic modulation of TET2: An emerging pathway in cardio-oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2163.

Abstract 7024: Development of quality control methods for reliable NGS measurement of methylation in cfDNA

Abstract Background and Purpose: Reliable measurement of circulating free genomic DNA (cfDNA) methylation patterns promises a means for cancer early detection as well as treatment response. Use of Next Generation Sequencing (NGS) methods to measure the cfDNA methylome across a large number of potentially methylated CpG sites may enable earlier detection by overcoming stochastic sampling associated with the small specimens obtainable by a blood draw. Wide-spread adoption of these methods for clinical diagnostic applications will be facilitated through improved quality controls that increase reliability. The goal of this study is to assess the performance of the SNAQ-SEQ™ method as a means to establish a limit of detection (LOD) for measurement of methylation at each targeted CpG site. For this purpose, we used test materials that were developed by the National Institute for Standards and Technology (NIST) to mimic methylated cfDNA. Methods: NIST test materials were formulated by physically shearing cell line gDNA then subjecting it to size separation to mimic a size distribution similar to that observed in cfDNA, then mixing sheared DNA in its “native” state of methylation with sheared DNA that was in vitro methylated. Non-sheared NIST test materials also were assessed in these studies. Synthetic spike-in internal standards (IS) were combined with NIST test materials and the combined samples were bisulfite converted, then subjected to PCR-amplicon library preparation. Libraries were sequenced on an Illumina MiSeq instrument and bioinformatic analysis was conducted using the Qiagen CLC Workbench. Results and Conclusions: In initial testing of an off-the-shelf IS for a region of the SOX2 gene, average methylation (preserved C) across 14 targeted CpG sites was 16.4% (0.5%-50%) in the “native” NIST non-sheared sample. This was consistent with the 11.6% methylation across all of SOX2 measured by the NIST. In contrast, in IS corresponding to the targeted SOX2 region the average preserved C was 0.32% (0.03%-0.5%). Use of synthetic internal standards enabled determination of LOD for each individual methylated site, controlling for all known sources of technical error, including inefficient bisulfite conversion, nucleotide substitution error, and alignment error. Studies are now underway that use the NIST test materials to measure methylation at five targets known to be altered in cfDNA from lung cancer subjects, SOX2, CDO1, TAC1, SOX17, and HOXA7. Citation Format: James C. Willey, Erin L. Crawford, Daniel J. Craig, Thomas M. Morrison, Hua-Jun He, James G. Herman. Development of quality control methods for reliable NGS measurement of methylation in cfDNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7024.

Abstract 1023: Whole-genome methylation analysis using liquid biopsy for pancreatic cancer diagnosis

Abstract Objective: Pancreatic cancer is one of the highly malignant tumors. Its diagnosis requires invasive ultrasound endoscopic biopsy or endoscopic retrograde cholangiopancreatography (ERCP). However, these methods are limited by false-positive results and complications. Liquid biopsy, which uses blood to detect KRAS mutations in cancer, can be used to overcome these hurdles. However, only about 30% of cases can be detected as a diagnostic marker by KRAS mutations using plasma from patients with stage I-II pancreatic cancer, and its clinical application remains a challenge. Therefore, in this study, we focused on diagnosing pancreatic cancer using methylated DNA in plasma cell-free DNA (cfDNA) obtained from pancreatic cancer and non-cancer patients. Subjects: Plasma was collected before the start of the treatment from six patients diagnosed with pancreatic cancer from 2019 to 2023 at our hospital, and six non-cancer patients simultaneously. Methods: Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing (NGS) was performed using the cfDNA obtained from the plasma of pancreatic cancer and non-cancer patients. Results: The cfDNA fragments obtained by WGBS revealed that promoter regions were mostly deleted, and no difference was observed between cancer and non-cancer patients. The methylation rate of cfDNA fragments by WGBS differed between cancer and non-cancer patients, with multiple methylation sites (>100 sites) in intergenic regions. Discussion: Although attempts have been made to diagnose cancer using genetic mutations and liquid biopsy, only a few studies are available on using methylation markers in the plasma cfDNA of pancreatic cancer patients, and the effectiveness of this method remains unclear. In the present study, we found that promoter regions were deleted by WGBS, and several distinct hypermethylated regions were present in the intergenic region between pancreatic cancer and non-cancer samples, suggesting the presence of certain markers that can distinguish between pancreatic cancer and non-cancer patients. Conclusion: This small number of cases suggests that hypermethylation of the intergenic regions could be helpful in the diagnosis of pancreatic cancer. We will need more cases in the future to verify the usefulness of hypermethylation of intergenic regions in the diagnosis of pancreatic cancer. Citation Format: Tomoaki Ito, Takuya Iwasawa, Satoshi Takeda, Chikako Okamoto, Tomoko Motohashi, Shuhei Ueda, Hisaki Kato, Riku Yamamoto, Akihiro Koizumi, Yuta Murai, Kosaku Nihei, Moe Itakura, Ryunosuke Akima, Mutsumi Sakurada, Kenichiro Tanaka, Tomoyuki Kushida, Koichi Sato. Whole-genome methylation analysis using liquid biopsy for pancreatic cancer diagnosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1023.

Abstract 1615: Balanced molecular feature selection unveils universally tumor-lineage informative methylation sites in colorectal cancer

Abstract In the era of precision medicine, performing comparative analysis over diverse patient populations is a fundamental step toward tailoring healthcare interventions. However, the critical aspect of equitably selecting molecular features across multiple patients is often overlooked. To address this challenge, we introduce FALAFL (FAir muLti-sAmple Feature seLection), a novel algorithmic approach based on integer linear programming. FALAFL is designed to bridge the gap between molecular feature selection and algorithmic fairness, ensuring a balanced selection of molecular features across different patient samples. We have applied FALAFL to the problem of selecting lineage-informative CpG sites within a cohort of 9 colorectal cancer patients subjected to low-coverage single-cell methylation sequencing. Our results demonstrate that FALAFL excels at rapidly determining the optimal set of CpG sites, which are well covered by cells across the vast majority of the patients, while ensuring that each patient contributes a similar number of sites to the final selection. An analysis of the FALAFL-selected CpG sites reveals that their lineage informativeness exhibits a strong association across diverse patient profiles, suggesting the non-stochasticity and universality of methylation changes in tumor evolution. Furthermore, these universally lineage-informative sites exhibit subclonal level alterations in the colorectal cancer primary tumors and are strongly associated with lineage-specific gene expression patterns. By integrating equity considerations into the molecular feature selection process, FALAFL is poised to propel equitable healthcare data science practices and advance our understanding of cancer and other complex diseases. Citation Format: Xuan Cindy Li, Yuelin Liu, Alejandro A. Schäffer, Stephen M. Mount, Süleyman C. Sahinalp. Balanced molecular feature selection unveils universally tumor-lineage informative methylation sites in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1615.

Abstract 2490: Quantification of tumor fraction and outcomes association in a real-world non-small cell lung cancer (NSCLC) cohort using a tissue agnostic epigenomic circulating tumor DNA (ctDNA) assay

Abstract Background: The validity of ctDNA assays for evaluating molecular response to therapy by measuring changes in variant allele fraction (VAF) while on treatment is well established, but they are prone to limitations such as low ctDNA levels and interference from copy number variation and clonal hematopoeisis (CH), which may be overcome by methylation-based quantification. ctDNA levels may be monitored throughout a patient's (pts) journey to indicate when relapse or progression is present, often sooner than current methods (RECIST). Here we describe the performance of a methylation-based ctDNA assay to quantify ctDNA levels and correlate changes with outcomes in a real-world NSCLC cohort. Methods: RADIOHEAD is a pan-tumor observational study of 1200 patients on standard of care ICI treatment regimens with plasma samples collected prospectively for retrospective analysis. We randomly selected 241 NSCLC pts that have a combined total of 761 samples (236 baseline, 191 C3D1, and 128 at 6 months post first dose). Samples were analyzed using a commercial NGS assay, which quantifies circulating tumor fraction (cTF) via interrogating thousands of methylation sites from ctDNA, validated with LoB, LoD, LoQ, and linearity studies. Cox proportional hazards (CPH) were used for comparison of real-world progression free survival (rwPFS). Gender, age, disease stage, and blood-assessed tumor mutational burden (bTMB) were included as covariates. Median rwPFS was calculated using Kaplan Meier analysis. rwPFS ordinal groups were defined as PFS event within 3mo, 3-6mo, 6-12mo, and greater than 12mo, and association with early ctDNA changes was assessed with a chi-squared test. Results: In this cohort, 4, 11, 83 and 142 pts were stage I to IV, respectively (1 unknown). Methylation based detection of ctDNA at baseline or C3D1 was associated with shorter rwPFS (baseline: mPFS 12.7 mo [9.3-19.5] vs NR [16.4-NR]; HR=2.2 [1.3-3.7] p<0.005, C3D1: mPFS 12.4 mo [9.3-16.1] vs NR [19.5-NR] HR= 2.2 [1.3-3.5], p<0.005) independent of stage, gender, or age. Longer rwPFS was associated with >95% reduction in cTF from baseline to C3D1 or low ctDNA at both timepoints (rwPFS <3mo = 12.5%, 3-6 mo = 30.8%, 6-12 = 37.1%, ≥12 mo = 55.3%; N=153, p=0.015). For pts with ctDNA not detected at C3D1, ctDNA detection at 6 months post first dose was strongly associated with shorter rwPFS (mPFS 13.5 mo [9.5-NR] vs. NR [19.5-NR]; HR= 6.2 [1.9-20.1], p<0.005). Conclusions: These data demonstrate a significant association of ctDNA detection via methylation-based cTF and on-treatment changes in cTF with rwPFS. Furthermore, subsequent cTF detection 6-months on-treatment, without cTF detected early on-treatment was associated with worse outcomes, suggesting the value of serial monitoring to improve identification of patients likely to progress. Citation Format: Sara Wienke, Sean Gordon, Samantha Liang, Jing Wang, Reagan Barnett, Kyle Chang, Shile Zhang, Carin R. Espenschied, Katie Quinn, Kimberly Banks. Quantification of tumor fraction and outcomes association in a real-world non-small cell lung cancer (NSCLC) cohort using a tissue agnostic epigenomic circulating tumor DNA (ctDNA) assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2490.

Abstract 7001: Profiling the CpG methylation patterns of Epstein-Barr virus DNA in lymphoma patients from Ethiopia

Abstract Introduction: Epstein-Barr virus (EBV) is a tumor virus associated with various malignancies, driven by genetic mutations and epigenetic alterations, including DNA methylation. Abnormal CpG methylation holds promise as a diagnostic and therapeutic biomarker for EBV-associated tumors. However, the understanding of EBV's epigenetic mechanisms remain limited. Determining the methylation profile of EBV is crucial for gaining insights into the pathogenesis of EBV-associated tumors, developing diagnostic biomarkers, and exploring potential therapeutic strategies. Therefore, our study aimed to assess the CpG methylation profile of EBV DNA in lymphoma patients from Ethiopia. Methods: This study enrolled 115 lymphoma patients from Tikur Anbessa Specialized Hospital in Addis Ababa, Ethiopia. Plasma and formalin-fixed paraffin-embedded blocks were collected from the participants, and isolation of DNA was performed from these samples. The methylation analysis was performed using the methylation-iPLEX assay. iPLEX capture and extension primers were designed to amplify and target EBV CpGs from bisulfite-converted DNA sequences. Ethical approval was also obtained from respected institutions. Results: Among the 115 participants, 65.2% (n = 75) were male patients. The largest proportion (n = 35, 30.4%) fell within the 41-60 age group. Non-Hodgkin lymphoma (NHL) was diagnosed in 96 patients, while 19 had Hodgkin lymphoma (HL). In the NHL group, the majority (n = 27, 28.1%) were classified as diffuse large cell lymphoma, followed by follicular lymphoma (n = 24, 25%). Out of the different EBV genome methylation sites, we have identified 24 EBV genes to assess the methylation status of the EBV genome. Average methylation levels of these genes were ranged from 45% to 50%. Notably, the HL group exhibited significant heterogeneity in methylation levels, while the CpG methylation status of EBV genes in NHL subtypes demonstrated a consistent pattern. A significant proportion of our samples exhibited methylation loss in the lytic gene BZLF1 and at the origin of replication associated with lytic replication. Conclusions: This study presents the first data from East Africa, shedding light on the EBV DNA methylation status in a diverse group of lymphoma patients. Further investigations in different locations are necessary to elucidate the impact of EBV DNA methylation on tumor progression. Citation Format: Seifegebriel T. Feleke, Kidist Z. Shita, Abdulaziz A. Sherif, Fisihatsion T. Woldegebriel, Christoph Weigel, Elshafa H. Ahmed, Tamrat A. Zeleke, Robert A. Baiocchi. Profiling the CpG methylation patterns of Epstein-Barr virus DNA in lymphoma patients from Ethiopia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7001.

Abstract 338: Unraveling layers of proteogenomic complexity in cancer through multiomic exploration of archived FFPE tissue

Abstract Formalin Fixed Paraffin Embedded (FFPE) tissues are a staple in clinical diagnostics associated with solid tumor. The preserved tumor tissue can be interrogated using classical histopathology and complemented with molecular approaches to elucidate cancerous SNPs, indels, structural variants, repeat expansion, copy number expansions, and mutational burden. Increasingly, approaches are being deployed to interrogate tissue not only through individual datasets but through integrated approaches that provide spatial information that defines the tumor microenvironment. Here, we illustrate using FFPE blocks from various tissues a multiomic workflow that allows for deep exploration of the molecular underpinnings of cancerous tissue. FFPE blocks were serially sliced into various FFPE slides with a single slide H&E stained. Individual slides were then utilized to explore the genome, epigenome, single cell RNA-seq, and digital spatial profiling. Genome information was captured using hybrid capture based approaches (whole exome sequencing and targeted cancer panel) followed by deep NGS on an Illumina platform and analyzed for a variety of variants and tumor mutational burden. DNA methylation was detailed using target capture probes targeting DNA methylation sites. Single cell approaches were applied to explore the transcriptome using 10X Genomics scRNAseq Flex kit. Digital spatial profiling was done using the NanoString for both transcriptomics and proteomics, with the GeoMx Whole Transcriptome Atlas and Human Core and Pan-Tumor protein panels. Aggregating these data illustrates the expanding landscape of information that can be extracted from FFPE derived tissue and the potential for novel discovery and diagnostic power integrating these complex data types holds. Citation Format: Andrea J. O'Hara, Yang Han, Ilaria DeVito, Laure Turner, Haythem Latif. Unraveling layers of proteogenomic complexity in cancer through multiomic exploration of archived FFPE tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 338.

Abstract 1740: Histone proteomic profiling of EMT-transformed MCF10A breast cells demonstrates a loss in novel histone arginine methylation sites via dual p53 and PTEN deletion

Abstract Metastatic potential of basal-like breast cancers typically is initiated by genetic alterations that lead to a process known as epithelial-mesenchymal transition (EMT). However, much is currently not understood regarding the role of epigenetic modifications that lead to invasive characteristics and EMT phenotype of metastatic breast cancers. Based on the previous notion connecting epigenetic changes to breast cancer metastasis, we performed DIA-based mass spectrometry of isolated histones from an isogenic panel of MCF10A breast cell lines where the tumor suppressor genes TP53 and PTEN were silenced and induced EMT. With this approach, we determined which histone modifications were differentially enriched in the non-EMT and EMT-induced MCF10A cell lines. From approximately 72 histone modifications identified and annotated from our mass spectrometry results, we were able to identify 5 histone events that were differentially enriched in our MCF10A cell line panel. Two events of note were histone H3 lysine-14 acetylation (H3K14ac) significantly increasing and histone H4 arginine 55 dimethylation (H4R55me2) significantly decreasing in our EMT-transformed MCF10A p53-/PTEN- cell lines when compared to the parental, non-tumorigenic MCF10A cell line, showing these events are differentially affected during the EMT process in breast cancer cells. Furthermore, significant arginine demethylation of H4R55me2 & H3.1R83me in the EMT-transformed MCF10A p53-/PTEN- cell lines corresponded with JMJD6, an established histone arginine demethylase, being overexpressed in basal-like breast cancer cell lines as well as basal-like breast cancer patients from The Cancer Genome Atlas (TCGA) and METABRIC datasets. Based on histone proteomic profiling of our isogenic cell line model, the loss of specific histone arginine methylation events corresponding with JMJD6 overexpression could highlight the potential for a targetable epigenetic mechanism in breast cancer metastasis. Citation Format: Charlotte B. McGuinness, Megan A. Wilson, Margaret V. Leonard, Maria Ouzounova, Hasan Korkaya, Austin Y. Shull. Histone proteomic profiling of EMT-transformed MCF10A breast cells demonstrates a loss in novel histone arginine methylation sites via dual p53 and PTEN deletion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1740.

Bacmethy: A novel and convenient tool for investigating bacterial DNA methylation pattern and their transcriptional regulation effects

AbstractDNA methylation serves as the primary mode of epigenetic regulation in prokaryotes, particularly through transcriptional regulation. With the rapid implementation of third‐generation sequencing technology, we are currently experiencing a golden age of bacterial epigenomics. However, there has been a lack of comprehensive research exploring the versatility and consequential impact of bacterial DNA methylome on cellular and physiological functions. There is a critical need for a user‐friendly bioinformatics tool that can effectively characterize DNA methylation modification features and predict the regulation patterns. To address this gap, the current study introduces Bacmethy, an innovative tool that utilizes SMRT‐seq data and offers a range of analytical modules. First, the tool classifies methylation sites in the genome, highlighting the distinct regulations present under varying modification fractions and location enrichment. Furthermore, this tool enables us to identify regulatory region methylation and potential cis and trans interactions between methylation sites and regulatory effectors. Using benchmark data sets and our data, we show that our tool facilitates the understanding of the distinctive traits of DNA methylation modifications and predicts transcriptional regulation effects on important physiological and pathological functions. Bacmethy code is freely available, and the Docker image is downloadable. Bacmethy has been made available as a user‐friendly web server interface at https://bacmethy.med.sustech.edu.cn.

Abstract P382: Epigenetic Regulation of the NF-kB Pathway by the Neural-Hematopoietic-Inflammatory Axis as a Potential Link Between Psychosocial Stress and Cardiovascular Risk: Data From the Washington DC Cardiovascular Health and Needs Assessment

Introduction: Chronic psychosocial stress (cPSS) is associated with cardiovascular disease (CVD) risk, caused in part by dysregulation of the neural-hematopoietic-inflammatory axis and epigenetic changes. cPSS may also affect NF-kB dependent pathways, suggesting a potential link to accelerated CVD risk and health inequities for populations most impacted by adverse social determinants. Hypothesis: We propose cPSS associates with greater amygdala activity (AmygA), a stress marker, and splenic activity (SpleenA), a hematopoietic activation measure. This relates to higher pro-inflammatory cytokine levels, partially due to less DNA methylation of NF-kB pathway-related genes. Methods: 60 African American adults (93.3% female, mean age 61) with CVD risk, living in the Washington, D.C. area underwent 18 FDG PET/CT to evaluate AmygA and SpleenA. DNA methylation analysis assessed epigenetic associations of the NF- κ B1/2 gene in PBMCs and ELISA- measured serum IL-1β and TNFα. Multivariable regression analysis adjusted for atherosclerotic CVD 10-year risk score and BMI was used to examine associations. Results: Greater AmygA and SpleenA were significantly associated with one another (β=0.26; p=0.003) and both were associated with greater pro-inflammatory cytokines IL1-β (AmygA:β =0.36, SpleenA:β=0.72, p<0.05) and TNF-α (AmygA:β=0.31, SpleenA:β=0.58, p<0.05). Further, we identified 2 significant methylation sites out of 81 on the NF- κ B1/2 gene. Notably, AmygA and SpleenA were inversely associated with the NF-κB1 cg01983105 and cg07955720 methylation sites (Table). Conclusions: We highlight a possible link between AmygA and SpleenA with decreased DNA methylation of the NF- κB gene. Our findings demonstrate a potential relationship between chronic stress-related neural activity and CVD risk through immune function and epigenetic alterations. These results should be examined in larger, diverse population-based cohorts with longitudinal data to identify intervention targets for reducing health inequities.

Abstract P524: Prolonged Mild Sleep Restriction Results in Specific Alterations in Genome-Wide DNA Methylation: A Randomized Crossover Trial

Introduction: Short sleep duration is associated with increased cardiometabolic risk. DNA methylation plays a critical role in the regulation of gene expression and studies suggest that sleep deprivation may alter DNA-methylation patterns. However, most findings are from acute sleep deprivation or short duration studies. Hypothesis: Prolonged sleep restriction study that mimics real-life situations is associated with differentially methylated CpG loci (DML) in the core clock candidate genes and across the epigenome in an epigenome-wide association study (EWAS) Methods: Sixty participants (65% women) aged 21-73 y were included in randomized crossover studies with 2 phases of 6 weeks each. Phases differed in sleep duration: either adequate sleep (AS; sleep ≥7h/night) or sleep restriction (SR; -1.5h/night relative to AS). DNA was isolated from whole blood at wk 0 and wk 6 of each phase. DNA methylation (DNAm) was quantified the Illumina Infinium MethylationEPIC BeadChip array v.2.0 (>900K methylation sites) and Partek Genomic Suite v.720.0831. After quality control and normalization, several global and stratified EWASs were performed to test the impact of sleep condition on DNAm. Analyses were adjusted for week, phase, sex, age, BMI and cell type composition. We also focused on methylation changes of the selected core-clock candidate genes ( RORA, CRY1, NR1D2, TIMELESS, NPAS2, NFIL3, RORB, PER3, CSNK1E, ARNTL2, CRY2, CLOCK, ARNTL, RORC, PER2, BHLHE40, NR1D1, CSNK1D, BHLHE41 and PER1 ). Results: In the candidate gene approach, we detected several significant DML. Top-ranked DML in selected core clock genes with significant interactions between condition and time were: cg02394126 at ARNTL (p<0.001), cg23506964 at CLOCK (p=0.001), cg03701037 at NPAS2 (p=0.009), cg06606972 at NPAS2 (p=0.009), and cg13576304 at RORA (p=0.008). Hypermethylation was primarily observed after 6 wk of SR vs AS for cg02394126, cg23506964, cg03701037, and cg06606972, while hypomethylation was observed cg13576304 ( RORA ). In our EWAS, we detected some suggestive significant condition x time interactions in cg23738833 at SNHG3-RCC1 (p=1,34E-06), cg13280380 in the FAF1 gene (p=2,25E-05), cg03179866 in the MMP12 gene (p=2,78E-05), and cg13063696 (p=3,21E-05). All but cg23738833 ( SNHG3-RCC1 ) showed hypermethylation after 6 wk of SR vs AS. Conclusion: Six weeks of mild SR was associated with changes in DNAm in core-clock candidate genes and in other genes in the EWAS. However, further studies are needed to confirm these findings and determine the functional pathways.

Identification of clinical characteristics biomarkers for rheumatoid arthritis through targeted DNA methylation sequencing

ObjectivesRheumatoid arthritis (RA) is a complex disease with a challenging diagnosis, especially in seronegative patients. The aim of this study is to investigate whether the methylation sites associated with the overall immune response in RA can assist in clinical diagnosis, using targeted methylation sequencing technology on peripheral venous blood samples. MethodsThe study enrolled 241 RA patients, 30 osteoarthritis patients (OA), and 30 healthy volunteers control (HC). Fifty significant cytosine guanine (CG) sites between undifferentiated arthritis and RA were selected and analyzed using targeted DNA methylation sequencing. Logistic regression models were used to establish diagnostic models for different clinical features of RA, and six machine learning methods (logit model, random forest, support vector machine, adaboost, naive bayes, and learning vector quantization) were used to construct clinical diagnostic models for different subtypes of RA. Least absolute shrinkage and selection operator regression and detrended correspondence analysis were utilized to screen for important CGs. Spearman correlation was used to calculate the correlation coefficient. ResultsThe study identified 16 important CG sites, including tumor necrosis factort receptor associated factor 5 (TRAF5) (chr1:211500151), mothers against decapentaplegic homolog 3 (SMAD3) (chr15:67357339), tumor endothelial marker 1 (CD248) (chr11:66083766), lysosomal trafficking regulator (LYST) (chr1:235998714), PR domain zinc finger protein 16 (PRDM16) (chr1:3307069), A-kinase anchoring protein 10 (AKAP10) (chr17:19850460), G protein subunit gamma 7 (GNG7) (chr19:2546620), yes1 associated transcriptional regulator (YAP1) (chr11:101980632), PRDM16 (chr1:3163969), histone deacetylase complex subunit sin3a (SIN3A) (chr15:75747445), prenylated rab acceptor protein 2 (ARL6IP5) (chr3:69134502), mitogen-activated protein kinase kinase kinase 4 (MAP3K4) (chr6:161412392), wnt family member 7A (WNT7A) (chr3:13895991), inhibin subunit beta B (INHBB) (chr2:121107018), deoxyribonucleic acid replication helicase/nuclease 2 (DNA2) (chr10:70231628) and chromosome 14 open reading frame 180 (C14orf180) (chr14:105055171). Seven CG sites showed abnormal changes between the three groups (P < 0.05), and 16 CG sites were significantly correlated with common clinical indicators (P < 0.05). Diagnostic models constructed using different CG sites had an area under the receiver operating characteristic curve (AUC) range of 0.64–0.78 for high-level clinical indicators of high clinical value, with specificity ranging from 0.42 to 0.77 and sensitivity ranging from 0.57 to 0.88. The AUC range for low-level clinical indicators of high clinical value was 0.63–0.72, with specificity ranging from 0.48 to 0.74 and sensitivity ranging from 0.72 to 0.88. Diagnostic models constructed using different CG sites showed good overall diagnostic accuracy for the four subtypes of RA, with an accuracy range of 0.61–0.96, a balanced accuracy range of 0.46–0.94, and an AUC range of 0.46–0.94. ConclusionsThis study identified potential clinical diagnostic biomarkers for RA and provided novel insights into the diagnosis and subtyping of RA. The use of targeted deoxyribonucleic acid (DNA) methylation sequencing and machine learning methods for establishing diagnostic models for different clinical features and subtypes of RA is innovative and can improve the accuracy and efficiency of RA diagnosis.

TCERG1L hypermethylation is a risk factor of diabetic retinopathy in Chinese children with type 1 diabetes.

To identify the differential methylation sites (DMS) and their according genes associated with diabetic retinopathy (DR) development in type 1 diabetes (T1DM) children. This study consists of two surveys. A total of 40 T1DM children was included in the first survey. Because no participant has DR, retina thinning was used as a surrogate indicator for DR. The lowest 25% participants with the thinnest macular retinal thickness were included into the case group, and the others were controls. The DNA methylation status was assessed by the Illumina methylation 850K array BeadChip assay, and compared between the case and control groups. Four DMS with a potential role in diabetes were identified. The second survey included 27 T1DM children, among which four had DR. The methylation patterns of the four DMS identified by 850K were compared between participants with and without DR by pyrosequencing. In the first survey, the 850K array revealed 751 sites significantly and differentially methylated in the case group comparing with the controls (|Δβ|>0.1 and Adj.P<0.05), and 328 of these were identified with a significance of Adj.P<0.01. Among these, 319 CpG sites were hypermethylated and 432 were hypomethylated in the case group relative to the controls. Pyrosequencing revealed that the transcription elongation regulator 1 like (TCERG1L, cg07684215) gene was hypermethylated in the four T1DM children with DR (P=0.018), which was consistent with the result from the first survey. The methylation status of the other three DMS (cg26389052, cg25192647, and cg05413694) showed no difference (all P>0.05) between participants with and without DR. The hypermethylation of the TCERG1L gene is a risk factor for DR development in Chinese children with T1DM.

Multi-omics profiling reveals an extensive regulation network shift in the domestication process of the traditional Chinese medicinal herb Rehmannia glutinosa Liboschitz (Orobanchaceae)

Plant domestication plays a vital role in human evolution and society development. Contrasted to the major crops, the domesticated procedure of medicinal herbs remains largely unknown. Here we analyzed the epigenomic, transcriptomic, and metabolomic profiling of three wild and nine cultivated samples of Dihuang (Rehmannia glutinosa Liboschitz), a well-known traditional Chinese medicinal herb, to elucidate the genetic differentiation and regulation mechanism during domestication. The results unraveled that tremendous differentiation existed among wild and cultivated types from genomes to metabolites. The cultivars presented significantly more methylated sites than the wild type and conjoint analyses indicated that hypermethylation of key genes was generally related to their down-regulated expressions and up-regulated metabolites in the pathways of monoterpenoid biosynthesis and carbohydrate metabolism involved in main components production and tuberous root enlargement. We also identified the key gene related to plant circadian rhythms and potential adaptation in the domestication of Dihuang. This work unveiled the systematic transformation from wild to cultivated Dihuang and provides new insights into the regulatory networks of genetic architectures, benefiting germplasm collection, cultivation, and utilization in the future.

Revealing distinct DNA methylation patterns in hepatic carcinoma through high-throughput sequencing

Abstract Objectives To study the relationship between DNA methylation and tumour development and provide experimental evidence for the personalized diagnosis and treatment of hepatic carcinoma. Methods The DNA of hepatic carcinoma tissue (Ca group) and adjacent normal tissue (T group) were extracted using the phenol-chloroform method and then treated with bisulfite. Twenty-five genes including 45 subtypes were amplified by PCR. The PCR products were sequenced via the Illumina 450k methylation array assay. The changes of methylated DNA performance were analysed through principal component analysis (PCA). Cluster analysis was used to evaluate the classification of methylated DNA regions. Haplotype abundance variation was tested for methylation differences. Statistical analysis was performed using the chi-square (χ2) test or Fisher’s exact test. Results Sequencing discoveries indicated CG-type methylation pervading all amplicons. However, CHG-type and CHH-type methylations were confined to only four amplicons (or nine subtypes). The methylation ratios of three specific amplicons (DAB2IP, PRDM14-1, Rab31-1) out of 45 amplicon subtypes in the Ca group significantly increased (over 10 %) compared to the T group (p&lt;0.05). Nineteen amplicons demonstrated minor distinction (methylation pattern variations between 1 and 10 %), with the remaining 23 amplicons showing only minimal disparities (under 1 %). PCA and cluster analysis unveiled a marked difference in methylation levels between cancerous and healthy tissues (p&lt;0.05). Conclusions The changes in haplotypes and methylation sites could serve as a biomarker for the clinical diagnosis of hepatic carcinoma. Methylation patterns might play an important role in the occurrence and development of hepatic carcinoma.

PCGIMA: developing the web server for human position-defined CpG islands methylation analysis.

Introduction: CpG island (CGI) methylation is one of the key epigenomic mechanisms for gene expression regulation and chromosomal integrity. However, classical CGI prediction methods are neither easy to locate those short and position-sensitive CGIs (CpG islets), nor investigate genetic and expression pattern for CGIs under different CpG position- and interval- sensitive parameters in a genome-wide perspective. Therefore, it is urgent for us to develop such a bioinformatic algorithm that not only can locate CpG islets, but also provide CGI methylation site annotation and functional analysis to investigate the regulatory mechanisms for CGI methylation. Methods: This study develops Human position-defined CGI prediction method to locate CpG islets using high performance computing, and then builds up a novel human genome annotation and analysis method to investigate the connections among CGI, gene expression and methylation. Finally, we integrate these functions into PCGIMA to provide relevant online computing and visualization service. Results: The main results include: (1) Human position-defined CGI prediction method is more efficient to predict position-defined CGIs with multiple consecutive (d) values and locate more potential short CGIs than previous CGI prediction methods. (2) Our annotation and analysis method not only can investigate the connections between position-defined CGI methylation and gene expression specificity from a genome-wide perspective, but also can analysis the potential association of position-defined CGIs with gene functions. (3) PCGIMA (http://www.combio-lezhang.online/pcgima/home.html) provides an easy-to-use analysis and visualization platform for human CGI prediction and methylation. Discussion: This study not only develops Human position-defined CGI prediction method to locate short and position-sensitive CGIs (CpG islets) using high performance computing to construct MR-CpGCluster algorithm, but also a novel human genome annotation and analysis method to investigate the connections among CGI, gene expression and methylation. Finally, we integrate them into PCGIMA for online computing and visualization.

Irreversible methadone-induced GSTP1 downregulation in SH-SY5Y cells

BackgroundMethadone has been reported to downregulate the expression of glutathione S-transferase P1 (GSTP1) among nine antioxidant genes in SH-SY5Y cells after both short- and long-term treatment. GSTP1 plays a key role in the detoxification of many xenobiotics and is frequently associated with various diseases, especially tumors. The objective of this study is to determine whether this change is reversible.MethodsTwo different treatment protocols were used. The first protocol evaluated the reversibility of the GSTP1 mRNA change, while the second protocol evaluated the methylation status of the GSTP1 promoter site. To investigate the reversibility of the GSTP1 mRNA change, SH-SY5Y cells were treated with methadone. The drug was then removed from the medium and the cells were cultured in methadone-free medium for a period of time. GSTP1 mRNA levels were expressed as cycle threshold (Ct) values using TATA box-binding protein as a calibrator gene. Methylation at the promoter site was detected by bisulfite treatment.ResultsThe analysis of variance revealed no significant change in GSTP1 mRNA levels in the cells after methadone was removed from the medium of methadone-treated cells. The study also examined the methylation status of a CpG island in the promoter of GSTP1 in the treated cells. The results demonstrate that although methadone downregulates the mRNA level of GSTP1 in treated cells, it does not induce methylation in the GSTP1 promoter region.ConclusionsThe expression of the GSTP1 remains downregulated even after methadone removal from SH-SY5Y cell culture medium; however, methylation of the GSTP1 promoter site does not play a role in this process.

A preliminary study on identification of the blood donor in a body fluid mixture using a novel compound genetic marker blood-specific methylation-microhaplotype

Blood-containing mixtures are frequently encountered at crime scenes involving violence and murder. However, the presence of blood, and the association of blood with a specific donor within these mixtures present significant challenges in forensic analysis. In light of these challenges, this study sought to address these issues by leveraging blood-specific methylation sites and closely linked microhaplotype sites, proposing a novel composite genetic marker known as “blood-specific methylation-microhaplotype”. This marker was designed to the detection of blood and the determination of blood donor within blood-containing mixtures. According to the selection criteria mentioned in the Materials and Methods section, we selected 10 blood-specific methylation-microhaplotype loci for inclusion in this study. Among these loci, eight exhibited blood-specific hypomethylation, while the remaining two displayed blood-specific hypermethylation. Based on data obtained from 124 individual samples in our study, the combined discrimination power (CPD) of these 10 successfully sequenced loci was 0.999999298. The sample allele methylation rate (Ram) was obtained from massive parallel sequencing (MPS), which was defined as the proportion of methylated reads to the total clustered reads that were genotyped to a specific allele. To develop an allele type classification model capable of identifying the presence of blood and the blood donor, we used the Random Forest algorithm. This model was trained and evaluated using the Ram distribution of individual samples and the Ram distribution of simulated shared alleles. Subsequently, we applied the developed allele type classification model to predict alleles within actual mixtures, trying to exclude non-blood-specific alleles, ultimately allowing us to identify the presence of blood and the blood donor in the blood-containing mixtures. Our findings demonstrate that these blood-specific methylation-microhaplotype loci have the capability to not only detect the presence of blood but also accurately associate blood with the true donor in blood-containing mixtures with the mixing ratios of 1:29, 1:19, 1:9, 1:4, 1:2, 2:1, 7:1, 8:1, 31:1 and 36:1 (blood:non-blood) by DNA mixture interpretation methods. In addition, the presence of blood and the true blood donor could be identified in a mixture containing four body fluids (blood:vaginal fluid:semen:saliva = 1:1:1:1). It is important to note that while these loci exhibit great potential, the impact of allele dropouts and alleles misidentification must be considered when interpreting the results. This is a preliminary study utilising blood-specific methylation-microhaplotype as a complementary tool to other well-established genetic markers (STR, SNP, microhaplotype, etc.) for the analysis in blood-containing mixtures.

Associations of environmental cadmium exposure with kidney damage: Exploring mediating DNA methylation sites in Chinese adults

Environmental exposure is widely recognized as the primary sources of Cadmium (Cd) in the human body, and exposure to Cd is associated with kidney damage in adults. Nevertheless, the role of DNA methylation in Cd-induced kidney damage remains unclear. This study aimed to investigate the epigenome-wide association of environmental Cd-related DNA methylation changes with kidney damage. We included 300 non-smoking adults from the China in 2019. DNA methylation profiles were measured with Illumina Infinium MethylationEPIC BeadChip array. Linear mixed-effect model was employed to estimate the effects of urinary Cd with DNA methylation. Differentially methylated positions (DMPs) associated with urinary Cd were then tested for the association with kidney damage indicators. The mediation analysis was further applied to explore the potential DNA methylation based mediators. The prediction model was developed using a logistic regression model, and used 1000 bootstrap resampling for the internal validation. We identified 27 Cd-related DMPs mapped to 20 genes after the adjustment of false-discovery-rate for multiple testing among non-smoking adults. 17 DMPs were found to be associated with both urinary Cd and kidney damage, and 14 of these DMPs were newly identified within the Chinese. Mediation analysis revealed that DNA methylation of cg26907612 and cg16848624 mediated the Cd-related reduced kidney damage. In addition, ten variables were selected using the LASSO regression analysis and were utilized to develop the prediction model. It found that the nomogram model predicted the risk of kidney damage caused by environmental Cd with a corrected C-index of 0.779. Our findings revealed novel DMPs associated with both environmental Cd exposure and kidney damage among non-smoking adults, and developed an easy-to-use nomogram-illustrated model using these novel DMPs. These findings could provide a theoretical basis for formulating prevention and control strategies for kidney damage from the perspective of environmental pollution and epigenetic regulation.