Distinct Methylation Signatures Research Articles

P.102 Integration of Ultrasensitive electroluminescent immunoassay and cell-free DNA methylation analysis for the non-invasive discrimination of adult diffuse gliomas

Background: Gliomas are highly aggressive brain tumors with nearly universal recurrence rate. Despite this, the ability to accurately predict tumor recurrence relies solely on serial MRI imaging, highlighting the need for prognostic biomarkers. Due to the low accuracies of individual serum markers, we have proposed the use of an integrated, multi-platform approach to biomarker discovery. Methods: A cohort of 107 glioma plasma samples, including 30 pairs, underwent plasma proteomic, consisting of a panel of serum proteins (FABP4, GFAP, NFL, Tau and MMP3,4 &7) quantified through ultrasensitive electrochemiluminescence multiplexed immunoassays, and plasma DNA methylation analysis, captured through cell-free methylated DNA immunoprecipitation and high-throughput sequencing. Results: Unsupervised hierarchal clustering revealed robust separation of primary and recurrent tumors through plasma proteomics, associated with a distinct plasma methylation signature. NFL, Tau and MMP3 levels differed between primary and recurrent samples; pair-wise analysis revealed increased in NFL and Tau concentrations upon recurrence. Tau levels predicted outcome independent of WHO Grade and IDH status. A predictive model created through the integration of the proteomic and methylation signatures revealed an AUC of 0.83. Conclusions: The combination of DNA methylation and plasma proteomics showcases that an integrative approach may improve the ability of these techniques for the serial monitoring of gliomas patients.

Cell-free DNA methylation reveals cell-specific tissue injury and correlates with disease severity and patient outcomes in COVID-19

BackgroundThe recently identified methylation patterns specific to cell type allows the tracing of cell death dynamics at the cellular level in health and diseases. This study used COVID-19 as a disease model to investigate the efficacy of cell-specific cell-free DNA (cfDNA) methylation markers in reflecting or predicting disease severity or outcome.MethodsWhole genome methylation sequencing of cfDNA was performed for 20 healthy individuals, 20 cases with non-hospitalized COVID-19 and 12 cases with severe COVID-19 admitted to intensive care unit (ICU). Differentially methylated regions (DMRs) and gene ontology pathway enrichment analyses were performed to explore the locus-specific methylation difference between cohorts. The proportion of cfDNA derived from lung and immune cells to a given sample (i.e. tissue fraction) at cell-type resolution was estimated using a novel algorithm, which reflects lung injuries and immune response in COVID-19 patients and was further used to evaluate clinical severity and patient outcome.ResultsCOVID‑19 patients had globally reduced cfDNA methylation level compared with healthy controls. Compared with non-hospitalized COVID-19 patients, the cfDNA methylation pattern was significantly altered in severe patients with the identification of 11,156 DMRs, which were mainly enriched in pathways related to immune response. Markedly elevated levels of cfDNA derived from lung and more specifically alveolar epithelial cells, bronchial epithelial cells, and lung endothelial cells were observed in COVID-19 patients compared with healthy controls. Compared with non-hospitalized patients or healthy controls, severe COVID-19 had significantly higher cfDNA derived from B cells, T cells and granulocytes and lower cfDNA from natural killer cells. Moreover, cfDNA derived from alveolar epithelial cells had the optimal performance to differentiate COVID-19 with different severities, lung injury levels, SOFA scores and in-hospital deaths, with the area under the receiver operating characteristic curve of 0.958, 0.941, 0.919 and 0.955, respectively.ConclusionSevere COVID-19 has a distinct cfDNA methylation signature compared with non-hospitalized COVID-19 and healthy controls. Cell type-specific cfDNA methylation signature enables the tracing of COVID-19 related cell deaths in lung and immune cells at cell-type resolution, which is correlated with clinical severities and outcomes, and has extensive application prospects to evaluate tissue injuries in diseases with multi-organ dysfunction.

Blood-based DNA methylation in advanced Nasopharyngeal Carcinoma exhibited distinct CpG methylation signature

The TNM staging system is currently used to detect cancer stages. Regardless, a small proportion of cancer patients recur even after therapy, suggesting more specific molecular tools are required to justify the stage-specific detection and prompt cancer diagnosis. Thus, we aimed to explore the blood-based DNA methylation signature of metastatic nasopharyngeal carcinoma (NPC) to establish a holistic methylation biomarker panel. For the identification of methylation signature, the EPIC BeadChip-based array was performed. Comparative analysis for identifying unique probes, validation, and functional studies was investigated by analyzing GEO and TCGA datasets. We observed 4093 differentially methylated probes (DMPs), 1232 hydroxymethylated probes, and 25 CpG islands. Gene expression study revealed both upregulated and downregulated genes. Correlation analysis suggested a positive (with a positive r, p ≤ 0.05) and negative (with a negative r, p ≤ 0.05) association with different cancers. TFBS analysis exhibited the binding site for many TFs. Furthermore, gene enrichment analysis indicated the involvement of those identified genes in biological pathways. However, blood-based DNA methylation data uncovered a distinct DNA methylation pattern, which might have an additive role in NPC progression by altering the TFs binding. Moreover, based on tissue-specificity, a variation of correlation between methylation and gene expression was noted in different cancers.

Integrated Methylation and Transcriptional Landscape and Evolution of Pediatric AML

Acute myeloid leukemia (AML) is an aggressive hematopoietic malignancy associated with poor outcomes despite intensive therapies. The genomic landscape of pediatric AML has been well characterized and has led to translational benefits, such as improved relapse predication and effective targeted therapies for a subset of individuals (e.g., FLT3-ITD AML). Despite these advances, the majority of patients continue to receive therapeutic interventions that have not changed in three decades. This underscores the need to advance our understanding of AML biology beyond genomic alterations (e.g., somatic mutations). Here, we present the largest (N = 858 patients) integrative analysis of pediatric AML paired transcriptomes and methylomes to date, performed at diagnosis for patients enrolled on Children's Oncology Group clinical trials AAML0531 (NCT00372593) or AAML1031 (NCT01371981). We also analyzed N = 400 and 253 corresponding transcriptomes and methylomes at relapse, respectively. Additionally, we performed comprehensive mutation and fusion calling from NGS data and integrated clinical covariates and outcomes. This robust dataset allowed us to uncover how pediatric AML epigenetics are perturbed from normal hematopoiesis, characterize the evolution of transcriptional and methylation changes from leukemia diagnosis to relapse, and identify more accurate relapse prediction models for pediatric AML. We initially performed unbiased hierarchical clustering on CpG sites that are differentially methylated between AML and normal bone marrow to identify distinct AML-restricted methylation (ARM) signatures. This analysis demonstrated that that these ARM clusters were enriched in specific cytomolecular subtypes of pediatric AML. Specifically, we identified methylation signatures that recapitulated their adult counterparts (e.g., IDH1/2, DNMT3A, WT1) and pediatric specific methylation signatures that clustered with RUNX1::RUNX1T1, CBFB::MYH11, KMT2A-rearrangement, NUP98::NSD1, NUP98::KDM5A, and CEBPA mutant AML. Next, we investigated the transcriptional and methylation signatures for the relapsed cases and compared them to diagnosis. We demonstrated that relapsed transcriptional and methylation signatures clustered within their cytomolecular subtype counterparts at diagnosis (i.e., AMLs at relapse more closely resemble AMLs at diagnosis with the same underlying gene fusion than other relapsed AMLs) ( Fig. 1A). However, analyzing our data in the context of these cytomolecular subtypes, we found that leukemias uniformly acquired a more stem-like state at relapse. We focused our biomarker discovery efforts on KMT2A-rearranged AMLs since (as a cohort) these patients have an intermediate risk of relapse and existing molecular biomarkers (e.g., KMT2A fusion partner and measurable residual disease detection) result in only modest improvements in relapse prediction. First, we found that CpG islands associated with CD34 and HOXA gene expression were frequently (but variably) hypermethylated, which was also associated with downregulation of CD34 and HOXA gene expression and favorable survival outcomes. Next, we performed non-negative matrix factorization on diagnosis and relapsed KMT2A-rearranged AMLs and identified a novel gene set associated with relapse and poor outcomes. These three distinct methylation-transcriptional findings (i.e., CD34, HOXA, and relapsed signatures) were subsequently transformed into a novel methylation-transcription biomarker score (MTBS) using machine learning algorithms (i.e., LASSO Cox regression). We used KMT2A-rearranged AML patients from AAML1031 as our training cohort (N = 129) to generate a MTBS that was able to distinguish KMT2A-rearranged cases with disparate outcomes. This algorithm was validated in an independent cohort from AAML0531 (N = 28) ( Fig. 1B). Additional methylation-transcriptional biomarker discovery efforts for pediatric AML are underway. Since pediatric AML is associated with a low mutational burden, understanding leukemia-specific transcriptional and epigenetic alterations is of utmost importance. Our study demonstrates the translational promise offered by deep functional genomic characterization of pediatric AML and we believe that further interrogation may provide additional novel insights into leukemia initiation, relapse prediction, and novel treatment approaches.

DNA Methylation Profiling Distinguishes Adamantinoma-Like Ewing Sarcoma From Conventional Ewing Sarcoma

Adamantinoma-like Ewing sarcoma (ALES) has traditionally been considered a variant of Ewing sarcoma because it generally harbors EWSR1::FLI1 fusions despite showing diffuse positivity for keratins and p40. However, it has become increasingly recognized that different tumors can have identical translocations, including shared fusions between carcinomas and sarcomas, raising questions as to whether ALES might represent a separate entity. Using methylation profiling, we further explored the relationship between Ewing sarcoma and ALES. The archives of multiple institutions were searched for candidate cases of ALES. DNA methylation profiling was performed and results were compared to corresponding data from conventional Ewing sarcoma. Twelve cases of ALES (5 previously reported) were identified in 10 men and 2 women (aged 20-72 years; median age, 41.5 years). Cases included tumors arising in the parotid gland (3), sinonasal cavity (2), submandibular gland (2), thyroid gland (1), neck (1), gingiva (1), hypopharynx (1), and mandible (1). Histologic review consistently showed sheets and nests of basaloid cells within a fibromyxoid or hyalinized stroma. All tumors were positive for at least 1 keratin and CD99 expression, whereas all 10 cases tested were positive for p63 or p40; S100 protein expression was noted in 2 cases. Cases harbored either EWSR1::FLI1 fusions (n = 6), FUS::FLI1 fusions (n = 1), and/or EWSR1 rearrangements (n = 6). Methylation profiling was successful in 11/12 cases evaluated. Unsupervised clustering and dimensionality reduction (Uniform Manifold Approximation and Projection) of DNA methylation data revealed a distinct methylation cluster for all 11 cases, including the tumor with the FUS::FLI1 fusion, which clearly segregated them from the conventional Ewing sarcoma. Follow-up (n = 11, 1-154 months) revealed that 4 patients experienced recurrence and 6 developed metastatic disease. ALES demonstrates a distinct methylation signature from conventional Ewing sarcoma. This finding adds to the distinctive immunoprofile of ALES, suggesting that these 2 tumors should be considered distinct entities rather than histologic extremes of the same disease.

Abstract 6698: Combinatorial genomic and epigenomic cell-free DNA analysis of high-risk metastatic castration resistant prostate cancer reveals prognostic liquid biopsy signatures

Abstract Background: Androgen receptor signaling inhibitors (ARSI) such abiraterone and enzalutamide have significantly improved clinical outcomes in metastatic castrate-resistant prostate cancer (mCRPC) patients. However, patients with genomic alterations in the androgen receptor (AR) and its enhancer region do not respond well and acquire resistance to these inhibitors. Here, we applied our previously developed cell-free DNA (cfDNA) liquid biopsy assay (EnhanceAR-Seq) to detect these high-risk mCRPC patients prior to the administration of first-line AR-directed therapy and correlated with survival. We also interrogated the plasma methylome to identify differentially methylated regions (DMRs) across these high-risk patients. Methodology: We applied EnhanceAR-Seq to plasma cfDNA isolated from 99 mCRPC patients enrolled from two institutions (n=52 Tulane; n=47 WashU). Plasma samples were collected prior to ARSI initiation (n=63) or during treatment (n=36). We also performed Enzymatic Methyl-seq in pre-treatment plasma from 43 patients. We split these 43 patients into cell-free genomically high-risk and low-risk groups using our EnhanceAR-seq results, and conducted DMR analysis using metilene. To identify significant DMRs, we performed multiple hypothesis testing and required q<0.05 using the Benjamini-Hochberg procedure, and further required at least 5 CpGs per DMR. Results: EnhanceAR-Seq detected AR/enhancer alterations in 35% of all plasma samples. Cell-free AR/enhancer detection was highly prognostic (PFS HR=2.80, p=0.0002; OS HR=2.6, p=0.01). When considering only pre-treatment plasma, AR/enhancer alterations detected in 44% (28/63) of samples correlated significantly with worse PFS (HR=2.21, p=0.009) and OS (HR=2.60, p=0.02). AR/enhancer alterations detected in 19% (7/36) of samples collected during ARSI were also associated with worse PFS (HR=15.6, p=0.0002) and OS (HR=8.09, p=0.05). Plasma methylome analysis revealed that for cell-free genomically high-risk mCRPC patients (based on AR/enhancer alterations detected in cfDNA), significantly hypomethylated DMRs were found in the AR promoter, upstream AR enhancer, and in AR-associated genes including FOXP1 and FOLH1. Significantly hypomethylated DMRs were also observed in DNA damage repair and cell cycle genes including MSH6, MSH3, FANCD2, CDK12 and RAD51B. Hypermethylated DMRs were seen in tumor suppressor genes including ZBTB16, BRCA2, WT1 and GNAS. Conclusions: AR/enhancer alterations detected in plasma cfDNA predicted inferior survival in mCRPC patients. Cell-free genomically high-risk mCRPC patients could be distinguished from low-risk patients based on distinct methylation signatures. Citation Format: Irfan Alahi, Pradeep S. Chauhan, Alexander L. Shiang, Jace Webster, Ha X. Dang, Lilli Greiner, Breanna yang, Elisa M. Ledet, Ramandeep K. Babbra, Wenjia Feng, Peter K. Harris, Ellen B. Jaeger, Patrick J. Miller, Sydney A. Caputo, Giordano Cittolin Santos, Oliver Sartor, Russell K. Pachynski, Christopher A. Maher, Aadel A. Chaudhuri. Combinatorial genomic and epigenomic cell-free DNA analysis of high-risk metastatic castration resistant prostate cancer reveals prognostic liquid biopsy signatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6698.

DICER1-associated central nervous system sarcoma: A comprehensive clinical and genomic characterization of case series of young adult patients.

DICER1 alterations are associated with intracranial tumors in the pediatric population, including pineoblastoma, pituitary blastoma, and the recently described "primary DICER1-associated CNS sarcoma" (DCS). DCS is an extremely aggressive tumor with a distinct methylation signature and a high frequency of co-occurring mutations. However, little is known about its treatment approach and the genomic changes occurring after exposure to chemoradiotherapy. We collected clinical, histological, and molecular data from eight young adults with DCS. Genomic analysis was performed by Next-generation Sequencing (NGS). Subsequently, an additional germline variants analysis was completed. In addition, an NGS analysis on post-progression tumor tissue or liquid biopsy was performed when available. Multiple clinicopathological characteristics, treatment variables, and survival outcomes were assessed. Median age was 20 years. Most lesions were supratentorial. Histology was classified as fusiform cell sarcomas (50%), undifferentiated (unclassified) sarcoma (37.5%), and chondrosarcoma (12.5%). Germline pathogenic DICER1 variants were present in two patients, 75% of cases had more than one somatic alteration in DICER1, and the most frequent commutation was TP53. Seven patients were treated with surgery, Ifosfamide, Cisplatin, and Etoposide (ICE) chemotherapy and radiotherapy. The objective response was 75%, and the median time to progression (TTP) was 14.5 months. At progression, the most common mutations were in KRAS and NF1. Overall survival was 30.8 months. DCS is an aggressive tumor with limited therapeutic options that requires a comprehensive diagnostic approach, including molecular characterization. Most cases had mutations in TP53, NF1, and PTEN, and most alterations at progression were related to MAPK, RAS and PI3K signaling pathways.

DNA methylation is a comprehensive marker for pediatric adrenocortical tumors.

Children diagnosed with pediatric adrenocortical tumors (pACT) have variable outcomes, and, to date, the disease lacks robust prognostic biomarkers. The prognostic potential of tumor methylation has been demonstrated in several cancers. We aimed to evaluate the pACT methylation profile and its association with disease presentation and survival. In this cross-sectional study, we accessed the DNA methylation (MethylationEPIC Array, Illumina) of 57 primary pACT from Southeastern Brazil and the respective patients' clinicopathological features. We also applied our analysis in an independent 48 pACT methylation dataset. Unsupervised learning whole-methylome analysis showed two groups with distinct methylation signatures: pACT-1 and pACT-2. Compared to pACT-2, pACT-1 tumors were enriched with higher methylation in CpG islands, mainly in gene promoter regions. The topmost hypermethylated gene in these samples was shown to be underexpressed. Patients in the pACT-1 group were older at diagnosis and were more likely to have carcinomas and nonlocalized/advanced and recurrent/metastatic disease. Univariate and bivariate regressions showed that pACT-1 methylation signature confers superior hazard ratio of disease progression and death than known prognostic features. The methylation groups had similar frequencies of germline mutations in the TP53 gene, including the regionally frequent p.R337H. Our analysis replication validated our findings and reproduced those recently described in pACT. We demonstrated the existence of different tumor methylation signatures associated with pACT presentation and clinical evolution, even in the context of germline TP53 mutations. Our data support tumor methylation profiling as a robust and independent prognostic biomarker for pACT and suggest a list of candidate genes for further validation.

Deoxyribonucleic acid methylation signatures in sperm deoxyribonucleic acid fragmentation

To evaluate Deoxyribonucleic acid (DNA) methylation patterns in sperm from men with differential levels of sperm DNA fragmentation index (DFI). Prospective study. University-affiliated reproductive medicine center. A total of 278 male patients consulting for couple infertility were recruited from the First Affiliated Hospital of Wenzhou Medical University. None. Genome-wide DNA methylation analysis was performed using Infinium MethylationEPIC BeadChip on spermatozoal DNA from 20 male patients. Differentially methylated regions (DMRs) were identified and validated using targeted bisulfite amplicon sequencing in spermatozoal DNA from 266 males. Unsupervised hierarchical clustering analysis revealed three main clusters corresponding to sperm DFI levels (low, medium, or high). Between-cluster comparisons identified 959 (medium-low), 738 (high-medium), and 937 (high-low) DMRs. Sixty-six DMRs were validated in the 266-sample cohort, of which nine CpG fragments corresponding to nine genes (BLCAP, DIRAS3, FAM50B, GNAS, MEST, TSPAN32, PSMA8, SYCP1, and TEX12) exhibited significantly altered methylation in those with high DFI (≥25%) compared with those with low DFI (<25%). We identified and validated a distinct DNA methylation signature associated with sperm DNA damage in a large, unselected cohort. These results indicate that sperm DNA damage may affect DNA methylation patterns in human sperm.

Deconvolution of sarcoma methylomes reveals varying degrees of immune cell infiltrates with association to genomic aberrations

BackgroundSoft-tissue sarcomas (STS) are a heterogeneous group of mesenchymal tumors for which response to immunotherapies is not well established. Therefore, it is important to risk-stratify and identify STS patients who will most likely benefit from these treatments.ResultsTo reveal shared and distinct methylation signatures present in STS, we performed unsupervised deconvolution of DNA methylation data from the TCGA sarcoma and an independent validation cohort. We showed that leiomyosarcoma can be subclassified into three distinct methylation groups. More importantly, we identified a component associated with tumor-infiltrating leukocytes, which suggests varying degrees of immune cell infiltration in STS subtypes and an association with prognosis. We further investigated the genomic alterations that may influence tumor infiltration by leukocytes including RB1 loss in undifferentiated pleomorphic sarcomas and ELK3 amplification in dedifferentiated liposarcomas.ConclusionsIn summary, we have leveraged unsupervised methylation-based deconvolution to characterize the immune compartment and molecularly stratify subtypes in STS, which may benefit precision medicine in the future.

Tumor DNA Methylation Profiling Is a Robust and Independent Prognostic Marker for Pediatric Patients With Adrenocortical Tumors

Abstract Pediatric adrenocortical tumors (pACTs) display complex genomic background and lack robust prognostic biomarkers. However, pACT methylation profiling was recently associated with patient prognosis. In order to evaluate whether tumor DNA methylation is associated with patient prognosis, we studied a Brazilian cohort of pACT in which most of the patients were carriers of the germline P53 p.R337H mutation (86%). We analyzed the DNA methylation profile of 57 tumor samples (MethylationEPIC BeadChip Array, Illumina) and the respective patients’ clinicopathological features associated with outcome and overall survival. Median age at diagnosis of the 40 girls and 17 boys was 2.1 years (range: 0.2–16.6). Reduced overall survival was observed in patients diagnosed after 4 years of age (n=43, HR=26.5, p&amp;lt;0.0001, 5-year survival (5ys)=43%), in those presenting with Cushing’s syndrome (n=7, HR=12.5, p&amp;lt;0.0001, 5ys=28%), advanced/non localized disease (IPACTR stages III and IV; n=11, HR=12.9, p&amp;lt;0.0001, 5ys=33%) or carcinomas (n=10, HR=4.9, p=0.04 5ys=56%). Unsupervised analysis of methylation data (Euclidean distance and Ward’s method; Pvclust package, R, version 4.0.3) included all 766,031 probes filtered in by the quality control step, and revealed two groups with distinct methylation signatures with a bootstrap support of 99%, namely pACT1 and pACT2. The overall variance of differentially methylated probes (DMPs; FDR p-values &amp;lt;10–6 and, simultaneously, median M-value difference &amp;gt;2) between the groups was 0.084% (n=642 probes). Tumors from pACT1 were enriched for hypomethylation in genes’ body region and for hypermethylation in promoter regions (p&amp;lt;0.0001). Gene set analysis showed that DMPs were mostly enriched in gene sets involved in nervous system differentiation and development, mRNA binding, and peptide secretion and related to pathways in cancer, cell adhesion, and calcium signaling. Methylation was not associated with germline P53 p.R337H mutation (p=0.57). Compared to pACT2, pACT1 group comprised patients older at diagnosis (p=0.0004) and higher frequencies of patients diagnosed after 4 years of age (80 vs 13%; p&amp;lt;0.0001), presenting with Cushing syndrome (40 vs. 4%; p=0.01), non-localized/advanced disease (70 vs 8%; p=0.0001), carcinomas (71 vs 17%. p=0.009), who needed adjuvant chemotherapy (90 vs. 9%; p&amp;lt;0.0001), and who experienced post-surgery recurrence or metastasis (90 vs 6%; p&amp;lt;0.0001). pACT1 methylation signature was associated with reduced overall survival from the disease (HR=51, p=0.0001, 5ys: 20 vs 98%), and remained associated after adjusting for prognostic features. Interestingly, different tumor methylation signatures were associated with pACT clinical presentation and evolution, regardless the presence of the P53 p.R337H mutation. Our data supports the analysis of methylation profiling as a robust and independent prognostic biomarker for pACT.

Human DNA methylation signatures differentiate persistent from resolving MRSA bacteremia

Persistent methicillin-resistant Staphylococcus aureus (MRSA) bacteremia is life threatening and occurs in up to 30% of MRSA bacteremia cases despite appropriate antimicrobial therapy. Isolates of MRSA that cause antibiotic-persistent methicillin-resistant S. aureus bacteremia (APMB) typically have in vitro antibiotic susceptibilities equivalent to those causing antibiotic-resolving methicillin-resistant S. aureus bacteremia (ARMB). Thus, persistence reflects host-pathogen interactions occurring uniquely in context of antibiotic therapy in vivo. However, host factors and mechanisms involved in APMB remain unclear. We compared DNA methylomes in circulating immune cells from patients experiencing APMB vs. ARMB. Overall, methylation signatures diverged in the distinct patient cohorts. Differentially methylated sites intensified proximate to transcription factor binding sites, primarily in enhancer regions. In APMB patients, significant hypomethylation was observed in binding sites for CCAAT enhancer binding protein-β (C/EBPβ) and signal transducer/activator of transcription 1 (STAT1). In contrast, hypomethylation in ARMB patients localized to glucocorticoid receptor and histone acetyltransferase p300 binding sites. These distinct methylation signatures were enriched in neutrophils and achieved a mean area under the curve of 0.85 when used to predict APMB using a classification model. These findings validated by targeted bisulfite sequencing (TBS-seq) differentiate epigenotypes in patients experiencing APMB vs. ARMB and suggest a risk stratification strategy for antibiotic persistence in patients treated for MRSA bacteremia.

Comprehensive Profiling of the Epitranscriptomic N6-Methyladenosine RNA Methylation in Chronic Lymphocytic Leukemia

Introduction N6-methyladenosine (m6A) is the most prevalent post-transcriptional modification of eukaryotic mRNA. Accumulating evidence suggests that RNA m6A methylation exerts crucial roles in oncogenesis. However, the mRNA m6A methylation pattern in chronic lymphocytic leukemia (CLL) has not been investigated. Hence, the aim of this study is to perform a comprehensive profiling to identify distinct m6A methylation signatures in CLL patients. Methods Peripheral blood samples from de novo CLL patients were collected with informed consents at the Department of Hematology in Shandong Provincial Hospital Affiliated to Shandong First Medical University. CD19+ B cells were isolated with informed consents from healthy donors. Methylated RNA immunoprecipitation sequencing (MeRIP-Seq) was conduct to profile mRNA m6A methylation of CLL-B cells and normal CD19+ B cells at Novogene (Beijing, China). The library preparations were sequenced on an Illumina Novaseq platform with a paired-end read length of 150 bp according to the standard protocols. The sequencing was carried out with 3 independent biological replicates. After mapping reads to the reference genome, exomePeak R package was used for the m6A peak identification in each anti-m6A immunoprecipitation group with the corresponding input samples serving as a control, and q-value threshold of enrichment of 0.05 was used for all data sets. The m6A-enriched motifs of each group were identified by HOMER. Differential peak calling was performed using exomePeak R package with parameters of p-value &amp;lt; 0.05 and fold_change &amp;gt; 1. Functional enrichment analyses of gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) of differentiated peaks associated genes were performed. All investigators comply with the guiding principles for experimental procedures found in the Declaration of Helsinki of the World Medical Association. Results By MeRIP sequencing, significant distribution of methylation peaks were detected in 5'UTR, 3'UTR and CDS regions of CLL primary cells (Figure 1A) and normal B cells (Figure 1B). Figure 1C-D illustrated the percentage of methylation peaks in the five regions, suggesting distinct m6A patterns in CLL cells. Moreover, Figure 1E-F revealed the positions of m6A methylation peaks in chromosomes of CLL and normal B cells. Furthermore, the compared distributions of m6A methylation peaks in CLL and normal B cells were presented in Figure 2A. Besides, the bean plot visibly displayed the obvious differentiation of methylation peaks in CLL group and normal B cells in read density (Figure 2B). Importantly, a total of 1836 significantly changed peaks, of which 1519 were significantly up-regulated and 317 peaks were significantly down-regulated (p&amp;lt;0.05, |log2Foldchange|&amp;gt;1; Figure 2C). These m6A peaks were located across 1850 genes. Functional enrichment analyses identified that differentiated peaks associated genes were potentially regulate RNA metabolic process via oncogenic pathways in CLL pathogenesis (Figure 3A-B). In addition, HOMER analysis identified 38 significant de novo m6A peak motifs, top 10 most significant peak motifs of which were presented (Figure 3C), illuminating potential detailed mechanism of m6A RNA methylation in the tumorigenesis and progression of CLL. Conclusion Taken together, our investigations explored for the first time the m6A methylation pattern of mRNA in CLL. m6A modifications play crucial roles in the progression and survival of CLL patients,highlighting m6A modifications-targeted intervention formulating a novel treatment paradigm in progressed CLL that warrants clinical investigation. Disclosures No relevant conflicts of interest to declare.

Combined Methylome and Transcriptome Analyses Reveals Potential Therapeutic Targets for EGFR Wild Type Lung Cancers with Low PD-L1 Expression.

Simple SummaryLow expression of programmed death-ligand 1 (PD-L1), epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLCs) are refractory, and only few therapeutic options exist. This study aims to clarify the molecular basis of this special subtype of NSCLC and identify potential therapeutic targets. We performed integrating data from multiple sources including transcriptome, methylome, and clinical outcome to uncover the effect of epigenetic changes acting this special subtype lung cancer. We elucidated both aberrant methylation and associated aberrant gene expression and the emerging methylation-transcription patterns were classified as HypoUp, HypoDown, HyperUp, or HyperDown. We found that the aberrant methylation-transcription patterns significantly affect the overall survival time of the patients. We used protein–drug interaction data and molecular docking analysis to identify potential therapeutic candidates. This study uncovered the distinct methylation-transcription characteristics of this special subtype lung cancer, and provided an adaptable way to identify potential therapeutic targets.Immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 have demonstrated remarkable treatment efficacy in advanced non-small cell lung cancer (NSCLC). However, low expression of programmed death-ligand 1 (PD-L1), epidermal growth factor receptor (EGFR) wild-type NSCLCs are refractory, and only few therapeutic options exist. Currently, combination therapy with ICIs is frequently used in order to enhance the treatment response rates. Yet, this regimen is still associated with poor treatment outcome. Therefore, identification of potential therapeutic targets for this subgroup of NSCLC is strongly desired. Here, we report the distinct methylation signatures of this special subgroup. Moreover, several druggable targets and relevant drugs for targeted therapy were incidentally identified. We found hypermethylated differentially methylated regions (DMRs) in three regions (TSS200, TSS1500, and gene body) are significantly higher than hypomethylated ones. Downregulated methylated genes were found to be involved in negative regulation of immune response and T cell-mediated immunity. Moreover, expression of four methylated genes (PLCXD3 (Phosphatidylinositol-Specific Phospholipase C, X Domain Containing 3), BAIAP2L2 (BAR/IMD Domain Containing Adaptor Protein 2 Like 2), NPR3 (Natriuretic Peptide Receptor 3), SNX10 (Sorting Nexin 10)) can influence patients’ prognosis. Subsequently, based on DrugBank data, NetworkAnalyst 3.0 was used for protein–drug interaction analysis of up-regulated differentially methylated genes. Protein products of nine genes were identified as potential druggable targets, of which the tumorigenic potential of XDH (Xanthine Dehydrogenase), ATIC (5-Aminoimidazole-4-Carboxamide Ribonucleotide Formyltransferase/IMP Cyclohydrolase), CA9 (Carbonic Anhydrase 9), SLC7A11 (Solute Carrier Family 7 Member 11), and GAPDH (Glyceraldehyde-3-Phosphate Dehydrogenase) have been demonstrated in previous studies. Next, molecular docking and molecular dynamics simulation were performed to verify the structural basis of the therapeutic targets. It is noteworthy that the identified pemetrexed targeting ATIC has been recently approved for first-line use in combination with anti-PD1 inhibitors against lung cancer, irrespective of PD-L1 expression. In future work, a pivotal clinical study will be initiated to further validate our findings.

Abstract 2114: HPV-driven cancers show distinct methylation signatures in cell-free DNA (cfDNA)

Abstract Accurate tissue of origin (TOO) prediction is crucial for effective clinical follow-up in early cancer detection from blood. In the second substudy of the Circulating Cell-free Genome Atlas (CCGA; NCT02889978), we trained logistic regression classifiers under cross-validation to detect and localize cancer. Input features were methylation states from a targeted cfDNA assay of 2023 participants. TOO classification accuracy was 89% across 20 pre-specified prediction classes. We subsequently sought to understand the causes of the remaining TOO errors. 45% of the errors fell into clusters reflecting similarities in developmental biology, histology, or oncological drivers. Here, we analyzed tissues that may be affected by HPV-driven cancers; these accounted for 21% of TOO errors. The original classifier, which used only human epigenetic states as input, demonstrated cross-scoring between likely HPV-driven cancers of the anus (N = 14) and cervix (N = 11), as well as confirmed HPV-positive head &amp; neck (H&amp;N) cancers (37/62). We also observed HPV-associated vulva (N = 9) and penis (N = 1) cancers, which were not directly trained as TOO classes, were assigned high H&amp;N scores. To test the hypothesis of HPV-driven TOO confusion, we assessed HPV cfDNA and HPV-driven methylation in human peripheral blood cfDNA, and used a specialist classifier restricted to HPV-associated cancers to resolve errors. We corroborated putative HPV-positive participants using targeted sequencing of HPV16 and HPV18 cfDNA fragments, and showed that the number of unique HPV-derived fragments in a sample matched with expected cancer localizations, HPV subtypes, and HPV status. Consistent with the literature, we found little evidence of HPV viremia in non-cancer participants despite the high prevalence of transient HPV infections in the US population. At 99.8% specificity, a cross-validated cutoff on the number of HPV cfDNA fragments in a sample achieved sensitivities of 78.6% (11/14), 36.3% (4/11), 66.6% (6/9), 100% (1/1), and 81.0% (30/37), for anus, cervix, vulva, penis, and confirmed HPV-positive H&amp;N cancers, respectively. These sensitivities were similar to those achieved by the epigenetic classifier. Finally, we trained a cross-validated specialist classifier using the same features as the TOO classifier, but restricted to HPV-driven cancers. This improved TOO accuracy for detected anal cancers from 11% (1/9) to 100% (9/9), with little effect on other classes. These data support that HPV presence may explain observed cross-scoring patterns between H&amp;N, cervix, and anus TOO prediction classes, which were driven by recurrent epigenomic changes in participants with HPV-positive cancers as detected by this assay. This suggests that modelling axes of shared biology across cancer types can be useful for accurate cfDNA TOO classification, which is critical to direct diagnostic work-up of diverse cancer types in a multi-cancer early detection test. Citation Format: Robert Calef, Oliver Venn, M. Cyrus Maher, John F. Beausang, Earl Hubbell, Aman Patel, Alexander P. Fields, Joerg Bredno, Arash Jamshidi, Alexander M. Aravanis. HPV-driven cancers show distinct methylation signatures in cell-free DNA (cfDNA) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2114.

High level MYCN amplification and distinct methylation signature define an aggressive subtype of spinal cord ependymoma

We report a novel group of clinically aggressive spinal cord ependymomas characterized by Grade III histology, MYCN amplification, an absence of NF2 alterations or other recurrent pathogenic mutations, and a unique methylation classifier profile. Seven cases were found to have MYCN amplification in the course of routine mutational profiling of 552 patients with central nervous system tumors between December 2016 and July of 2019 and an eighth patient was identified from an unrelated set of cases. Methylation array analysis revealed that none of the 8 cases clustered with any of the nine previously described ependymoma methylation subgroups, and 7 of 8 formed their own tight unique cluster. Histologically all cases showed grade III features, and all demonstrated aggressive clinical behavior. These findings are presented in the context of data from three other studies describing similar cases. Therefore, a combined total of 27 MYCN amplified spinal cord ependymoma cases have now been reported in the literature, warranting their consideration as a distinctive subtype of spinal cord ependymoma (SP-EPN-MYCN) with their unique molecular characteristics and aggressive clinical behavior.

Proteomic and Genomic Methylation Signatures of Idiopathic Subglottic Stenosis.

Idiopathic subglottic stenosis (iSGS) is a chronic inflammatory condition that causes dyspnea and affects middle-aged women of White race and non-Latino or Hispanic ethnicity. To better characterize its phenotype and pathogenesis, we assessed the proteomic and genomic methylation signatures of subglottic tissue collected from iSGS patients compared to controls. Molecular analysis of clinical biospecimens. We collected subglottic tissue biopsies from 12 patients during direct laryngoscopy, immediately prior to surgical treatment of iSGS; as well as from 4 age-, sex-, and race/ethnicity-matched control patients undergoing other direct laryngoscopic procedures. We isolated protein and genomic DNA, acquired proteomic data using label-free quantitative mass spectrometry techniques, and acquired genome-wide methylation data using bisulfite conversion and a microarray platform. We compared molecular profiles across the iSGS and control groups, and with respect to clinical course in the iSGS group. Eight of the 12 iSGS patients underwent subsequent blood collection and plasma isolation for further assessment. Proteomic analysis revealed 42 differentially abundant proteins in the iSGS biopsies compared to controls, inferring enrichment of biological pathways associated with early wound healing, innate immunity, matrix remodeling, and metabolism. Proteome-based hierarchical clustering organized patients into two iSGS and one control subgroups. Methylation analysis revealed five hypermethylated genes in the iSGS biopsies compared to controls, including the biotin recycling enzyme biotinidase (BTD). Follow-up analysis showed elevated plasma BTD activity in iSGS patients compared to both controls and published normative data. iSGS exhibits distinct proteomic and genomic methylation signatures. These signatures expand current understanding of the iSGS phenotype, support the possibility of disease subgroups, and should inform the direction of future experimental studies. Not applicable Laryngoscope, 131:E540-E546, 2021.

Abstract P1-21-02: Distinct methylation and copy number alteration patterns in phyllodes tumors of the breast and its mimics

Abstract Background: Phyllodes tumor (PT), a rare fibroepithelial neoplasm of the breast, poses a significant diagnostic challenge in breast pathology, as there are no generally accepted histological criteria or cutoffs to unambiguously differentiate PT variants (benign, borderline, malignant) and fibroadenomas (FA) of the breast. In recent years, genome-wide DNA methylation analysis has gained wide interest as an objective tool to distinguish all sorts of neoplasms based on their individual methylation signatures. For brain tumors, methylation-based classification already outperforms classification by conventional histology and has led to changes in the WHO tumor classification. Materials and Methods: We have so far analyzed fresh frozen as well as formalin-fixed, paraffin-embedded tissue samples of PT (n=31) and FA (n=2) on Illumina Infinium Methylation EPIC bead chips. The resulting data were preprocessed, normalized, mapped to the genome and converted into beta values. Top differentially methylated probes were determined by the calculation of standard deviations across the dataset. Such filtered sets of methylation beta values were then compared by a dimension reduction algorithm alongside TCGA methylome datasets as well as collections from GEO and the entire diagnostic database of our institute (n=14342). In parallel, the genome-wide copy number alterations were calculated from array data for each case. Results: In analogy to other tumor entities included in our reference cohort (brain tumors, sarcomas, carcinomas, melanomas), PT and FA of the breast show distinct DNA methylation patterns that contain a breast-specific signature as well as tumor-derived patterns. Their methylomes are distinct from breast adenocarcinoma as well as from healthy breast tissue. Two distinct groups within the PT/FA spectrum were identified so far: One group contains a high fraction of histologically malignant PT and is enriched for complex copy number alterations while the other group, also containing the currently two included fibroadenomas and, features less prominent to no copy number variants and a higher similarity to the overall normal breast tissue methylation signature. Conclusion: The distinct methylation signatures of the histological PT/FA spectrum will not only allow the diagnostic discrimination of PTs from histological mimics such as FA or carcinomas, but will also enable the distinction of benign, borderline and malignant PTs, thus paving the way to an optimized prognostic patient stratification and clinical management. Citation Format: Simone Muenst, Tatjana Vlajnic, Savas Deniz Soysal, Stefan Frank, Jürgen Hench. Distinct methylation and copy number alteration patterns in phyllodes tumors of the breast and its mimics [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-21-02.

Epigenomic Signatures in Myelodysplastic Syndrome Patients As Predictors of Donor Compatibility and Transplant Outcome

Myelodysplastic syndromes (MDS) are a heterogeneous group of hematopoietic stem cell disorders for which allogeneic hematopoietic stem cell transplantation (HCT) is currently the only curative treatment. Epigenetic lesions are considered a major pathogenetic determinant in many cancers, including MDS, and combination epigenetic therapies have emerged. In this study, we hypothesize that interplay between key epigenomic signatures in the MDS patient undergoing HCT and their donor epigenomic profile serve as a prognostic factor of post-HCT MDS relapse risk. Reduced representation bisulfite sequencing (RRBS) was chosen to identify genome-wide epigenetic alterations as a cost-efficient method for building large data resources that reduces sequence redundancy and selects only CpG-rich regions of the genome for sequencing. A unique cohort of 188 samples from the Center for International Blood and Marrow Transplant Research (CIBMTR) biorepository was sequenced through RRBS. This cohort was composed of 94 pre-transplant samples from MDS patients that received peripheral blood stem cell grafts and were selected as case/controls for post-HCT relapse/non-relapse matched on patient, disease and transplant characteristics. The remaining 94 samples were from the patients' healthy allogeneic donors. Only patient samples that were wild-type for previously-identified MDS-prognostic TP53, RAS pathway and JAK2 mutations were included in this cohort to promote discovery of novel factors. We developed methylPrep, a Python application, to filter the low methylation calls and group shared sites by donors, relapsed patients and non-relapsed patients. We comprehensively identified differentially methylated regions (DMRs) by comparing the methylation patterns in healthy donors and MDS patients that relapsed or did not relapse. The healthy donor group displayed higher global methylation levels (GML) than the patient group as a whole, and the relapsed patient showed higher GML than the non-relapsed patient, though these differences were not statistically significant, and we continue to investigate whether hypo-methylating agents play a role. We selected high DMRs (50-bp interval), with at least 25% difference in methylation calls, using Fisher's exact test, where the threshold q-value equals 0.05, and uncovered 367 significant hyper-DMRs and 38 significant hypo-DMRs in donors compared to patients genome-wide. For disease relapsed versus non-relapsed MDS patients, we identified 121 hyper-DMRs and 64 hypo-DMRs, and the distribution of DMRs was highly varied. Furthermore, we compared epigenome compatibility between donors and patients who did or did not relapse after transplantation and discovered a distinct difference in DMR patterns from chromosome to chromosome and through region annotation. Interestingly, a higher number of DMRs were located in promoter regions between donors and non-relapsed patients versus donors and disease-relapsed patients. Identified DMRs, especially those located in promoter regions, may be involved in regulation of gene expression. These promoter DMRs may serve as candidate indicators or sites for potential diagnosis and therapy selection for MDS patients and may aid in the prediction of transplant outcomes and matching of the best donor for the MDS patient. Continued investigation will enable validation and assessment of the impact and mode of action for these distinct methylation signatures and global methylation patterns in MDS associated with HCT outcomes. Figure Disclosures Nazha: Incyte: Speakers Bureau; Daiichi Sankyo: Consultancy; Jazz Pharmacutical: Research Funding; Novartis: Speakers Bureau; Tolero, Karyopharma: Honoraria; MEI: Other: Data monitoring Committee; Abbvie: Consultancy.

GENE-60. THE EPITRANSCRIPTOMIC CODE IN LGG: METABOLICALLY REPROGRAMMED IDH-MUTANT GLIOMAS ALTER tRNA MODIFICATION LANDSCAPE

Abstract BACKGROUND Diffuse lower grade gliomas (LGGs) are generally slow growing primary central nervous system tumors that occur in early adult life. The prevalence of isocitrate dehydrogenase (IDH) mutations is high in LGG, and induces excess production of the oncometabolite 2-hydroxyglutarate (2-HG). These gain-of-function mutations play a key role in promoting metabolic reprogramming of the cancer cell that affects activity of α-KG dependent demethylases. Inhibition of DNA demethylase activity leads to glioma with a CpG island methylator phenotype (G-CIMP). Whether the activity of RNA demethylases and methylation status of tRNAs in LGG are modulated by changes in IDH-status is unknown. AIM: To investigate whether IDH mutations play a role in reprogramming of tRNA modifications in adult glioma. MATERIALS AND METHODS We combined small RNAseq and LC-MS/MS analysis to identify distinct tRNA processing patterns and methylation signatures in LGG tissues. To address important experimental bottlenecks that limit RNAseq-based detection of tRNA and possibly other modified small noncoding RNAs, we employed a tailored small RNAseq method with validation of specific methylation sites by mass-spectrometry. RESULTS Our customized small RNAseq approach yielded &gt;100 fold increase in sequencing reads per tRNA type, thereby dramatically improving tRNA detection when compared to currently used small RNAseq approaches. Moreover, LC-MS/MS analysis revealed a higher abundance of modified nucleosides in tRNA from IDH-mutant LGG compared to IDH-wildtype LGG. Analysis of tRNA from IDH-mutant and IDH-wildtype LGG using the combination of our tailored small RNAseq and LC-MS/MS methodology demonstrated strong differential tRNA expression, tRFs processing and tRNA methylation. CONCLUSION We described an approach that makes use of tailored small RNA sequencing combined with mass-spectrometry that enables insights into cancer driven alterations in tRNA methylation patterns and differential tRNA processing signatures. Our data implies that tumor metabolic reprogramming deregulates tRNA methylation, contributing to an altered epitranscriptomic code in IDH-mutant LGG.