Epigenomic Signatures Research Articles

Multi-omics profiling of DNA methylation and gene expression alterations in human cocaine use disorder

Structural and functional changes of the brain are assumed to contribute to excessive cocaine intake, craving, and relapse in cocaine use disorder (CUD). Epigenetic and transcriptional changes were hypothesized as a molecular basis for CUD-associated brain alterations. Here we performed a multi-omics study of CUD by integrating epigenome-wide methylomic (N = 42) and transcriptomic (N = 25) data from the same individuals using postmortem brain tissue of Brodmann Area 9 (BA9). Of the N = 1 057 differentially expressed genes (p < 0.05), one gene, ZFAND2A, was significantly upregulated in CUD at transcriptome-wide significance (q < 0.05). Differential alternative splicing (AS) analysis revealed N = 98 alternatively spliced transcripts enriched in axon and dendrite extension pathways. Strong convergent overlap in CUD-associated expression deregulation was found between our BA9 cohort and independent replication datasets. Epigenomic, transcriptomic, and AS changes in BA9 converged at two genes, ZBTB4 and INPP5E. In pathway analyses, synaptic signaling, neuron morphogenesis, and fatty acid metabolism emerged as the most prominently deregulated biological processes. Drug repositioning analysis revealed glucocorticoid receptor targeting drugs as most potent in reversing the CUD expression profile. Our study highlights the value of multi-omics approaches for an in-depth molecular characterization and provides insights into the relationship between CUD-associated epigenomic and transcriptomic signatures in the human prefrontal cortex.

Genome-Wide Mapping of Main Histone Modifications and Coordination Regulation of Metabolic Genes under Salt Stress in Pea (Pisum sativum L)

Abstract Pea occupy a key position in modern biogenetics, playing a multifaceted roles as food, vegetable, fodder, and green manure. However, due to the complex nature of its genome and the prolonged unveiling of high-quality genetic maps, research into the molecular mechanisms underlying pea development and stress responses has been significantly delayed. Furthermore, the exploration of its epigenetic modification profiles and associated regulatory mechanisms remains uncharted. This research conducted a comprehensive investigation of four specific histone marks, namely H3K4me3, H3K27me3, H3K9ac, and H3K9me2 and the transcriptome in pea under normal condition, and established a global map of genome-wide regulatory elements, chromatin states, and dynamics based on these major modifications. Our analysis identified epigenomic signals across approximately 82.6% of the genome. Each modification exhibits distinct enrichment patterns: H3K4me3 is predominantly associated with the gibberellin response pathway, H3K27me3 is primarily associated with auxin and ethylene responses, and H3K9ac is primarily associated with negative regulatory stimulus responses. We also identified a novel bivalent chromatin state (H3K9ac-H3K27me3) in pea, which is related to their development and stress response. Additionally, we unveil that these histone modifications synergistically regulate metabolic-related genes, influencing metabolite production under salt stress conditions. Our findings offer a panoramic view of the major histone modifications in pea, elucidate their interplay, and highlight their transcriptional regulatory roles during salt stress.

Organoid culture promotes dedifferentiation of mouse myoblasts into stem cells capable of complete muscle regeneration.

Experimental cell therapies for skeletal muscle conditions have shown little success, primarily because they use committed myogenic progenitors rather than true muscle stem cells, known as satellite cells. Here we present a method to generate in vitro-derived satellite cells (idSCs) from skeletal muscle tissue. When transplanted in small numbers into mouse muscle, mouse idSCs fuse into myofibers, repopulate the satellite cell niche, self-renew, support multiple rounds of muscle regeneration and improve force production on par with freshly isolated satellite cells in damaged skeletal muscle. We compared the epigenomic and transcriptional signatures between idSCs, myoblasts and satellite cells and used these signatures to identify core signaling pathways and genes that confer idSC functionality. Finally, from human muscle biopsies, we successfully generated satellite cell-like cells in vitro. After further development, idSCs may provide a scalable source of cells for the treatment of genetic muscle disorders, trauma-induced muscle damage and age-related muscle weakness.

Simultaneous Visualization of R-Loops/RNA:DNA Hybrids and Replication Forks in a DNA Combing Assay.

R-loops, structures that play a crucial role in various biological processes, are integral to gene expression, the maintenance of genome stability, and the formation of epigenomic signatures. When these R-loops are deregulated, they can contribute to the development of serious health conditions, including cancer and neurodegenerative diseases. The detection of R-loops is a complex process that involves several approaches. These include S9.6 antibody- or RNAse H-based immunoprecipitation, non-denaturing bisulfite footprinting, gel electrophoresis, and electron microscopy. Each of these methods offers unique insights into the nature and behavior of R-loops. In our study, we introduce a novel protocol that has been developed based on a single-molecule DNA combing assay. This innovative approach allows for the direct and simultaneous visualization of RNA:DNA hybrids and replication forks, providing a more comprehensive understanding of these structures. Our findings confirm the transcriptional origin of the hybrids, adding to the body of knowledge about their formation. Furthermore, we demonstrate that these hybrids have an inhibitory effect on the progression of replication forks, highlighting their potential impact on DNA replication and cellular function.

CircNAP1L4 regulates pulmonary artery smooth muscle cell proliferation via the NAP1L4-mediated super-enhancer-driven glycolysis gene hexokinase II (HK II) in pulmonary hypertension.

Glycolysis is a major determinant of pulmonary artery smooth muscle cell (PASMC) proliferation in pulmonary hypertension (PH). Circular RNAs (circRNAs) are powerful regulators of glycolysis in multiple diseases; however, the role of circRNAs in glycolysis in PH has been poorly characterized. The aim of this study was to uncover the regulatory mechanism of a new circRNA, circNAP1L4, in human pulmonary artery smooth muscle cell (HPASMC) proliferation through the host protein NAP1L4 to regulate the super-enhancer-driven glycolysis gene hexokinase II (HK II). CircNAP1L4 was downregulated in hypoxic HPASMCs and plasma of PH patients. Functionally, circNAP1L4 overexpression inhibited glycolysis and proliferation in hypoxic HPASMCs. Mechanistically, circNAP1L4 directly bound to its host protein NAP1L4 and affected the ability of NAP1L4 to move into the nucleus to regulate the epigenomic signals of the super-enhancer of HK II. Intriguingly, circNAP1L4 overexpression inhibited the proliferation but not the migration of human pulmonary arterial endothelial cells (HPAECs) cocultured with HPASMCs. Furthermore, pre-mRNA-processing-splicing Factor 8 (PRP8) was found to regulate the production ratio of circNAP1L4 and linear NAP1L4. Invivo, targeting circNAP1L4 alleviates SU5416 combined with hypoxia (SuHx)-induced PH. Overall, these findings reveal a new circRNA that inhibits PASMC proliferation and serves as a therapeutic target for PH.

EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data.

Transcriptional regulation, critical for cellular differentiation and adaptation to environmental changes, involves coordinated interactions among DNA sequences, regulatory proteins, and chromatin architecture. Despite extensive data from consortia like ENCODE, understanding the dynamics of cis-regulatory elements (CREs) in gene expression remains challenging. Deep learning is a powerful tool for learning gene expression and epigenomic signals from DNA sequences, exhibiting superior performance compared to conventional machine learning approaches. However, even the most advanced deep learning-based methods may fall short in capturing the regulatory effects of distal elements such as enhancers, limiting their predictive accuracy. In addition, these methods may require significant resources to train or to adapt to newly generated data. To address these challenges, we present EPInformer, a scalable deep-learning framework for predicting gene expression by integrating promoter-enhancer interactions with their sequences, epigenomic signals, and chromatin contacts. Our model outperforms existing gene expression prediction models in rigorous cross-chromosome validation, accurately recapitulates enhancer-gene interactions validated by CRISPR perturbation experiments, and identifies crucial transcription factor motifs within regulatory sequences. EPInformer is available as open-source software at https://github.com/pinellolab/EPInformer.

Integrated epigenomic exposure signature discovery.

Aim: The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis.Materials & methods: Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES).Results: Signatures were developed for seven exposures including Staphylococcus aureus, human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and Bacillus anthracis vaccinations. ESs differed in the assays and features selected and predictive value.Conclusion: Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment.

Sources of gene expression variation in a globally diverse human cohort.

Genetic variation that influences gene expression and splicing is a key source of phenotypic diversity1-5. Although invaluable, studies investigating these links in humans have been strongly biased towards participants of European ancestries, which constrains generalizability and hinders evolutionary research. Here to address these limitations, we developed MAGE, an open-access RNA sequencing dataset of lymphoblastoid cell lines from 731 individuals from the 1000 Genomes Project6, spread across 5 continental groups and 26 populations. Most variation in gene expression (92%) and splicing (95%) was distributed within versus between populations, which mirrored the variation in DNA sequence. We mapped associations between genetic variants and expression and splicing of nearby genes (cis-expression quantitative trait loci (eQTLs) and cis-splicing QTLs (sQTLs), respectively). We identified more than 15,000 putatively causal eQTLs and more than 16,000 putatively causal sQTLs that are enriched for relevant epigenomic signatures. These include 1,310 eQTLs and 1,657 sQTLs that are largely private to underrepresented populations. Our data further indicate that the magnitude and direction of causal eQTL effects are highly consistent across populations. Moreover, the apparent 'population-specific' effects observed in previous studies were largely driven by low resolution or additional independent eQTLs of the same genes that were not detected. Together, our study expands our understanding of human gene expression diversity and provides an inclusive resource for studying the evolution and function of human genomes.

Unraveling epigenomic signatures and effectiveness of electroconvulsive therapy in treatment-resistant depression patients: a prospective longitudinal study

BackgroundElectroconvulsive therapy (ECT) benefits patients with treatment-resistant depression (TRD), but the underlying biological processes are unclear. We conducted an epigenome-wide association study in 32 TRD patients undergoing ECT to depict ECT-associated methylation changes. Illness severity and ECT outcomes were assessed with the Montgomery–Åsberg Depression Rating Scale at baseline (T0) and 1 month after its end (T1). Methylation was profiled at T0 and T1 with the Illumina Infinium Methylation EPIC BeadChip array.ResultsLongitudinal T0–T1 analyses showed 3 differentially methylated probes (DMPs) with nominal p values ≤ 10−5, with 2 annotated in the genes CYB5B and PVRL4. Including covariates, we found 4 DMPs for symptoms variation, annotated in FAM20C, EPB41, OTUB1 and ADARB1, and 3 DMPs for response status, with 2 annotated in IQCE and FAM20C. Regional analysis revealed 54 differentially methylated regions (DMRs) with nominal p value area ≤ 0.05, with 9 presenting adjusted p-value area ≤ 0.10, annotated in MCF2L, SLC25A24, RUNX3, MIR637, FOXK2, FAM180B, POU6F1, ALS2CL and CCRL2. Considering covariates, we found 21 DMRs for symptoms variation and 26 DMRs for response (nominal p value area ≤ 0.05), with 4 presenting adjusted p-value area ≤ 0.10 for response, annotated in SNORD34, NLRP6, GALNT2 and SFT2D3. None remained significant after false discovery rate correction. Notably, ADARB1 variants are associated with suicide attempt in patients with psychiatric disorders, and SLC25A24 relates to conduct disorder. Several DMPs and DMRs are annotated in genes associated with inflammatory/immune processes. Longitudinal analyses on females (n = 22) revealed statistically significant DMRs (adjusted p value area ≤ 0.05) and trend-significant DMRs (adjusted p value area ≤ 0.07) for symptoms variation and response status, annotated in genes related to psychiatric disorders (ZFP57, POLD4, TRIM10, GAS7, ADORA2A, TOLLIP), trauma exposure (RIPOR2) and inflammatory/immune responses (LAT, DLX4, POLD4, FAM30A, H19). Pathway analysis on females revealed enrichment for transcriptional activity, growth factors, DNA maintenance, and immune pathways including IRF7 and IRF2.ConclusionAlthough no significant results were found for the whole cohort, the study provides insights into ECT-associated methylation changes, highlighting DMPs and DMRs related to ECT outcomes. Analyses on females revealed significant DMRs and pathways related to psychiatric disorders and inflammatory/immune processes.

Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) biomarker studies rarely employ multi-omic biomarker strategies and pertinent clinicopathologic characteristics to predict mortality. In this study we determine for the first time a combined epigenetic, gene expression, and histology signature that differentiates between patients with different tobacco use history (heavy tobacco use with ≥10 pack years vs. no tobacco use). Using The Cancer Genome Atlas (TCGA) cohort (n = 257) and an internal cohort (n = 40), we identify 3 epigenetic markers (GPR15, GNG12, GDNF) and 13 expression markers (IGHA2, SCG5, RPL3L, NTRK1, CD96, BMP6, TFPI2, EFEMP2, RYR3, DMTN, GPD2, BAALC, and FMO3), which are dysregulated in OSCC patients who were never smokers vs. those who have a ≥ 10 pack year history. While mortality risk prediction based on smoking status and clinicopathologic covariates alone is inaccurate (c-statistic = 0.57), the combined epigenetic/expression and histologic signature has a c-statistic = 0.9409 in predicting 5-year mortality in OSCC patients.

Classification of HER2 status across multiple cancers using epigenomic profiles from a novel liquid biopsy assay.

3047 Background: The efficacy of trastuzumab deruxtecan in multiple cancers led to a recent FDA granting of priority review for the treatment of adults with HER2-positive solid tumors. This underscores the critical need for reliable assessment of HER2 expression across cancers. The current standard using IHC/ISH for HER2 scoring is fraught with challenges including scoring discordance and tumor heterogeneity. Here we describe the ability to classify HER2 status from 1 ml of plasma, using epigenomic signatures from a novel multi-analyte liquid biopsy (LBx) platform, offering a minimally invasive approach for patient (pt) selection across cancers. Methods: We selected 179 samples from 172 pts with advanced breast (BC), gastro-esophageal (GEA) and ovarian (OV) cancers who had associated HER2 status scored from tissue-based IHC/ISH according to ASCO/CAP guidelines (table). Samples were taken at baseline or at progression and those with detectable cell free DNA, as assessed by iChorCNA, were profiled for genome-wide epigenomic signals across histone modifications associated with active enhancers, promoters and DNA methylation. A regularized regression model developed to classify HER2 status in BC cell lines and was refined and validated for HER2 status prediction for each pt cohort (HER2+ = 3+, 2+/ISH+; HER2- = 2+/ISH-, 1+, 0). The BC cell-line derived HER2 classifier was refined to incorporate GEA and OV cancer specific features before being applied to those samples. Performance was assessed via AUC in a leave-one-out cross-validation schema. We also evaluated HER2 status at progression in a subset of pts with benchmarked HER2 IHC to assess dynamic changes in receptor status by LBx. Results: The epigenomic HER2 classifier was applied to all samples with ctDNA detectable by ichorCNA (90 of 179; 50%). HER2 classification of BC pts by epigenomic liquid biopsy was concordant with standard tissue-based IHC for 64/72 (89%) BC samples (AUC 0.9, table). HER2 classifier predictions for all longitudinally collected samples were concordant with IHC-based HER2 status, including the one patient whose status switched from HER2+ to HER2- at progression. Accurate classification of 11/14 (79%, GEA) and 4/4 (100%, OV) pts was achieved using the indication-refined HER2 classifier. Conclusions: We demonstrate proof of concept for a HER2 classification approach using comprehensive epigenomic signals from 1 ml of plasma that could be applied across multiple cancers. With further development, our genome-wide profiling approach could alleviate clinical constraints associated with multiple tissue-based HER2 scoring assays (IHC/ISH) and enable longitudinal monitoring of HER2 status on therapy. [Table: see text]

Epigenomic signatures of sarcomatoid differentiation to guide the treatment of renal cell carcinoma

Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and a heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are the limited understanding of its gene regulatory programs and the low diagnostic yield of tumor biopsies due to spatial heterogeneity. Herein, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries from tissue and plasma samples from 50 patients with RCC and healthy volunteers. By profiling histone modifications and DNA methylation, we identified highly recurrent epigenomic reprogramming enriched in sRCC. Furthermore, CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs, and FOSL1 expression was associated with the response to ICIs in RCC in two randomized clinical trials. Finally, we established a blood-based diagnostic approach using detectable sRCC epigenomic signatures in patient plasma, providing a framework for discovering epigenomic correlates of tumor histology via liquid biopsy.

Liver epigenomic signature associated with chronic oxidative stress in a mouse model of glutathione deficiency

Oxidative stress is intimately involved in the pathogenesis of fatty liver disease (FLD). A major factor contributing to oxidative stress is the depletion of the ubiquitous antioxidant glutathione (GSH). Unexpectedly, chronic GSH deficiency renders glutamate-cysteine ligase modifier subunit (Gclm)-null mice protected from fatty liver injuries. Epigenetic regulation serves as an important cellular mechanism in modulating gene expression and disease outcome in FLD, although it is not well understood how systemic redox imbalance modifies the liver epigenome. In the current study, utilizing the Gclm-null mouse model, we aimed to elucidate redox-associated epigenomic changes and their implications in liver stress response. We performed high-throughput array-based DNA methylation profiling (MeDIP array) in 22,327 gene promoter regions (from −1300 bp to +500 bp of the Transcription Start Sites) in the liver and peripheral blood cells. Results from the MeDIP array demonstrate that, although global methylation enrichment in gene promoters did not change, low GSH resulted in prevalent demethylation at the individual promoter level. Such an effect likely attributed to a declined availability of the methyl donor S-adenosyl methionine (SAM) in Gclm-null liver. Functional enrichment analysis of liver target genes is suggestive of a potential role of epigenetic mechanisms in promoting cellular survival and lipid homeostasis in Gclm-null liver. In comparison with the liver tissue, MeDIP array in peripheral blood cells revealed a panel of 19 gene promoters that are candidate circulating biomarkers for hepatic epigenomic changes associated with chronic GSH deficiency. Collectively, our results provided new insights into the in vivo interplay between liver redox state and DNA methylation status. The current study laid the groundwork for future epigenetic/epigenomic investigations in experimental settings or human populations under conditions of liver oxidative stress induced by environmental or dietary challenges.

Novel epigenomic liquid biopsy assay to predict estrogen receptor (ER) status and to infer ER pathway activation in breast cancer.

1066 Background: Endocrine therapy (ET) is the cornerstone of treatment for ER-positive (ER+) breast cancer (BC). However, BC may lose ER expression over the disease course, and ER+ tumors may become resistant to ET regardless of ER expression. Blood-based biomarkers to infer ER expression and to predict ET sensitivity are lacking. Methods: We identified 44 patients (pts) with metastatic BC seen at Dana-Farber Cancer Institute from 2012-2023, who had blood samples drawn in Streck tubes within 6 weeks of tumor biopsy with ER scored via immunohistochemistry (IHC). We applied a novel, multi-analyte, liquid biopsy assay to capture genome-wide epigenomic signals, mapping enhancers, promoters, and DNA methylation data from 1mL of plasma. First, we applied a previously developed, IHC-benchmarked, regularized logistic regression model to infer ER status from plasma-based epigenomic profiles (Parsons et al., SABCS 2023). Second, we applied a novel ER pathway activity score involving promoters and enhancers of certain genes previously associated with ER activity (Guan et al., Cell 2019). The ER activity score was corrected for the circulating tumor DNA (ctDNA) fraction as assessed by low pass whole genome sequencing (ichorCNA algorithm). We evaluated the association between the ER activity score and the ER status by IHC using the Wilcoxon rank-sum test. ER expression ≥1% was considered positive. Results: The ER classifier and the ER activity score have been applied to 19 of 44 samples (43%) all of which had detectable ctDNA. Eleven out of 19 (58%) pts had ER+ BC by IHC (ER IHC range 80-95%). Overall, 18/19 (95%) were correctly classified as ER+ or ER- by the ER classifier (AUC=1). Three of 19 (16%) samples were collected from pts with ER+ BC at primary diagnosis and ER- BC at time of tissue sampling. For them, the ER classifier correctly predicted ER- status. We observed a significantly higher ER activity score in samples from pts with ER+ BC than pts with ER- BC as measured by IHC (p= 0.0012). For pts with ER+ BC, we observed an association between lower ER activity scores and a higher number of lines of ET prior to blood sampling, with lower scores for pts who received &gt;4 prior lines. We will present full results from this cohort and an expanded cohort and correlate the ER score with response to ET. Conclusions: We applied a novel blood-based epigenomic classifier able to infer ER status and a novel epigenomic activity score to predict ER signaling from a minimal plasma volume. We plan to validate our findings on a larger cohort and correlate with response to ET. If confirmed, this assay may represent a valuable, minimally invasive tool to help guide treatment selection for patients with ER+ BC and predict response to novel endocrine agents.

Dysregulated expression of cholesterol biosynthetic genes in Alzheimer's disease alters epigenomic signatures of hippocampal neurons

Aging is the main risk factor of cognitive neurodegenerative diseases such as Alzheimer's disease, with epigenome alterations as a contributing factor. Here, we compared transcriptomic/epigenomic changes in the hippocampus, modified by aging and by tauopathy, an AD-related feature. We show that the cholesterol biosynthesis pathway is severely impaired in hippocampal neurons of tauopathic but not of aged mice pointing to vulnerability of these neurons in the disease. At the epigenomic level, histone hyperacetylation was observed at neuronal enhancers associated with glutamatergic regulations only in the tauopathy. Lastly, a treatment of tau mice with the CSP-TTK21 epi-drug that restored expression of key cholesterol biosynthesis genes counteracted hyperacetylation at neuronal enhancers and restored object memory. As acetyl-CoA is the primary substrate of both pathways, these data suggest that the rate of the cholesterol biosynthesis in hippocampal neurons may trigger epigenetic-driven changes, that may compromise the functions of hippocampal neurons in pathological conditions.

Minimal Residual Disease using a Plasma-Only Circulating Tumor DNA Assay to Predict Recurrence of Metastatic Colorectal Cancer Following Curative Intent Treatment.

Minimal residual disease (MRD) detection can identify the recurrence in patients with colorectal cancer (CRC) following definitive treatment. We evaluated a plasma-only MRD assay to predict recurrence and survival in patients with metastatic CRC who underwent curative intent procedures (surgery and/or radiotherapy), with or without (neo)adjuvant chemotherapy. The primary objective of this study was to assess the correlation of postprocedure tumor cell-free DNA detection status with radiographic disease recurrence. Preprocedure and postprocedure longitudinal samples were collected from 53 patients and analyzed with a multiomic MRD assay detecting circulating tumor DNA (ctDNA) from genomic and epigenomic signals. Preprocedure and postprocedure ctDNA detection correlated with recurrence-free and overall survival (OS). From 52 patients, 230/233 samples were successfully analyzed. At the time of data cutoff, 36 (69.2%) patients recurred with median follow-up of 31 months. Detectable ctDNA was observed in 19/42 patients (45.2%) with ctDNA analyzed 3 weeks postprocedure. ctDNA detection 3 weeks postprocedure was associated with shorter median recurrence-free survival (RFS; HR, 5.27; 95% CI, 2.31-12.0; P < 0.0001) and OS (HR, 12.83; 95% CI, 3.6-45.9; P < 0.0001). Preprocedure ctDNA detection status was not associated with RFS but was associated with improved OS (HR, 4.65; 95% CI, 1.4-15.2; P = 0.0111). Undetectable ctDNA preprocedure had notable long-term OS, >90% 3 years postprocedure. In this cohort of oligometastatic CRC, detection of ctDNA preprocedure or postprocedure was associated with inferior outcomes even after accounting for known prognostic clinicopathologic variables. This suggests ctDNA may enhance current risk stratification methods helping the evaluation of novel treatments and surveillance strategies toward improving patient outcomes.

Abstract PS06-07: Liquid biopsy determination of HER2 status in breast cancer: results from a novel epigenomic platform

Abstract Background: Tumor HER2 status remains a critical predictive biomarker for patients with breast cancer given the availability of highly effective anti-HER2 therapies. However, determination of HER2 status relies on a complex, tissue-dependent algorithm optimized for extremes of the phenotype – HER2+ vs HER2- status. Given the challenges in reliably obtaining informative tissue biopsies as disease progresses, the new therapeutic relevance of HER2-low breast cancer (IHC 1+ and FISH-negative IHC 2+), and the undependability of biomarkers in this range, better approaches are needed. Epigenomic signatures detectable in cell-free tumor DNA (cfDNA) may provide a minimally invasive, reliable determination of HER2 status. Here, we present a multimodal epigenomic liquid biopsy platform that could offer a minimally invasive alternative to tissue-based determination of transcriptionally regulated targets such as HER2. Methods: We identified patients with metastatic breast cancer (n=20) that were HER2-positive with IHC 3+ (n=6) or HER2-negative with IHC 0 (n=14) based on ASCO/CAP guidelines who underwent research biopsies at the Dana-Farber Cancer Institute from 2012-2023. Study participants had undergone concurrent blood sampling collected in Streck Tubes, processed as plasma, and stored at -80ºC. We applied a novel, multimodal epigenomic assay to profile tumor-derived gene regulatory programs from 1mL plasma. This genome-wide approach analyzed histone modifications associated with active gene promoters and enhancers, and DNA methylation. Classifier feature selection was derived from epigenomically profiled breast cancer cell lines. Final classifier performance was cross validated using a standard Leave one Out (LoO) scheme. Results: Our cross-validated classifier yielded an area under the ROC curve (AUC) of 0.91 in the 20 samples tested. When including only samples with detectable ctDNA as assessed by low pass whole genome sequencing (ichorCNA algorithm) (N=13), our classifier had an AUC of 0.98. Using regularized regression approach, we identified 33 loci with the highest predictive value; 8 loci were within the ERBB2 amplicon on chromosome 17, while the remaining 25 loci were in other genomic regions. We will present results from this and an expanded cohort, including participants with HER2 IHC 1+ and 2+ disease. Conclusions: We present a novel, minimally invasive HER2 classifier leveraging epigenomic information from cell-free tumor DNA from 1 mL plasma. If this approach remains robust in accurately classifying additional HER2 states, it could address the limitations of current tissue-based testing. Integration of this epigenomic platform in prospective interventional studies could support the development of novel and improved predictive classifiers for response to HER2-directed therapy. Citation Format: Heather Parsons, Sylvan Baca, Anthony D'Ippolito, Hyun-Hwan Jeong, Kalie Smith, Paolo Tarantino, Melissa Hughes, Kerry Sendrick, Corrie Painter, Ji-Heui Seo, Elizabeth Grant, Jamey Guess, Matthew Davidsohn, Gitanjali Lakshminarayanan, Sarah Strauss, Hunter Savignano, John Canniff, Brad Fortunato, Matthew Eaton, Toni Choueiri, Sara Tolaney, Matthew Freedman, Nancy Lin. Liquid biopsy determination of HER2 status in breast cancer: results from a novel epigenomic platform [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS06-07.

Abstract PS06-06: Analysis of ctDNA for the detection of minimal residual disease (MRD) using a tissue-free, multiomic assay in patients with early-stage breast cancer

Abstract Background: The detection of ctDNA in patients with early-stage breast cancer after completion of adjuvant therapy is associated with a high risk of recurrence. Current clinical guidelines do not recommend routine screening for metastatic disease unless there are clinical signs and symptoms in patients who completed adjuvant therapy. However, ctDNA may serve as an early biomarker of recurrence which may allow effective identification of patients with asymptomatic distant metastases or molecular relapse only, who could benefit from early treatment intervention. Herein, we utilized a tissue-free, multiomic assay for the sensitive and specific detection of MRD in patients with early-stage breast cancer. Methods: Plasma samples were collected from patients with stage I-III breast cancer who were enrolled in the SUCCESS-A phase 3 clinical trial (NCT02181101) between 2006 and 2007. All patients received adjuvant chemotherapy +/- endocrine therapy and/or anti-HER2 therapy. Samples were collected approximately two years after completion of adjuvant chemotherapy, and plasma samples selected for analysis were from patients without evidence of disease recurrence prior to sample collection. Presence of MRD was assessed using Guardant Reveal powered by Infinity, which evaluates the epigenomic signals associated with cancer versus normal DNA for the detection of ctDNA. Samples with the presence of ctDNA are characterized for somatic alterations with common sources of interference such as clonal hematopoiesis excluded. An analytically validated bioinformatics pipeline was used for the detection of breast cancer ctDNA. Samples were analyzed blinded to the clinical data. Median survival times were estimated using the Kaplan-Meier method and hazard ratios were calculated based on univariable cox regression models. Results: A total of 311 plasma samples from 311 patients were evaluable. ctDNA was detected in 34% (13/38) of patients who subsequently developed distant recurrence and in none (0/7) of the patients who had local or contralateral breast cancer recurrence. ctDNA was detected in 60% (9/15) of samples that were collected within one year before recurrence. In the ctDNA detected samples from patients who had disease recurrence, the median time from sample collection to recurrence was 7.9 months (range, 1.4-28.6 months). ctDNA was detected in 6 patients who did not have a documented disease recurrence, resulting in a specificity of 97.7% (260/266). In the overall cohort, ctDNA detection was prognostic for recurrence-free survival (RFS; HR 11.0, 95% CI 2.28-53.6; p&amp;lt; 0.0001), distant recurrence-free survival (D-RFS; HR 13.7, 95% CI 2.52-74.9; p&amp;lt; 0.0001), and overall survival (OS; HR 17.4, 95% CI 1.33-227; p&amp;lt; 0.0001). Conclusion: Detection of ctDNA after adjuvant chemotherapy was highly prognostic and demonstrated high specificity in an early-stage breast cancer cohort. Larger, prospective studies are needed to confirm the prognostic value of ctDNA in the post-treatment setting and assess the clinical utility of MRD detection in this population. Citation Format: Wolfgang Janni, Thomas Friedl, Brigitte Rack, Peter A. Fasching, Andreas Hartkopf, Hans Tesch, Ralf Lorenz, Georg Heinrich, Jens-Uwe Blohmer, Tanja Fehm, Volkmar Müller, Andreas Schneeweiss, Matthias Beckmann, Matthias Ruebner, Nadia Harbeck, Klaus Pantel, Derek Dustin, Mingyang Cai. Analysis of ctDNA for the detection of minimal residual disease (MRD) using a tissue-free, multiomic assay in patients with early-stage breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS06-06.

Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures

Regular exercise has many physical and brain health benefits, yet the molecular mechanisms mediating exercise effects across tissues remain poorly understood. Here we analyzed 400 high-quality DNA methylation, ATAC-seq, and RNA-seq datasets from eight tissues from control and endurance exercise-trained (EET) rats. Integration of baseline datasets mapped the gene location dependence of epigenetic control features and identified differing regulatory landscapes in each tissue. The transcriptional responses to 8weeks of EET showed little overlap across tissues and predominantly comprised tissue-type enriched genes. We identified sex differences in the transcriptomic and epigenomic changes induced by EET. However, the sex-biased gene responses were linked to shared signaling pathways. We found that many G protein-coupled receptor-encoding genes are regulated by EET, suggesting a role for these receptors in mediating the molecular adaptations to training across tissues. Our findings provide new insights into the mechanisms underlying EET-induced health benefits across organs.

Machine learning identifies activation of RUNX/AP-1 as drivers of mesenchymal and fibrotic regulatory programs in gastric cancer.

Gastric cancer (GC) is the fifth most common cancer worldwide and is a heterogeneous disease. Among GC subtypes, the mesenchymal phenotype (Mes-like) is more invasive than the epithelial phenotype (Epi-like). Although gene expression of the epithelial-to-mesenchymal transition (EMT) has been studied, the regulatory landscape shaping this process is not fully understood. Here we use ATAC-seq and RNA-seq data from a compendium of GC cell lines and primary tumors to detect drivers of regulatory state changes and their transcriptional responses. Using the ATAC-seq data, we developed a machine learning approach to determine the transcription factors (TFs) regulating the subtypes of GC. We identified TFs driving the mesenchymal (RUNX2, ZEB1, SNAI2, AP-1 dimer) and the epithelial (GATA4, GATA6, KLF5, HNF4A, FOXA2, GRHL2) states in GC. We identified DNA copy number alterations associated with dysregulation of these TFs, specifically deletion of GATA4 and amplification of MAPK9 Comparisons with bulk and single-cell RNA-seq data sets identified activation toward fibroblast-like epigenomic and expression signatures in Mes-like GC. The activation of this mesenchymal fibrotic program is associated with differentially accessible DNA cis-regulatory elements flanking upregulated mesenchymal genes. These findings establish a map of TF activity in GC and highlight the role of copy number driven alterations in shaping epigenomic regulatory programs as potential drivers of GC heterogeneity and progression.