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PubMed2026

CAR-T Cell Therapy: Manufacturing Platforms and Clinical Consequences.

Chimeric antigen receptor (CAR) T-cell therapy has transformed hematological cancer care, yet variability in efficacy, durability, and safety cannot be explained solely by antigen selection or patient factors. We propose that manufacturing platforms are active biological determinants of outcome. Viral vectors, used in all licensed products, provide stable genomic integration and durable expression but are limited by cost, cargo capacity, and centralized production. Nonviral strategies, including transposons, CRISPR knock-ins, and messenger RNA delivery, enable faster, less-expensive manufacturing with larger payloads, while introducing distinct safety and persistence profiles. This review presents a three-layer mechanistic framework that reframes manufacturing as biology: integration biology determines genomic risk and transgene stability; clonal fitness shapes persistence, dominance, and exhaustion; and epigenomic imprinting, influenced by gene transfer method, cytokines, and culture stress, preconfigures functional trajectories. Clinical observations link platform choice to immune recovery, where prolonged B-cell aplasia and delayed T-cell reconstitution contribute to infection-related nonrelapse mortality, and hematopoietic reserve at apheresis emerges as a practical predictor. Finally, manufacturing is positioned as the key to democratizing cell therapy. Decentralized, nonviral production aligned with regulatory standards may enable equitable access and transition CAR-T therapy from innovation to sustainable global care.

Humans↗

PubMed2023

CasKAS: direct profiling of genome-wide dCas9 and Cas9 specificity using ssDNA mapping.

Detecting and mitigating off-target activity is critical to the practical application of CRISPR-mediated genome and epigenome editing. While numerous methods have been developed to map Cas9 binding specificity genome-wide, they are generally time-consuming and/or expensive, and not applicable to catalytically dead CRISPR enzymes. We have developed CasKAS, a rapid, inexpensive, and facile assay for identifying off-target CRISPR enzyme binding and cleavage by chemically mapping the unwound single-stranded DNA structures formed upon binding of a sgRNA-loaded Cas9 protein. We demonstrate this method in both in vitro and in vivo contexts.

CRISPR-Cas Systems↗

PubMed2025

Multi-omics signature of healthy versus unhealthy lifestyles reveals associations with diseases.

This multi-omics cross-sectional study investigated differences in metabolomics, proteomics, and epigenomics profiles between two groups of adults matched for age but differing in lifestyle factors such as body composition, diet, and physical activity patterns. Data from prior studies were utilized for a comprehensive integrative analysis. The study included 52 participants in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females). Using multi-omics integration software (OmicsNet and Pathview), 96 significantly (p < 0.05) enriched pathways were identified that differentiated the LIFE and CON groups. Top pathways significantly (p < 2.63 × 10-5) influenced by group status included fatty acid degradation, fatty acid elongation, glutathione metabolism, Parkinson disease, and central carbon metabolism in cancer. This study identified a distinct metabolic signature comprised of metabolites, proteins, and gene methylation sites associated with a healthy lifestyle. These findings provide unique, but complementary, results to previous single-omics analyses using metabolomics and proteomics procedures which showed that the LIFE group exhibited lower plasma bile acid levels, higher levels of beneficial fatty acids, reduced innate immune activation, enhanced lipoprotein metabolism, and increased HDL remodeling. The current multi-omics analysis builds on these previous results by providing a more holistic view of how metabolites, proteins, and methylation sites associated with a healthy lifestyle, providing a larger, more comprehensive list of altered pathways. Additionally, the integrated analysis revealed connections between lifestyle factors and conditions such as cancer and insulin resistance beyond what identified in the single-omics approaches, highlighting the broader metabolic impact of lifestyle on health. Overall, the signatures identified by this multi-omics approach provide a basis for developing more translational biomarkers, such as those that defined the cancer and insulin resistance pathways that can be used to assess one's state of health and provide guidance on behavior modifications that should be taken to lower disease risk.

Humans↗

PubMed2026

EWAS in a polyphenol dense, DNA methylation-targeted, controlled diet and lifestyle study.

BACKGROUND: Dietary and lifestyle factors can influence DNA methylation patterns. We previously reported epigenetic age attenuation following a controlled study using an 8-week polyphenol-dense, DNA methylation-targeted diet and lifestyle intervention in healthy males (Methylation Diet and Lifestyle Study), with phytonutrient/polyphenol-rich foods (green tea, oolong tea, curcumin, garlic, and berries) being most predictive of this effect. METHODS: Here we conducted an epigenome-wide association study (EWAS) in 38 participants from the Methylation Diet and Lifestyle Study. The intervention included a dietary pattern intentionally rich in substrate and cofactor nutrients for methylation pathways, and components known to alter DNA-methyltransferase (DNMT) enzyme activity. In line with prior EWAS studies with small sample sizes where FDR-significant findings are unlikely, we used pre-specified nominal P-value thresholds (0.001, 0.0001) for the exploratory analyses. RESULTS: At P < 0.001 (unadjusted), 676 differentially methylated loci (DML) were identified in the intervention group versus 286 in controls. At P < 0.0001 (unadjusted), 50 DML were identified in the intervention group compared to 13 in controls. Fifteen DML were in transcription start site-proximal regions of genes including those involved in zinc homeostasis and nutrient sensing, development and pluripotency, proteostasis and genome stability, tumor suppression, and synaptic function. A group-by-time interaction analysis identified 70 intervention-specific DML at P < 0.0001, with nominal enrichment including autophagy, mTOR signaling, and chromatin remodeling pathways. A regional DMR analysis identified 128 within-group and 129 interaction-specific DMRs. DMR functional enrichment analyses revealed convergent nominal associations with lipid metabolism (alpha-linolenic acid, lipoic acid, biosynthesis of unsaturated fatty acids, PPAR signaling, cholesterol homeostasis), central energy metabolism (TCA cycle, glycolysis/gluconeogenesis, pentose phosphate, pyruvate), and nutrient sensing (PI3K-Akt, mTOR, AMPK, autophagy as well as other pathways). As expected for the limited cohort size and short intervention duration, none of the single CpG findings or enrichment analyses survived multiple test correction and are therefore considered exploratory and hypothesis-generating only. CONCLUSION: This EWAS identified a larger number of nominally changing CpGs in the intervention group compared to controls as well as biologically coherent methylation changes. These findings provide mechanistic hypotheses for previously observed epigenetic age attenuation. Replication in larger cohorts, longer intervention durations, and functional validation remain essential.

DNA methylation↗

PubMed2026

Accurately Deciphering Tissue Heterogeneity From Spatial Multi-Modal and Multi-Omics With STransformer.

Advances in spatially resolved technologies enable the simultaneous acquisition of diverse data modalities within a tissue slice while preserving critical spatial context, which presents unprecedented opportunities to decipher intricate tissue heterogeneity. However, existing computational approaches lack the intrinsic flexibility to universally process both spatial multi-modal and multi-omics data. Here, we introduce STransformer, a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short-range cellular interactions and tissue-wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity. Systematic evaluations across diverse species, tissue types, and data modalities highlight its profound versatility. For spatial multi-modal data, STransformer delineates intricate anatomical structures in the human cortex, uncovers pathological mechanisms in Alzheimer's disease, and characterizes dynamic spatiotemporal developmental trajectories during chicken cardiogenesis. Scaling to spatial multi-omics data, STransformer synergizes spatial transcriptomic and proteomic profiles to decipher intricate immune microenvironments within the human tonsil, and jointly analyzes spatial epigenomic and transcriptomic data to infer regulatory mechanisms in the mouse embryonic brain. Consequently, STransformer serves as a highly versatile and robust analytical framework for advancing our understanding of tissue heterogeneity and disease pathogenesis.

Multiomics↗

PubMed2026

Livestock Multi-Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation.

Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This review traces the progression from single-omics accumulation to multi-dimensional integration, highlighting how large-scale genomic, epigenomic, and transcriptomic projects lay the foundation for functional dissection. We identify core impediments: extreme species diversity, marked data heterogeneity, limited sample sizes, and a pervasive reduction of multi-omics data to simplistic differential screens, resulting in low translational efficiency. We critically appraise four common pitfalls-overinterpreting correlation as causation, relegating proteomics to corroborating transcriptomics, incomplete microbiome-host integration lacking environmental context, and systematic neglect of metabolic fluxomics-and show how exposomics and fluxomics add necessary causal and dynamic dimensions. To address these, we propose a livestock-adapted three-tier analytical framework: (1) statistical association of cross-omics covariation patterns; (2) machine learning-driven feature mining and integrative modeling; and (3) causal interpretation encompassing Mendelian randomization, prior-knowledge-guided network inference, and physical causal evidence via fluxomics and metabolic control analysis. We further discuss how multimodal sequencing (single-cell, spatial, temporal) and generative AI can fundamentally mitigate heterogeneity and strengthen causal evidence. Finally, we outline future priorities in database standardization, livestock-specific benchmarking, and translational pipelines, charting a path from correlation-centric reporting to mechanistic causality and precision breeding.

Animals↗

PubMed2024

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort.

OBJECTIVE: Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout. METHODS: We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1. RESULTS: In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation. CONCLUSION: This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

Humans↗

PubMed2026

Multi-Omics Biomarker Signatures for Precision Diagnosis and Prognosis in Primary Liver Cancer: A Literature Review.

Primary liver cancer (PLC) is a biologically heterogeneous group of malignancies dominated by hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and a smaller subset of combined hepatocellular-cholangiocarcinoma (cHCC-CCA), and its clinical burden remains high because current diagnostic and prognostic tools do not adequately capture molecular diversity. Conventional imaging, serum markers, and histopathological assessment remain insufficient for precise early diagnosis, subtype-resolved classification, and outcome stratification, while tissue and liquid biopsy approaches have expanded the range of analytes available for clinical assessment. Recent studies have identified candidate biomarker signatures across genomic, epigenomic, transcriptomic, proteomic, metabolomic, and circulating layers, suggesting that integrated multi-omics profiling may better represent tumor lineage, clonal evolution, immune context, and therapeutic vulnerability than isolated molecular readouts. However, these layers are not equally mature for clinical use: genomic testing is closest to routine therapeutic application in iCCA, plasma methylation assays are advancing for HCC surveillance augmentation, and many proteomic or metabolomic panels remain validation-stage tools. Their clinical value remains constrained by sampling bias, biospecimen-dependent signal loss, assay standardization, cost, and the need for prospective validation across clinically diverse populations. This narrative review critically synthesizes current evidence on multi-omics biomarker signatures for precision diagnosis and prognosis in primary liver cancer and argues that clinically useful signatures should be question-specific, stage-aware, and specimen-aware rather than universal multi-analyte panels.

Humans↗

PubMed2026

Exploratory single-nucleus multiomics analysis of myeloid cell states associated with neoadjuvant chemotherapy response in pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) continues to be one of the most lethal human malignancies, with the vast majority of patients ineligible for immunotherapy. Tumour-associated macrophages (TAMs) are key regulators of the PDAC tumour microenvironment (TME), yet their transcriptional and epigenomic heterogeneity in the context of chemotherapy response is poorly understood. Therefore, we performed an exploratory single nucleus multiomics analysis of PDAC tumors stratified by histopathologic response to neoadjuvant chemotherapy. METHODS: Surgical resection specimens from PDAC patients were classified as responders or non-responders using the American College of Pathologists (CAP) histopathologic criteria. Frozen tissue underwent simultaneous snRNA-seq and snATAC-seq on the 10x Genomics Chromium Single Cell Multiome platform, followed by downstream analyses such as differential gene expression, GO and hallmark pathway enrichment, pseudotime trajectory inference and ChromVAR transcription factor motif analysis. RESULTS: Multiomics profiling of 30 840 high-quality nuclei revealed a myeloid compartment that differed in composition and transcriptional state between CAP-defined responders and non-responders in this small cohort. We observed a trend toward higher LAM-like state proportions in the responders than non-responders (38.4% vs. 26.7%), although this disparity did not achieve statistical significance. The transcriptional programs of the responder myeloid cells are associated with phagocytosis and lipid handling. Chromatin accessibility analysis further suggested candidate response-associated transcription factor motif accessibility patterns. CONCLUSIONS: Neoadjuvant-treated PDAC tumours from CAP-defined responders in this cohort myeloid landscape with apparent enrichment of LAM-like states and immune-activating transcriptional/epigenetic programs. However, these findings are preliminary and hypothesis-generating because of the small cohort size, heterogeneous treatment regimens, absence of matched pre-treatment biopsies, and lack of knockout validation. Larger treatment cohorts and functional/mechanistic studies are needed to determine whether LAM-like myeloid programs contribute to chemotherapy response or reflect a consequence of chemotherapy treatment.

Humans↗

PubMed2007

Inhibitors of histone deacetylases as potential therapeutic tools for high-risk embryonal tumors of the nervous system of childhood.

The origin of malignant embryonal tumors is incompletely understood and certain risk groups remain difficult to treat. The epigenetic structure of DNA and its lesions play a role in the origin of these neoplasms. Manipulation of the epigenome may offer novel treatment options. The authors evaluated the cytotoxicity of histone deacetylase inhibitors (HDI) [MS-275, SAHA, TSA, M344, M360, D85, SW55, SW187 and valproic acid (VPA)] on 13 embryonal tumor cell lines [4 medulloblastomas, 5 neuroblastomas, 2 atypical teratoid/rhabdoid tumors (AT/RT), and 2 malignant rhabdoid tumors of the kidney (RTK)] in MTT assay. In addition, HDI effects on hyperacetylation, reexpression of growth regulatory genes and apoptosis were characterized by Western analysis, RT-PCR and annexin-V staining. All HDI inhibited cell proliferation in a time- and dose-dependent manner. VPA was least cytotoxic with GI50 values after 72 hr ranging from 53.6 to 332.9 microM, while TSA was most efficient with GI50 values after 72 hr ranging from 0.01 to 8.8 microM. M344 and M360 were also highly effective. Western blot revealed hyperacetylation of histone H4 after HDI treatment. Reactivation of several genes including the proapoptotic CASP8 was identified by RT-PCR. Annexin-V staining demonstrated a dose and time dependent induction of apoptosis. HDI inhibited the growth of medulloblastoma, neuroblastoma and rhabdoid tumors in vitro. Treatment with HDI induced the reactivation of growth regulatory genes and consequently apoptosis. Our results warrant further studies and may help in the design of new protocols geared at the treatment of high risk embryonal tumors.

Acetylation↗

PubMed2003

Chromatin remodeling as a guide to transcriptional regulatory networks in mammals.

An important challenge of genome biology is a dissection of transcriptional regulatory networks that operate inside the nucleus during ontogeny and disease (Wyrick and Young [2002] Curr. Opin. Genet. Dev. 12:130). Limitations of existing experimental tools greatly complicate such analysis in the human genome: for example, genome-wide expression profiling of cells responding to a stimulus fails to reveal a majority of the genes involved in the functional network of responding to that stimulus [Giaver et al., 2002; Birrell et al., 2002]. This article discusses recent advances in analyzing mammalian transcriptional regulatory circuits [Nikiforov et al., 2002; Weinmann et al., 2002; Ren et al., 2000]. As evidenced by these and other data, paucity of information about the location of regulatory DNA elements in the human genome presents an obstacle to comprehensive transcription network analysis. It has been known since the late 1970s that chromatin over active regulatory DNA stretches is stably remodeled into "nuclease hypersensitive sites" [Elgin, 1988; Gross and Garrard 1988]. Massively parallel analysis of such remodeling in cell nuclei identifies regulatory DNA that is difficult to map comprehensively using other approaches, reveals genes poised for rapid activation, and offers a novel perspective on the "epigenome"--the regulatory program being executed by the genome in a given cell type.

Animals↗

PubMed2024

The effect of low birth weight as an intrauterine exposure on the early onset of sarcopenia through possible molecular pathways.

Sarcopenia, a musculoskeletal disease characterized by the progressive loss of skeletal muscle mass, strength, and physical performance, presents significant challenges to global public health due to its adverse effects on mobility, morbidity, mortality, and healthcare costs. This comprehensive review explores the intricate connections between sarcopenia and low birth weight (LBW), emphasizing the developmental origins of health and disease (DOHaD) hypothesis, inflammatory processes (inflammaging), mitochondrial dysfunction, circadian rhythm disruptions, epigenetic mechanisms, and genetic variations revealed through genome-wide studies (GWAS). A systematic search strategy was developed using PubMed to identify relevant English-language publications on sarcopenia, LBW, DOHaD, inflammaging, mitochondrial dysfunction, circadian disruption, epigenetic mechanisms, and GWAS. The publications consist of 46.2% reviews, 21.2% cohort studies, 4.8% systematic reviews, 1.9% cross-sectional studies, 13.4% animal studies, 4.8% genome-wide studies, 5.8% epigenome-wide studies, and 1.9% book chapters. The review identified key factors contributing to sarcopenia development, including the DOHaD hypothesis, LBW impact on muscle mass, inflammaging, mitochondrial dysfunction, the influence of clock genes, the role of epigenetic mechanisms, and genetic variations revealed through GWAS. The DOHaD theory suggests that LBW induces epigenetic alterations during foetal development, impacting long-term health outcomes, including the early onset of sarcopenia. LBW correlates with reduced muscle mass, grip strength, and lean body mass in adulthood, increasing the risk of sarcopenia. Chronic inflammation (inflammaging) and mitochondrial dysfunction contribute to sarcopenia, with LBW linked to increased oxidative stress and dysfunction. Disrupted circadian rhythms, regulated by genes such as BMAL1 and CLOCK, are associated with both LBW and sarcopenia, impacting lipid metabolism, muscle mass, and the ageing process. Early-life exposures, including LBW, induce epigenetic modifications like DNA methylation (DNAm) and histone changes, playing a pivotal role in sarcopenia development. Genome-wide studies have identified candidate genes and variants associated with lean body mass, muscle weakness, and sarcopenia, providing insights into genetic factors contributing to the disorder. LBW emerges as a potential early predictor of sarcopenia development, reflecting the impact of intrauterine exposures on long-term health outcomes. Understanding the complex interplay between LBW with inflammaging, mitochondrial dysfunction, circadian disruption, and epigenetic factors is essential for elucidating the pathogenesis of sarcopenia and developing targeted interventions. Future research on GWAS and the underlying mechanisms of LBW-associated sarcopenia is warranted to inform preventive strategies and improve public health outcomes.

Humans↗

PubMed2026

Maternal Chrono-Nutrition and Placental DNA Methylation: The BiSC Study.

The impact of diet during pregnancy on birth outcomes and child health is well established, and epigenetic changes may be one mechanism underlying such associations, but the role of meal timing (chrono-nutrition) is unclear. We conducted an epigenome-wide association study (EWAS) of maternal meal timing and placental DNAm (plaDNAm). Data came from 389 pregnant women in the Barcelona Life Study Cohort (BiSC). Chrono-nutrition and dietary data were collected at 20 weeks of pregnancy, and plaDNAm at delivery was characterized using the Illumina EPIC array. Linear robust regression models tested associations between five chrono-nutritional behaviors (time of first and last meal, nighttime fasting duration, number of eating occasions, and eating jetlag) and plaDNAm. We identified 7 CpGs significantly associated with time of last meal (Bonferroni p < 1E-08) and 63 suggestive CpGs (p < 1E-05). Hits included cg13147785 (E2F8), linked to placental cell cycle regulation, cg17665505 (DAP) and cg18303215 (ABCG5), associated with smoking and lung diseases in adults. To conclude, maternal chrono-nutrition was associated with some CpGs in the placenta, particularly time of last meal. Further studies are needed to clarify how meal timing may influence fetal development and long-term health through epigenetic mechanisms.

Humans↗

PubMed2006

Dual inheritance.

Genetic inheritance in higher organisms normally refers to the transmission of information from one generation to the next. Nevertheless, there is also inheritance in somatic cells, characterised by the phenotypic stability of differentiated cells that divide (such as fibroblasts and lymphocytes), and also mitosis of stem line cells, which gives rise to another stem line daughter cell, and one that will differentiate. Thus, there is a dual inheritance systems in these organisms, one of which is genetic and the other epigenetic. In the latter, heritable information is superimposed on DNA sequences, and one well-known mechanism is heritable methylation of cytosine. Much information will come from the human epigenome project that will reveal the patterns of DNA methylation in distinct differentiated cells. There have also been innumerable studies on the abnormal de novo methylation and silencing of tumour suppressor genes in cancer cells.

Animals↗

PubMed2006

Germline recruitment in mice: a genetic program for epigenetic reprogramming.

Germ cells provide an enduring link between generations and therefore must possess the fundamental ability of reprogramming their genome to generate a totipotent state. We wish to understand the molecular basis of the unique properties of the mammalian germ line. Recently we identified Blimp1, a potent transcriptional repressor of a histone methyltransferase subfamily, as a critical determinant of the germ cell lineage in mice. Surprisingly, Blimp1 expression marks the origin of the germ line in proximal epiblast cells in pregastrulation embryos, substantially earlier than previously thought. Furthermore, we showed that established primordial germ cells undergo extensive erasure of genome-wide histone H3 lysine 9 dimethylation (H3K9me2) and DNA methylation, two major repressive epigenetic modifications, and instead acquire high levels of H3-K27 trimethylation (H3K27me3) in their migration period. We suggest that germline specification is a genetic system for the orderly reprogramming of the cells' epigenome toward a totipotent state, with reacquisition of totipotency-associated transcription factors and continued Blimp1 expression preventing their reversion to an explicit pluripotent state or somatic differentiation.

Animals↗

PubMed2026

Esketamine multi-omic biomarker evaluation in major depressive disorder (EMBER-MDD): concept, objectives and methodologies of a non-clinical investigator-initiated study.

Treatment resistance (TR) in major depressive disorder (MDD) affects a substantial minority of patients and is hard to recognize early, delaying intensified care. The Esketamine multi-omic biomarker evaluation in MDD (EMBER-MDD) is a non-interventional, investigator-initiated, in-vitro study within the EU Psych-STRATA programme, analyzing biospecimens collected in the randomized INTENSIFY study and the mirror OBS-TR cohort after participants complete treatment. EMBER-MDD aims to discover individual-omic and integrated multi-omic (hypothesis-free) biomarkers and signatures associated with TR risk, and molecular correlates of clinical response to esketamine nasal spray versus treatment as usual (TAU). Biomaterials will derive from approximately 420 adults with MDD (estimated n = 210 esketamine; n = 210 TAU) and include whole blood, RNA-stabilized whole blood, plasma and serum, sampled at baseline and, when feasible, during and after treatment (up to ~ 5,040 aliquots stored at - 80 °C). Genomics will use baseline DNA genotyping on Illumina Infinium GSA v3.0+MD arrays; epigenomics will profile genome-wide DNA methylation across time points using MethylationEPIC v2.0; transcriptomics will employ mRNA-seq (NovaSeq X/ X Plus); and proteomics/ metabolomics will be generated using high-throughput Olink and/ or Biocrates platforms. Each layer will undergo state-of-the-art preprocessing and analyses (e.g., GWAS/ PRS, EWAS, differential expression, WGCNA, pathway and network analyses), followed by integrative strategies including QTL mapping (meQTL/ eQTL/ pQTL/ mQTL) and intermediate-fusion machine learning with nested cross-validation, explainable AI (SHAP/ LIME) and treatment-effect modelling. All outputs are research-only and will not support individual efficacy, tolerability, or clinical decision-making. The study will deliver robust biosignatures and mechanistic hypotheses to guide future validation and inform stratified, molecularly guided intervention strategies in subsequent prospective trials. Trial registration number: 2023-506617-21-00 and 2025-178-f-S.

Humans↗

PubMed2026

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS] ≥ 0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (≥ 0.3 to < 0.84) and only 3.2% remained completely unclassifiable (CS < 0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors↗

PubMed2006

High-resolution mapping of DNA methylation in human genome using oligonucleotide tiling array.

DNA methylation is an epigenetic mark crucial in regulation of gene expression. Aberrant DNA methylation causes silencing of tumor suppressor genes and promotes chromosomal instability in human cancers. Most of previous studies for DNA methylation have focused on limited genomic regions, such as selected genes or promoter CpG islands (CGIs) containing recognition sites of methylation-sensitive restriction enzymes. Here, we describe a method for high-resolution analysis of DNA methylation using oligonucleotide tiling arrays. The input material is methylated DNA immunoprecipitated with anti-methylcytosine antibodies. We examined the ENCODE region ( approximately 1% of human genome) in three human colorectal cancer cell lines and identified over 700 candidate methylated sites (CMS), where 24 of 25 CMS selected randomly were subsequently verified by bisulfite sequencing. CMS were enriched in the 5' regulatory regions and the 3' regions of genes. We also compared DNA methylation patterns with histone H3 and H4 acetylation patterns in the HOXA cluster region. Our analysis revealed no acetylated histones in the hypermethylated region, demonstrating reciprocal relationship between DNA methylation and histone H3 and H4 acetylation. Our method recognizes DNA methylation with little bias by genomic location and, therefore, is useful for comprehensive high-resolution analysis of DNA methylation providing new findings in the epigenomics.

Acetylation↗