ABSTRACT
Multi-omics (genomics, transcriptomics, epigenomics, proteomics, metabolomics, etc.) research approaches are vital for understanding the hierarchical complexity of human biology and have proven to be extremely valuable in cancer research and precision medicine. Emerging scientific advances in recent years have made high-throughput genome-wide sequencing a central focus in molecular research by allowing for the collective analysis of various kinds of molecular biological data from different types of specimens in a single tissue or even at the level of a single cell. Additionally, with the help of improved computational resources and data mining, researchers are able to integrate data from different multi-omics regimes to identify new prognostic, diagnostic, or predictive biomarkers, uncover novel therapeutic targets, and develop more personalized treatment protocols for patients. For the research community to parse the scientifically and clinically meaningful information out of all the biological data being generated each day more efficiently with less wasted resources, being familiar with and comfortable using advanced analytical tools, such as Google Cloud Platform becomes imperative. This project is an interdisciplinary, cross-organizational effort to provide a guided learning module for integrating transcriptomics and epigenetics data analysis protocols into a comprehensive analysis pipeline for users to implement in their own work, utilizing the cloud computing infrastructure on Google Cloud. The learning module consists of three submodules that guide the user through tutorial examples that illustrate the analysis of RNA-sequence and Reduced-Representation Bisulfite Sequencing data. The examples are in the form of breast cancer case studies, and the data sets were procured from the public repository Gene Expression Omnibus. The first submodule is devoted to transcriptomics analysis with the RNA sequencing data, the second submodule focuses on epigenetics analysis using the DNA methylation data, and the third submodule integrates the two methods for a deeper biological understanding. The modules begin with data collection and preprocessing, with further downstream analysis performed in a Vertex AI Jupyter notebook instance with an R kernel. Analysis results are returned to Google Cloud buckets for storage and visualization, removing the computational strain from local resources. The final product is a start-to-finish tutorial for the researchers with limited experience in multi-omics to integrate transcriptomics and epigenetics data analysis into a comprehensive pipeline to perform their own biological research.This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [16] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.
Subject(s)
Cloud Computing , Epigenomics , Humans , Epigenomics/methods , Epigenesis, Genetic , Transcriptome , Computational Biology/methods , Gene Expression Profiling/methods , Software , Data Mining/methodsABSTRACT
Inflammatory bowel disease (IBD) represents heterogeneous and relapsing intestinal conditions with a severe impact on the quality of life of individuals and a continuously increasing prevalence. In recent years, the development of sequencing technology has provided new means of exploring the complex pathogenesis of IBD. An ideal solution is represented by the approach of precision medicine that investigates multiple cellular and molecular interactions, which are tools that perform a holistic, systematic, and impartial analysis of the genomic, transcriptomic, proteomic, metabolomic, and microbiomics sets. Hence, it has led to the orientation of current research towards the identification of new biomarkers that could be successfully used in the management of IBD patients. Multi-omics explores the dimension of variation in the characteristics of these diseases, offering the advantage of understanding the cellular and molecular mechanisms that affect intestinal homeostasis for a much better prediction of disease development and choice of treatment. This review focuses on the progress made in the field of prognostic and predictive biomarkers, highlighting the limitations, challenges, and also the opportunities associated with the application of genomics and epigenomics technologies in clinical practice.
Subject(s)
Biomarkers , Epigenesis, Genetic , Inflammatory Bowel Diseases , Humans , Inflammatory Bowel Diseases/genetics , Inflammatory Bowel Diseases/metabolism , Prognosis , Epigenomics/methods , Genomics/methods , Genetic Predisposition to DiseaseABSTRACT
Alcelaphine gammaherpesvirus 1 (AlHV-1) asymptomatically persists in its natural host, the wildebeest. However, cross-species transmission to cattle results in the induction of an acute and lethal peripheral T cell lymphoma-like disease (PTCL), named malignant catarrhal fever (MCF). Our previous findings demonstrated an essential role for viral genome maintenance in infected CD8+ T lymphocytes but the exact mechanism(s) leading to lymphoproliferation and MCF remained unknown. To decipher how AlHV-1 dysregulates T lymphocytes, we first examined the global phenotypic changes in circulating CD8+ T cells after experimental infection of calves. T cell receptor repertoire together with transcriptomics and epigenomics analyses demonstrated an oligoclonal expansion of infected CD8+ T cells displaying effector and exhaustion gene signatures, including GZMA, GNLY, PD-1, and TOX2 expression. Then, among viral genes expressed in infected CD8+ T cells, we uncovered A10 that encodes a transmembrane signaling protein displaying multiple tyrosine residues, with predicted ITAM and SH3 motifs. Impaired A10 expression did not affect AlHV-1 replication in vitro but rendered AlHV-1 unable to induce MCF. Furthermore, A10 was phosphorylated in T lymphocytes in vitro and affected T cell signaling. Finally, while AlHV-1 mutants expressing mutated forms of A10 devoid of ITAM or SH3 motifs (or both) were able to induce MCF, a recombinant virus expressing a mutated form of A10 unable to phosphorylate its tyrosine residues resulted in the lack of MCF and protected against a wild-type virus challenge. Thus, we could characterize the nature of this γ-herpesvirus-induced PTCL-like disease and identify an essential mechanism explaining its development.
Subject(s)
CD8-Positive T-Lymphocytes , Gammaherpesvirinae , Animals , CD8-Positive T-Lymphocytes/immunology , Gammaherpesvirinae/genetics , Gammaherpesvirinae/immunology , Cattle , Malignant Catarrh/virology , Malignant Catarrh/immunology , Herpesviridae Infections/immunology , Herpesviridae Infections/virologyABSTRACT
PROBLEM: Preeclampsia (PE) and fetal growth restriction (FGR) are often associated with maternal inflammation and an increased risk of cardiovascular and metabolic disease in the affected mothers. The mechanism responsible for this increased risk of subsequent disease may involve reprogramming of innate immune cells, characterized by epigenetic modifications. METHOD OF STUDY: Circulating monocytes from women with PE, FGR, or uncomplicated pregnancies (control) were isolated before labor. Cytokine release from monocytes following exposure to lipopolysaccharide (LPS) and the presence of lysine 4-trimethylated histone 3 (H3K4me3) within TNF promoter sequences were evaluated. Single-cell transcriptomic profiles of circulating monocytes from women with PE or uncomplicated pregnancies were assessed. RESULTS: Monocytes from women with PE or FGR exhibited increased IL-10 secretion and decreased IL-1ß and GM-CSF secretion in response to LPS. While TNFα secretion was not significantly different in cultures of control monocytes versus those from complicated pregnancies with or without LPS exposure, monocytes from complicated pregnancies had significantly decreased levels of H3K4me3 associated with TNF promoter sequences. Cluster quantification and pathway analysis of differentially expressed genes revealed an increased proportion of anti-inflammatory myeloid cells and a lower proportion of inflammatory non-classical monocytes among the circulating monocyte population in women with PE. CONCLUSIONS: Monocytes from women with PE and FGR exhibit an immune tolerance phenotype before initiation of labor. Further investigation is required to determine whether this tolerogenic phenotype persists after the affected pregnancy and contributes to increased risk of subsequent disease.
Subject(s)
Fetal Growth Retardation , Immunity, Innate , Lipopolysaccharides , Monocytes , Pre-Eclampsia , Humans , Female , Pregnancy , Adult , Monocytes/immunology , Pre-Eclampsia/immunology , Lipopolysaccharides/immunology , Fetal Growth Retardation/immunology , Histones/metabolism , Cells, Cultured , Epigenesis, Genetic , Cellular Reprogramming , Tumor Necrosis Factor-alpha/metabolism , Promoter Regions, Genetic/genetics , Cytokines/metabolismABSTRACT
BACKGROUND: The Pharyngeal Endoderm (PE) is an extremely relevant developmental tissue, serving as the progenitor for the esophagus, parathyroids, thyroids, lungs, and thymus. While several studies have highlighted the importance of PE cells, a detailed transcriptional and epigenetic characterization of this important developmental stage is still missing, especially in humans, due to technical and ethical constraints pertaining to its early formation. RESULTS: Here we fill this knowledge gap by developing an in vitro protocol for the derivation of PE-like cells from human Embryonic Stem Cells (hESCs) and by providing an integrated multi-omics characterization. Our PE-like cells robustly express PE markers and are transcriptionally homogenous and similar to in vivo mouse PE cells. In addition, we define their epigenetic landscape and dynamic changes in response to Retinoic Acid by combining ATAC-Seq and ChIP-Seq of histone modifications. The integration of multiple high-throughput datasets leads to the identification of new putative regulatory regions and to the inference of a Retinoic Acid-centered transcription factor network orchestrating the development of PE-like cells. CONCLUSIONS: By combining hESCs differentiation with computational genomics, our work reveals the epigenetic dynamics that occur during human PE differentiation, providing a solid resource and foundation for research focused on the development of PE derivatives and the modeling of their developmental defects in genetic syndromes.
Subject(s)
Cell Differentiation , Endoderm , Epigenesis, Genetic , Human Embryonic Stem Cells , Humans , Endoderm/cytology , Endoderm/metabolism , Human Embryonic Stem Cells/metabolism , Human Embryonic Stem Cells/cytology , Pharynx/cytology , Pharynx/metabolism , Tretinoin/pharmacology , Tretinoin/metabolism , Gene Expression Regulation, Developmental , Transcription Factors/metabolism , Transcription Factors/genetics , MiceABSTRACT
BACKGROUND: Peripheral T cell lymphomas (PTCLs) are prototypical epigenetic malignancies with invariably poor prognoses. Novel and effective therapeutic strategies are needed to improve clinical outcomes, particularly in relapsed/refractory patients. METHODS: We conducted a multicenter phase 2 study to evaluate the therapeutic efficacy of azacitidine and chidamide, alone or in combination with gemcitabine and oxaliplatin (GemOx), in patients with relapsed/refractory PTCLs (registration number: ChiCTR2000037232). The primary endpoint was the best overall response rate. FINDINGS: As of May 1st, 2024, thirty patients were evaluable for efficacy and toxicity. The best overall response rate was 53.3%, meeting its primary endpoint. Among the patients with angioimmunoblastic T cell lymphoma (AITL; N = 19), a numerically higher response rate was observed, regardless of whether chemotherapy was combined, compared to patients with non-AITL. After a median follow-up of 36.6 months, median progression-free survival and overall survival were 7.1 and 8.7 months, respectively. Patients with AITL who received combination chemotherapy (N = 12) achieved the most promising response rates (overall response rate, 91.7%; complete remission rate, 66.7%) and survival outcomes (median progression-free survival, 17.2 months; median overall survival, 38.8 months). The most common grade 3-4 toxicities were neutropenia (40.0%) and thrombocytopenia (30.0%). CONCLUSIONS: The combination of epigenetic therapy with GemOx was well tolerated and highly effective in patients with relapsed/refractory PTCLs. Patients with AITL, in particular, may benefit more from this combination treatment and should be the focus of future studies. FUNDING: This work was funded by the Natural Science Foundation of Jiangsu Province (BK20232039).
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Posterior fossa group A (PFA) ependymoma is a lethal brain cancer diagnosed in infants and young children. The lack of driver events in the PFA linear genome led us to search its 3D genome for characteristic features. Here, we reconstructed 3D genomes from diverse childhood tumor types and uncovered a global topology in PFA that is highly reminiscent of stem and progenitor cells in a variety of human tissues. A remarkable feature exclusively present in PFA are type B ultra long-range interactions in PFAs (TULIPs), regions separated by great distances along the linear genome that interact with each other in the 3D nuclear space with surprising strength. TULIPs occur in all PFA samples and recur at predictable genomic coordinates, and their formation is induced by expression of EZHIP. The universality of TULIPs across PFA samples suggests a conservation of molecular principles that could be exploited therapeutically.
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BACKGROUND: Overeating and inactivity are associated with type 2 diabetes. This study aimed to investigate its pathological basis using integrated omics and db/db/mice, a model representing this condition. METHODS: The study involved housing 8-week-old db/m and db/db mice for 8 weeks. Various analyses were conducted, including gene expression in skeletal muscle and small intestine using next-generation sequencing; cytokine arrays of serum; assessment of metabolites in skeletal muscle, stool, and serum; and analysis of the gut microbiota. Histone modifications in small intestinal epithelial cells were profiled using CUT&Tag. RESULTS: Compared with db/m mice, db/db mice had 22.4% lower grip strength and approximately five times the visceral fat weight (P < 0.0001). Serum cytokine arrays showed a 2.8-fold relative concentration of VEGF-A in db/db mice (P < 0.0001) and lower concentrations of several other cytokines. mRNA sequencing revealed downregulation of Myh expression in skeletal muscle, upregulation of lipid and glucose transporters, and downregulation of amino acid transporters in the small intestine of db/db/mice. The concentrations of saturated fatty acids in skeletal muscle were significantly higher, and the levels of essential amino acids were lower in db/db mice. Analysis of the gut microbiota, 16S rRNA sequencing, revealed lower levels of the phylum Bacteroidetes (59.7% vs. 44.9%) and higher levels of the phylum Firmicutes (20.9% vs. 31.4%) in db/db mice (P = 0.003). The integrated signal of histone modifications of lipid and glucose transporters was higher, while the integrated signal of histone modifications of amino acid transporters was lower in the db/db mice. CONCLUSIONS: The multi-omics approach provided insights into the epigenomic alterations in the small intestine, suggesting their involvement in the pathogenesis of inactivity-induced muscle atrophy in obese mice.
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Plants possess diverse cell types and intricate regulatory mechanisms to adapt to the ever-changing environment of nature. Various strategies have been employed to study cell types and their developmental progressions, including single-cell sequencing methods which provide high-dimensional catalogs to address biological concerns. In recent years, single-cell sequencing technologies in transcriptomics, epigenomics, proteomics, metabolomics, and spatial transcriptomics have been increasingly used in plant science to reveal intricate biological relationships at the single-cell level. However, the application of single-cell technologies to plants is more limited due to the challenges posed by cell structure. This review outlines the advancements in single-cell omics technologies, their implications in plant systems, future research applications, and the challenges of single-cell omics in plant systems.
Subject(s)
Genomics , Metabolomics , Plants , Proteomics , Single-Cell Analysis , Single-Cell Analysis/methods , Plants/genetics , Plants/metabolism , Metabolomics/methods , Proteomics/methods , Genomics/methods , Epigenomics/methods , Transcriptome/geneticsABSTRACT
Osteoarthritis (OA) is the most common form of arthritis with well recognized multifactorial nature. While several environmental factors such as older age, obesity and previous joint injury are strongly associated with its development, a genetic influence on OA has been recognized for over 80 years. Identification of genes associated with OA has received considerable attention over the last two decades, aided by the rapidly evolving genotyping and sequencing technologies. More than 300 genomic loci have been identified to be associated with OA at different joints. These findings are likely to help our better understanding of the pathogenesis of OA and lead to important therapeutic and diagnostic advances in this most common disabling rheumatic disorder. This article will review the data that support the role of genetic factors in common idiopathic OA.
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Cancer drug resistance is associated with metabolic adaptation. Cancer cells have been shown to implicate acetylated polyamines in adaptations during cell death. However, exploring the mimetic of acetylated polyamines as a potential anticancer drug is lacking. We performed intracellular metabolite profiling of human breast cancer MCF-7 cells treated with doxorubicin (DOX), a well known anticancer drug. A novel and in-house vertical tube gel electrophoresis assisted procedure followed by LC-HRMS analysis was employed to detect acetylated polyamines such as N1-acetylspermidine. We designed a mimetic N1-acetylspermidine (MINAS) which is a known substrate of histone deacetylase 10 (HDAC10). Molecular docking and molecular dynamics (MDs) simulations were used to evaluate the inhibitory potential of MINAS against HDAC10. The inhibitory potential and the ADMET profile of MINAS were compared to a known HDAC10 inhibitor Tubastatin A. N1-acetylspermidine, an acetylated form of polyamine, was detected intracellularly in MCF-7 cells treated with DOX over DMSO-treated MCF-7 cells. We designed and curated MINAS (PubChem CID 162679241). Molecular docking and MD simulations suggested the strong and comparable inhibitory potential of MINAS (-8.2 kcal/mol) to Tubastatin A (-8.4 kcal/mol). MINAS and Tubastatin A share similar binding sites on HDAC10, including Ser138, Ser140, Tyr183, and Cys184. Additionally, MINAS has a better ADMET profile compared to Tubastatin A, with a high MRTD value and lower toxicity. In conclusion, the data show that N1-acetylspermidine levels rise during DOX-induced breast cancer cell death. Additionally, MINAS, an N1-acetylspermidine mimetic compound, could be investigated as a potential anticancer drug when combined with chemotherapy like DOX.
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Technological advancements in cell-free DNA (cfDNA) liquid biopsy have triggered exponential growth in numerous clinical applications. While cfDNA-based liquid biopsy has made significant strides in personalizing cancer treatment, the exploration and translation of epigenetics in liquid biopsy to clinical practice is still nascent. This comprehensive review seeks to provide a broad yet in-depth narrative of the present status of epigenetics in cfDNA liquid biopsy and its associated challenges. It highlights the potential of epigenetics in cfDNA liquid biopsy technologies with the hopes of enhancing its clinical translation. The momentum of cfDNA liquid biopsy technologies in recent years has propelled epigenetics to the forefront of molecular biology. We have only begun to reveal the true potential of epigenetics in both our understanding of disease and leveraging epigenetics in the diagnostic and therapeutic domains. Recent clinical applications of epigenetics-based cfDNA liquid biopsy revolve around DNA methylation in screening and early cancer detection, leading to the development of multi-cancer early detection tests and the capability to pinpoint tissues of origin. The clinical application of epigenetics in cfDNA liquid biopsy in minimal residual disease, monitoring, and surveillance are at their initial stages. A notable advancement in fragmentation patterns analysis has created a new avenue for epigenetic biomarkers. However, the widespread application of cfDNA liquid biopsy has many challenges, including biomarker sensitivity, specificity, logistics including infrastructure and personnel, data processing, handling, results interpretation, accessibility, and cost effectiveness. Exploring and translating epigenetics in cfDNA liquid biopsy technology can transform our understanding and perception of cancer prevention and management. cfDNA liquid biopsy has great potential in precision oncology to revolutionize conventional ways of early cancer detection, monitoring residual disease, treatment response, surveillance, and drug development. Adapting the implementation of liquid biopsy workflow to the local policy worldwide and developing point-of-care testing holds great potential to overcome global cancer disparity and improve cancer outcomes.
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BACKGROUND: As key regulators of gene expression, microRNAs affect many cardiovascular mechanisms and have been associated with several cardiovascular diseases. In this study, we aimed to investigate the relation of whole blood microRNAs with several quantitative measurements of vascular function, and explore their biological role through an integrative microRNA-gene expression analysis. METHODS: Peripheral whole blood microRNA expression was assessed through RNA-Seq in 2606 participants (45.8% men, mean age: 53.93, age range: 30 to 95 years) from the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany. Weighted gene co-expression network analysis was used to cluster microRNAs with highly correlated expression levels into 14 modules. Through linear regression models, we investigated the association between each module's expression and quantitative markers of vascular health, including pulse wave velocity, total arterial compliance index, cardiac index, stroke index, systemic vascular resistance index, reactive skin hyperemia and white matter hyperintensity burden. For each module associated with at least one trait, one or more hub-microRNAs driving the association were defined. Hub-microRNAs were further characterized through mapping to putative target genes followed by gene ontology pathway analysis. RESULTS: Four modules, represented by hub-microRNAs miR-320 family, miR-378 family, miR-3605-3p, miR-6747-3p, miR-6786-3p, and miR-330-5p, were associated with total arterial compliance index. Importantly, the miR-320 family module was also associated with white matter hyperintensity burden, an effect partially mediated through arterial compliance. Furthermore, hub-microRNA miR-192-5p was related to cardiac index. Functional analysis corroborated the relevance of the identified microRNAs for vascular function by revealing, among others, enrichment for pathways involved in blood vessel morphogenesis and development, angiogenesis, telomere organization and maintenance, and insulin secretion. CONCLUSIONS: We identified several microRNAs robustly associated with cardiovascular function, especially arterial compliance and cardiac output. Moreover, our results highlight miR-320 as a regulator of cerebrovascular damage, partly through modulation of vascular function. As many of these microRNAs were involved in biological processes related to vasculature development and aging, our results contribute to the understanding of vascular physiology and provide putative targets for cardiovascular disease prevention.
Subject(s)
MicroRNAs , Humans , Male , Middle Aged , Female , MicroRNAs/blood , MicroRNAs/genetics , Aged , Adult , Aged, 80 and over , Gene Regulatory Networks , Gene Expression Regulation , Blood Vessels/physiology , Cohort Studies , Gene Ontology , Gene Expression ProfilingABSTRACT
As development varies greatly across the tree of life, it may seem difficult to suggest a model that proposes a single mechanism for understanding collective cell behaviors and the coordination of tissue formation. Here we propose a mechanism called differentiation waves, which unify many disparate results involving developmental systems from across the tree of life. We demonstrate how a relatively simple model of differentiation proceeds not from function-related molecular mechanisms, but from so-called differentiation waves. A phenotypic model of differentiation waves is introduced, and its relation to molecular mechanisms is proposed. These waves contribute to a differentiation tree, which is an alternate way of viewing cell lineage and local action of the molecular factors. We construct a model of differentiation wave-related molecular mechanisms (genome, epigenome, and proteome) based on bioinformatic data from the nematode Caenorhabditis elegans. To validate this approach across different modes of development, we evaluate protein expression across different types of development by comparing Caenorhabditis elegans with several model organisms: fruit flies (Drosophila melanogaster), yeast (Saccharomyces cerevisiae), and mouse (Mus musculus). Inspired by gene regulatory networks, two Models of Interactive Contributions (fully-connected MICs and ordered MICs) are used to suggest potential genomic contributions to differentiation wave-related proteins. This, in turn, provides a framework for understanding differentiation and development.
ABSTRACT
BACKGROUND: Physical activity is well known for its multiple health benefits and although the knowledge of the underlying molecular mechanisms is increasing, our understanding of the role of epigenetics in long-term training adaptation remains incomplete. In this intervention study, we included individuals with a history of > 15 years of regular endurance or resistance training compared to age-matched untrained controls performing endurance or resistance exercise. We examined skeletal muscle DNA methylation of genes involved in key adaptation processes, including myogenesis, gene regulation, angiogenesis and metabolism. RESULTS: A greater number of differentially methylated regions and differentially expressed genes were identified when comparing the endurance group with the control group than in the comparison between the strength group and the control group at baseline. Although the cellular composition of skeletal muscle samples was generally consistent across groups, variations were observed in the distribution of muscle fiber types. Slow-twitch fiber type genes MYH7 and MYL3 exhibited lower promoter methylation and elevated expression in endurance-trained athletes, while the same group showed higher methylation in transcription factors such as FOXO3, CREB5, and PGC-1α. The baseline DNA methylation state of those genes was associated with the transcriptional response to an acute bout of exercise. Acute exercise altered very few of the investigated CpG sites. CONCLUSIONS: Endurance- compared to resistance-trained athletes and untrained individuals demonstrated a different DNA methylation signature of selected skeletal muscle genes, which may influence transcriptional dynamics following a bout of acute exercise. Skeletal muscle fiber type distribution is associated with methylation of fiber type specific genes. Our results suggest that the baseline DNA methylation landscape in skeletal muscle influences the transcription of regulatory genes in response to an acute exercise bout.
Subject(s)
DNA Methylation , Exercise , Muscle, Skeletal , Resistance Training , Humans , Male , Exercise/physiology , Adult , Muscle, Skeletal/metabolism , Muscle, Skeletal/physiology , Epigenesis, Genetic , Physical Endurance/geneticsABSTRACT
Primary liver cancer, more specifically hepatocellular carcinoma (HCC), remains a significant global health problem associated with increasing incidence and mortality. Clinical, biological, and molecular heterogeneity are well-known hallmarks of cancer and HCC is considered one of the most heterogeneous tumour types, displaying substantial inter-patient, intertumoural and intratumoural variability. This heterogeneity plays a pivotal role in hepatocarcinogenesis, metastasis, relapse and drug response or resistance. Unimodal single-cell sequencing techniques have already revolutionised our understanding of the different layers of molecular hierarchy in the tumour microenvironment of HCC. By highlighting the cellular heterogeneity and the intricate interactions among cancer, immune and stromal cells before and during treatment, these techniques have contributed to a deeper comprehension of tumour clonality, hematogenous spreading and the mechanisms of action of immune checkpoint inhibitors. However, major questions remain to be elucidated, with the identification of biomarkers predicting response or resistance to immunotherapy-based regimens representing an important unmet clinical need. Although the application of single-cell multi-omics in liver cancer research has been limited thus far, a revolution of individualised care for patients with HCC will only be possible by integrating various unimodal methods into multi-omics methodologies at the single-cell resolution. In this review, we will highlight the different established single-cell sequencing techniques and explore their biological and clinical impact on liver cancer research, while casting a glance at the future role of multi-omics in this dynamic and rapidly evolving field.
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Colorectal cancer is one of the most common cancers worldwide. Lymph node metastasis is an important marker of colorectal cancer progression and plays a key role in the evaluation of patient prognosis. Accurate preoperative assessment of lymph node metastasis is crucial for devising appropriate treatment plans. However, current clinical imaging methods have limitations in many aspects. Therefore, the discovery of a method for accurately predicting lymph node metastasis is crucial clinical decision-making. DNA methylation is a common epigenetic modification that can regulate gene expression, which also has an important impact on the development of colorectal cancer. It is considered to be a promising biomarker with good specificity and stability and has promising application in predicting lymph node metastasis in patients with colorectal cancer. This article reviews the characteristics and limitations of currently available methods for predicting lymph node metastasis in patients with colorectal cancer and discusses the role of DNA methylation as a biomarker.