dbEM: A database of epigenetic modifiers curated from cancerous and normal genomes

Decoding the therapeutic landscape of alpha-linolenic acid: a network pharmacology and bioinformatics investigation against cancer-related epigenetic modifiers

Omega-3 (n - 3) and omega-6 (n - 6) polyunsaturated fatty acids (PUFAs) are vital for human health, but an imbalance between these types is associated with chronic diseases, including cancer. Alpha-linolenic acid (ALA), a n - 3 PUFA, shows promise as an anticancer agent in both laboratory and animal studies. However, the precise molecular mechanisms underlying ALA's actions against cancer-related epigenetic modifiers (CaEpM) remain unclear. To understand this, we employed network pharmacology (NP) and molecular docking techniques. Our study identified 51 potential ALA targets and GO and KEGG pathway analysis revealed possible molecular targets and signaling pathways of ALA against CaEpM. From PPI analysis, EZH2, KAT2B, SIRT1, KAT2A, KDM6B, EHMT2, WDR5, SETD7, SIRT2, and HDAC3 emerged as the top 10 potential targets. Additionally, GeneMANIA functional association (GMFA) network analysis of these top 10 targets was performed to enhance NP insights and explore ALA's multi-target approach. After an exhaustive analysis of the core FGN subnetwork, it became evident that 9 out of the 15 targets-namely EZH2, SUZ12, EED, PARP1, HDAC3, DNMT1, NCOR2, KAT2B, and TRRAP-manifested evidently strong and abundant interconnections among each other. Molecular docking of both top 10 targets and core FGN targets confirmed strong binding affinity between ALA and SIRT2, WDR5, KDM6B, EHMT2, HDAC3, EZH2, PARP1, and KAT2B, underscoring their roles in ALA's anti-CaEpM mechanism. Our findings suggest that ALA may target key signaling pathways related to transcriptional regulation, microRNA involvement, stem cell pluripotency and cellular senescence in cancer epigenetics. These findings illuminate ALA's potential as a multi-target agent against CaEpM.Communicated by Ramaswamy H. Sarma.

Combinatorial effector targeting (COMET) for transcriptional modulation and locus-specific biochemistry

Understanding how human gene expression is coordinately regulated by functional units of proteins across the genome remains a major biological goal. Here, we present COMET, a high-throughput screening platform for combinatorial effector targeting for the identification of transcriptional modulators. We generate libraries of combinatorial dCas9-based fusion proteins, containing two to six effector domains, allowing us to systematically investigate more than 110,000 combinations of effector proteins at endogenous human loci for their influence on transcription. Importantly, we keep full proteins or domains intact, maintaining catalytic cores and surfaces for protein-protein interactions. We observe more than 5800 significant hits that modulate transcription, we demonstrate cell type specific transcriptional modulation, and we further investigate epistatic relationships between our effector combinations. We validate unexpected combinations as synergistic or buffering, emphasizing COMET as both a method for transcriptional effector discovery, and as a functional genomics tool for identifying novel domain interactions and directing locus-specific biochemistry.

Functional mapping of epigenetic regulators uncovers coordinated tumor suppression by the HBO1 and MLL1 complexes

Epigenetic dysregulation is widespread in cancer. However, the specific epigenetic regulators and the processes they control to drive cancer phenotypes are poorly understood. Here, we employed a novel, scalable and high-throughput in vivo method to perform iterative functional screens of over 250 epigenetic regulatory genes within autochthonous oncogenic KRAS-driven lung tumors. We identified multiple novel epigenetic tumor suppressor and tumor dependency genes. We show that a specific HBO1 complex and the MLL1 complex are among the most impactful tumor suppressive epigenetic regulators in lung. The histone modifications generated by the HBO1 complex are frequently absent or reduced in human lung adenocarcinomas. The HBO1 and MLL1 complexes regulate chromatin accessibility of shared genomic regions, lineage fidelity and the expression of canonical tumor suppressor genes. The HBO1 and MLL1 complexes are epistatic during lung tumorigenesis, and their functional correlation is conserved in human cancer cell lines. Together, these results demonstrate the value of quantitative methods to generate a phenotypic roadmap of epigenetic regulatory genes in tumorigenesis in vivo .

Epigenetic target identification strategy based on multi-feature learning

The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics increases. In this study, we introduce a novel epigenetic target identification strategy (ETI-Strategy) that integrates a multi-task graph convolutional neural network prior model and a protein-ligand interaction classification discriminating model using large-scale bioactivity data for a panel of 55 epigenetic targets. Our approach utilizes machine learning techniques to achieve an AUC value of 0.934 for the prior model and 0.830 for the discriminating model, outperforming inverse docking in predicting protein-ligand interactions. When comparing with other open-source target identification tools, it was found that only our tool was able to accurately predict all the targets corresponding to each compound. This further demonstrates the ability of our strategy to take full advantage of molecular-level information as well as protein-level information in molecular activity prediction. Our work highlights the contribution of machine learning in the identification of potential epigenetic targets and offers a novel approach for epigenetic drug discovery and development.Communicated by Ramaswamy H. Sarma.

Differentiation shifts from a reversible to an irreversible heterochromatin state at the DM1 locus

Epigenetic defects caused by hereditary or de novo mutations are implicated in various human diseases. It remains uncertain whether correcting the underlying mutation can reverse these defects in patient cells. Here we show by the analysis of myotonic dystrophy type 1 (DM1)-related locus that in mutant human embryonic stem cells (hESCs), DNA methylation and H3K9me3 enrichments are completely abolished by repeat excision (CTG2000 expansion), whereas in patient myoblasts (CTG2600 expansion), repeat deletion fails to do so. This distinction between undifferentiated and differentiated cells arises during cell differentiation, and can be reversed by reprogramming of gene-edited myoblasts. We demonstrate that abnormal methylation in DM1 is distinctively maintained in the undifferentiated state by the activity of the de novo DNMTs (DNMT3b in tandem with DNMT3a). Overall, the findings highlight a crucial difference in heterochromatin maintenance between undifferentiated (sequence-dependent) and differentiated (sequence-independent) cells, thus underscoring the role of differentiation as a locking mechanism for repressive epigenetic modifications at the DM1 locus.

Targeting JMJD1C to selectively disrupt tumor Treg cell fitness enhances antitumor immunity

Regulatory T (Treg) cells are critical for immune tolerance but also form a barrier to antitumor immunity. As therapeutic strategies involving Treg cell depletion are limited by concurrent autoimmune disorders, identification of intratumoral Treg cell-specific regulatory mechanisms is needed for selective targeting. Epigenetic modulators can be targeted with small compounds, but intratumoral Treg cell-specific epigenetic regulators have been unexplored. Here, we show that JMJD1C, a histone demethylase upregulated by cytokines in the tumor microenvironment, is essential for tumor Treg cell fitness but dispensable for systemic immune homeostasis. JMJD1C deletion enhanced AKT signals in a manner dependent on histone H3 lysine 9 dimethylation (H3K9me2) demethylase and STAT3 signals independently of H3K9me2 demethylase, leading to robust interferon-γ production and tumor Treg cell fragility. We have also developed an oral JMJD1C inhibitor that suppresses tumor growth by targeting intratumoral Treg cells. Overall, this study identifies JMJD1C as an epigenetic hub that can integrate signals to establish tumor Treg cell fitness, and we present a specific JMJD1C inhibitor that can target tumor Treg cells without affecting systemic immune homeostasis.

A comprehensive atlas of epigenetic regulators reveals tissue-specific epigenetic regulation patterns

Epigenetic machinery contributes to gene regulation in eukaryotic species. However, the machinery including more than 600 epigenetic regulator (ER) genes responsible for reading, writing, and erasing histone modifications and DNA modifications remains largely uncharacterized across species. We compile a comprehensive list of ERs based on an evolutionary analysis across 23 species, which is the most comprehensive ER list in various species until recently. We further perform comparative transcriptomic analyses across different tissues in humans, mice, as well as other amniote species. We observe a consistent tissue-of-origin expression specificity pattern of duplicated ER genes across species and suggest links between expression specificity and ER gene evolution as well as ER function. Additional analyses further suggest that ER duplication can generate tissue-specific ER genes with the same epigenetic substrates, which may be closely related to their regulatory specificity in tissue development. Our work can serve as a foundation to better comprehend the tissue-specific expression patterns of ER genes from an evolutionary perspective and also the functional implications of ERs in tissue-specific epigenetic regulation.

The epigenetic modifier lysine methyltransferase 2C is frequently mutated in gastric remnant carcinoma

Gastric remnant carcinoma (GRC), which occurs in the stomach after partial gastrectomy, is a rare and aggressive form of gastric adenocarcinoma (GAC). Comprehensive profiling of genomic mutations in GRC could provide the basis for elucidating the origin and characteristics of this cancer. Herein, whole-exome sequencing (WES) was performed on 36 matched tumor-normal samples from patients with GRC and identified recurrent mutations in epigenetic modifiers, notably KMT2C, ARID1A, NSD1, and KMT2D, in 61.11% of cases. Mutational signature analysis revealed a low frequency of microsatellite instability (MSI) in GRC, which was further identified by MSIsensor, MSI-polymerase chain reaction, and immunohistochemistry analysis. Comparative analysis demonstrated that GRC had a distinct mutation spectrum compared to that of GAC in The Cancer Genome Atlas samples, with a significantly higher mutation rate of KMT2C. Targeted deep sequencing (Target-seq) of an additional 25 paired tumor-normal samples verified the high mutation frequency (48%) of KMT2C in GRC. KMT2C mutations correlated with poor overall survival in both WES and Target-seq cohorts and were independent prognosticators in GRC. In addition, KMT2C mutations were positively correlated with favorable outcomes in immune checkpoint inhibitor-treated pan-cancer patients and associated with higher intratumoral CD3+ , CD8+ tumor-infiltrating lymphocyte counts, and PD-L1 expression in GRC samples (p = 0.018, 0.092, 0.047, 0.010, and 0.034, respectively). Our dataset provides a platform for information and knowledge mining of the genomic characteristics of GRC and helps to frame new therapeutic approaches for this disease.

An Updated Overview of Existing Cancer Databases and Identified Needs

Our search of existing cancer databases aimed to assess the current landscape and identify key needs. We analyzed 71 databases, focusing on genomics, proteomics, lipidomics, and glycomics. We found a lack of cancer-related lipidomic and glycomic databases, indicating a need for further development in these areas. Proteomic databases dedicated to cancer research were also limited. To assess overall progress, we included human non-cancer databases in proteomics, lipidomics, and glycomics for comparison. This provided insights into advancements in these fields over the past eight years. We also analyzed other types of cancer databases, such as clinical trial databases and web servers. Evaluating user-friendliness, we used the FAIRness principle to assess findability, accessibility, interoperability, and reusability. This ensured databases were easily accessible and usable. Our search summary highlights significant growth in cancer databases while identifying gaps and needs. These insights are valuable for researchers, clinicians, and database developers, guiding efforts to enhance accessibility, integration, and usability. Addressing these needs will support advancements in cancer research and benefit the wider cancer community.

Diverse clonal fates emerge upon drug treatment of homogeneous cancer cells

Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells1-7. Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy7-9; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues.

Impact of IDH Mutations, the 1p/19q Co-Deletion and the G-CIMP Status on Alternative Splicing in Diffuse Gliomas

By generating protein diversity, alternative splicing provides an important oncogenic pathway. Isocitrate dehydrogenase (IDH) 1 and 2 mutations and 1p/19q co-deletion have become crucial for the novel molecular classification of diffuse gliomas, which also incorporates DNA methylation profiling. In this study, we have carried out a bioinformatics analysis to examine the impact of the IDH mutation, as well as the 1p/19q co-deletion and the glioma CpG island methylator phenotype (G-CIMP) status on alternative splicing in a cohort of 662 diffuse gliomas from The Cancer Genome Atlas (TCGA). We identify the biological processes and molecular functions affected by alternative splicing in the various glioma subgroups and provide evidence supporting the important contribution of alternative splicing in modulating epigenetic regulation in diffuse gliomas. Targeting the genes and pathways affected by alternative splicing might provide novel therapeutic opportunities against gliomas.

ALTERED LEVELS OF H3K9AC, H3K4ME3, AND H3K27ME3 IN PROMOTERS OF DIFFERENTIALLY EXPRESSED GENES RELATED TO INNATE IMMUNE RESPONSE IN SEPTIC PATIENTS WITH DIFFERENT CLINICAL OUTCOMES

ABSTRACT

Sepsis is one of the leading causes of morbidity and mortality worldwide. Monocytes seem to undergo functional reprogramming during sepsis, resulting in dysregulated host immune response. To clarify this dysregulation mechanism, we investigated three histone modifications found in promoters of genes involved in innate immune response, and associated these findings with gene transcription in septic patients. These results were compared with public transcriptome data of the target genes and epigenetic enzymes that modulate the histone modifications. We used peripheral blood mononuclear cell from surviving and nonsurviving septic patients, and healthy volunteers to evaluate the expression of genes involved in innate immune response and the enrichment of H3K9ac, H3K4me3, and H3K27me3 in their promoters, by RT-qPCR and ChIP, respectively. Finally, we used transcriptome data sets to validate our findings. We found alterations in the chromatin enrichment of different genes, with an increase in H3K9ac in the anti-inflammatory cytokine IL-10 and the antimicrobial gene FPR1 , as well as an increase in H3K27me3 in the IL-10 and HLA-DR promoter in nonsurvivors septic patients when compared with survivors. These alterations were partially associated with the gene expression profile. In addition, we found moderate to strong correlation between gene transcription and the enzymes that modulate these histone modifications in the transcriptome data sets. Our study, one of the pioneering by evaluating septic patients' samples, suggests that epigenetic enzymes modulate the prevalent histone marks in promoters of genes involved in the immune-inflammatory response, altering the transcription of these specific genes during sepsis. Furthermore, nonsurviving sepsis patients have a more pronounced epigenetic dysregulation compared with survivors, suggesting a more dysfunctional response.

A polyphenol-rich green Mediterranean diet enhances epigenetic regulatory potential: the DIRECT PLUS randomized controlled trial

BACKGROUND

The capacity of a polyphenol-enriched diet to modulate the epigenome in vivo is partly unknown. Given the beneficial metabolic effects of a Mediterranean (MED) diet enriched in polyphenols and reduced in red/processed meat (green-MED), as previously been proven by the 18-month DIRECT PLUS randomized controlled trial, we analyzed the effects of the green-MED diet on methylome and transcriptome levels to highlight molecular mechanisms underlying the observed metabolic improvements.

METHODS

Our study included 260 participants (baseline BMI = 31.2 kg/m², age = 5 years) of the DIRECT PLUS trial, initially randomized to one of the intervention arms: A. healthy dietary guidelines (HDG), B. MED (440 mg polyphenols additionally provided by walnuts), C. green-MED (1240 mg polyphenols additionally provided by walnuts, green tea, and Mankai: green duckweed shake). Blood methylome and transcriptome of all study subjects were analyzed at baseline and after completing the 18-month intervention using Illumina EPIC and RNA sequencing technologies.

RESULTS

A total of 1573 differentially methylated regions (DMRs; false discovery rate (FDR) < 5 %) were found in the green-MED compared to the MED (177) and HDG (377) diet participants. This corresponded to 1753 differentially expressed genes (DEGs; FDR < 5 %) in the green-MED intervention compared to MED (7) and HDG (738). Consistently, the highest number (6 %) of epigenetic modulating genes was transcriptionally changed in subjects participating in the green-MED intervention. Weighted cluster network analysis relating transcriptional and phenotype changes among participants subjected to the green-MED intervention identified candidate genes associated with serum-folic acid change (all P < 1 × 10^-3) and highlighted one module including the KIR3DS1 locus, being negatively associated with the polyphenol changes (e.g. P < 1 × 10^-4), but positively associated with the MRI-assessed superficial subcutaneous adipose area-, weight- and waist circumference- 18-month change (all P < 0.05). Among others, this module included the DMR gene Cystathionine Beta-Synthase, playing a major role in homocysteine reduction.

CONCLUSIONS

The green-MED high polyphenol diet, rich in green tea and Mankai, renders a high capacity to regulate an individual's epigenome. Our findings suggest epigenetic key drivers such as folate and green diet marker to mediate this capacity and indicate a direct effect of dietary polyphenols on the one‑carbon metabolism.

Promises and challenges in pharmacoepigenetics

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

Pediatric chordoma associated with tuberous sclerosis complex: A rare case report with a thorough analysis of potential therapeutic molecular targets

Chordoma associated with tuberous sclerosis complex (TSC) is an extremely rare tumor that was described only in 13 cases since 1975. Сhordoma itself is a malignant slow-growing bone tumor thought to arise from vestigial or ectopic notochordal tissue. Chordoma associated with TSC differs from chordoma in the general pediatric population in the median age, where the diagnosis of TSC-associated chordoma is 6.2 months, whereas for chordoma in the general pediatric population it is set to 12 years. The majority of TSC-associated chordomas are localized in skull-based and sacrum regions, and rare in the spine. Chordomas are genetically heterogeneous tumors characterized by chromosomal instability (CIN), and alterations involving PI3K-AKT signaling pathway genes and chromatin remodeling genes. Here we present the 14th case of chordoma associated with TSC in a 1-year-old pediatric patient. Alongside biallelic inactivation of the TSC1 gene, molecular genetic analysis revealed CIN and involvement of epigenetic regulation genes. In addition, we found the engagement of CBX7 and apolipoprotein B editing complex (APOBEC3) genes that were not yet seen in chordomas before. Amplification of CBX7 may epigenetically silence the CDKN2A gene, whereas amplification of APOBEC3 genes can explain the frequent occurrence of CIN in chordomas. We also found that KRAS gene is located in the region with gain status, which may suggest the ineffectiveness of potential EGFR monotherapy. Thus, molecular genetic analysis carried out in this study broadens the horizons of possible approaches for targeted therapies with potential applications for personalized medicine.

Innovative in Silico Approaches for Characterization of Genes and Proteins

Bioinformatics is an amalgamation of biology, mathematics and computer science. It is a science which gathers the information from biology in terms of molecules and applies the informatic techniques to the gathered information for understanding and organizing the data in a useful manner. With the help of bioinformatics, the experimental data generated is stored in several databases available online like nucleotide database, protein databases, GENBANK and others. The data stored in these databases is used as reference for experimental evaluation and validation. Till now several online tools have been developed to analyze the genomic, transcriptomic, proteomics, epigenomics and metabolomics data. Some of them include Human Splicing Finder (HSF), Exonic Splicing Enhancer Mutation taster, and others. A number of SNPs are observed in the non-coding, intronic regions and play a role in the regulation of genes, which may or may not directly impose an effect on the protein expression. Many mutations are thought to influence the splicing mechanism by affecting the existing splice sites or creating a new sites. To predict the effect of mutation (SNP) on splicing mechanism/signal, HSF was developed. Thus, the tool is helpful in predicting the effect of mutations on splicing signals and can provide data even for better understanding of the intronic mutations that can be further validated experimentally. Additionally, rapid advancement in proteomics have steered researchers to organize the study of protein structure, function, relationships, and dynamics in space and time. Thus the effective integration of all of these technological interventions will eventually lead to steering up of next-generation systems biology, which will provide valuable biological insights in the field of research, diagnostic, therapeutic and development of personalized medicine.

MIAOME: Human Microbiome Affect The Host Epigenome

Besides the genetic factors having tremendous influences on the regulations of the epigenome, the microenvironmental factors have recently gained extensive attention for their roles in affecting the host epigenome. There are three major types of microenvironmental factors: microbiota-derived metabolites (MDM), microbiota-derived components (MDC) and microbiota-secreted proteins (MSP). These factors can regulate host physiology by modifying host gene expression through the three highly interconnected epigenetic mechanisms (e.g. histone modifications, DNA modifications, and non-coding RNAs). However, no database was available to provide the comprehensive factors of these types. Herein, a database entitled 'Human Microbiome Affect The Host Epigenome (MIAOME)' was constructed. Based on the types of epigenetic modifications confirmed in the literature review, the MIAOME database captures 1068 (63 genus, 281 species, 707 strains, etc.) human microbes, 91 unique microbiota-derived metabolites & components (16 fatty acids, 10 bile acids, 10 phenolic compounds, 10 vitamins, 9 tryptophan metabolites, etc.) derived from 967 microbes; 50 microbes that secreted 40 proteins; 98 microbes that directly influence the host epigenetic modification, and provides 3 classifications of the epigenome, including (1) 4 types of DNA modifications, (2) 20 histone modifications and (3) 490 ncRNAs regulations, involved in 160 human diseases. All in all, MIAOME has compiled the information on the microenvironmental factors influence host epigenome through the scientific literature and biochemical databases, and allows the collective considerations among the different types of factors. It can be freely assessed without login requirement by all users at: http://miaome.idrblab.net/ttd/

Reviewing cancer's biology: an eclectic approach

BACKGROUND

Cancer refers to a group of some of the worldwide most diagnosed and deadliest pathophysiological conditions that conquered researchers' attention for decades and yet begs for more questions for a full comprehension of its complex cellular and molecular pathology.

MAIN BODY

The disease conditions are commonly characterized by unrestricted cell proliferation and dysfunctional replicative senescence pathways. In fact, the cell cycle operates under the rigorous control of complex signaling pathways involving cyclins and cyclin-dependent kinases assumed to be specific to each phase of the cycle. At each of these checkpoints, the cell is checked essentially for its DNA integrity. Genetic defects observed in these molecules (i.e., cyclins, cyclin-dependent kinases) are common features of cancer cells. Nevertheless, each cancer is different concerning its molecular and cellular etiology. These could range from the genetic defects mechanisms and/or the environmental conditions favoring epigenetically harbored homeostasis driving tumorigenesis alongside with the intratumoral heterogeneity with respect to the model that the tumor follows.

CONCLUSIONS

This review is not meant to be an exhaustive interpretation of carcinogenesis but to summarize some basic features of the molecular etiology of cancer and the intratumoral heterogeneity models that eventually bolster anticancer drug resistance for a more efficient design of drug targeting the pitfalls of the models.

A Systematic Review of Transcriptional Dysregulation in Huntington's Disease Studied by RNA Sequencing

Huntington's disease (HD) is a chronic neurodegenerative disorder caused by an expansion of polyglutamine repeats in exon 1 of the Huntingtin gene. Transcriptional dysregulation accompanied by epigenetic alterations is an early and central disease mechanism in HD yet, the exact mechanisms and regulators, and their associated gene expression programs remain incompletely understood. This systematic review investigates genome-wide transcriptional studies that were conducted using RNA sequencing (RNA-seq) technology in HD patients and models. The review protocol was registered at the Open Science Framework (OSF). The biomedical literature and gene expression databases, PubMed and NCBI BioProject, Array Express, European Nucleotide Archive (ENA), European Genome-Phenome Archive (EGA), respectively, were searched using the defined terms specified in the protocol following the PRISMA guidelines. We conducted a complete literature and database search to retrieve all RNA-seq-based gene expression studies in HD published until August 2020, retrieving 288 articles and 237 datasets from PubMed and the databases, respectively. A total of 27 studies meeting the eligibility criteria were included in this review. Collectively, comparative analysis of the datasets revealed frequent genes that are consistently dysregulated in HD. In postmortem brains from HD patients, DNAJB1, HSPA1B and HSPB1 genes were commonly upregulated across all brain regions and cell types except for medium spiny neurons (MSNs) at symptomatic disease stage, and HSPH1 and SAT1 genes were altered in expression in all symptomatic brain datasets, indicating early and sustained changes in the expression of genes related to heat shock response as well as response to misfolded proteins. Specifically in indirect pathway medium spiny neurons (iMSNs), mitochondria related genes were among the top uniquely dysregulated genes. Interestingly, blood from HD patients showed commonly differentially expressed genes with a number of brain regions and cells, with the highest number of overlapping genes with MSNs and BA9 region at symptomatic stage. We also found the differential expression and predicted altered activity of a set of transcription factors and epigenetic regulators, including BCL6, EGR1, FOSL2 and CREBBP, HDAC1, KDM4C, respectively, which may underlie the observed transcriptional changes in HD. Altogether, our work provides a complete overview of the transcriptional studies in HD, and by data synthesis, reveals a number of common and unique gene expression and regulatory changes across different cell and tissue types in HD. These changes could elucidate new insights into molecular mechanisms of differential vulnerability in HD. Systematic Review Registration: https://osf.io/pm3wq.

Prognostic Significance of Dysregulated Epigenomic and Chromatin Modifiers in Cervical Cancer

To broaden the understanding of the epigenomic and chromatin regulation of cervical cancer, we examined the status and significance of a set of epigenomic and chromatin modifiers in cervical cancer using computational biology. We observed that 61 of 917 epigenomic and/or chromatin regulators are differentially upregulated in human cancer, including 25 upregulated in invasive squamous cell carcinomas and 29 in cervical intraepithelial neoplasia 3 (CIN3), of which 14 are upregulated in cervical intraepithelial neoplasia 2 (CIN2). Interestingly, 57 of such regulators are uniquely upregulated in cervical cancer, but not ovarian and endometrial cancers. The observed overexpression of 57 regulators was found to have a prognostic significance in cervical cancer. The collective overexpression of these regulators, as well as its subsets belonging to specific histone modifications and corresponding top ten positively co-overexpressed genes, correlated with reduced survival of patients with high expressions of the tested overexpressed regulators compared to cases with low expressions. Using cell-dependency datasets from human cervical cancer cells, we found that 20 out of 57 epigenomic and chromatin regulators studied here appeared to be essential genes, as the depletion of these genes was accompanied by the loss in cellular viability. In brief, the results presented here provide further insights into the role of epigenomic and chromatin regulators in the oncobiology of cervical cancer and broaden the list of new potential molecules of therapeutic importance.

Transcriptome and proteome mapping in the sheep atria reveal molecular featurets of atrial fibrillation progression

AIMS

Atrial fibrillation (AF) is a progressive cardiac arrhythmia that increases the risk of hospitalization and adverse cardiovascular events. There is a clear demand for more inclusive and large-scale approaches to understand the molecular drivers responsible for AF, as well as the fundamental mechanisms governing the transition from paroxysmal to persistent and permanent forms. In this study, we aimed to create a molecular map of AF and find the distinct molecular programmes underlying cell type-specific atrial remodelling and AF progression.

METHODS AND RESULTS

We used a sheep model of long-standing, tachypacing-induced AF, sampled right and left atrial tissue, and isolated cardiomyocytes (CMs) from control, intermediate (transition), and late time points during AF progression, and performed transcriptomic and proteome profiling. We have merged all these layers of information into a meaningful three-component space in which we explored the genes and proteins detected and their common patterns of expression. Our data-driven analysis points at extracellular matrix remodelling, inflammation, ion channel, myofibril structure, mitochondrial complexes, chromatin remodelling, and genes related to neural function, as well as critical regulators of cell proliferation as hallmarks of AF progression. Most important, we prove that these changes occur at early transitional stages of the disease, but not at later stages, and that the left atrium undergoes significantly more profound changes than the right atrium in its expression programme. The pattern of dynamic changes in gene and protein expression replicate the electrical and structural remodelling demonstrated previously in the sheep and in humans, and uncover novel mechanisms potentially relevant for disease treatment.

CONCLUSIONS

Transcriptomic and proteomic analysis of AF progression in a large animal model shows that significant changes occur at early stages, and that among others involve previously undescribed increase in mitochondria, changes to the chromatin of atrial CMs, and genes related to neural function and cell proliferation.

Comparative transcriptome analysis reveals key epigenetic targets in SARS-CoV-2 infection

COVID-19 is an infection caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus 2), which has caused a global outbreak. Current research efforts are focused on the understanding of the molecular mechanisms involved in SARS-CoV-2 infection in order to propose drug-based therapeutic options. Transcriptional changes due to epigenetic regulation are key host cell responses to viral infection and have been studied in SARS-CoV and MERS-CoV; however, such changes are not fully described for SARS-CoV-2. In this study, we analyzed multiple transcriptomes obtained from cell lines infected with MERS-CoV, SARS-CoV, and SARS-CoV-2, and from COVID-19 patient-derived samples. Using integrative analyses of gene co-expression networks and de-novo pathway enrichment, we characterize different gene modules and protein pathways enriched with Transcription Factors or Epifactors relevant for SARS-CoV-2 infection. We identified EP300, MOV10, RELA, and TRIM25 as top candidates, and more than 60 additional proteins involved in the epigenetic response during viral infection that has therapeutic potential. Our results show that targeting the epigenetic machinery could be a feasible alternative to treat COVID-19.

A systematic dissection of the epigenomic heterogeneity of lung adenocarcinoma reveals two different subclasses with distinct prognosis and core regulatory networks

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly malignant and heterogeneous tumor that involves various oncogenic genetic alterations. Epigenetic processes play important roles in lung cancer development. However, the variation in enhancer and super-enhancer landscapes of LUAD patients remains largely unknown. To provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we investigate the H3K27ac histone modification profiles of tumors and adjacent normal lung tissues from 42 LUAD patients and explore the role of epigenetic alterations in LUAD progression.

RESULTS

A high intertumoral epigenetic heterogeneity is observed across the LUAD H3K27ac profiles. We quantitatively model the intertumoral variability of H3K27ac levels at proximal gene promoters and distal enhancers and propose a new epigenetic classification of LUAD patients. Our classification defines two LUAD subgroups which are highly related to histological subtypes. Group II patients have significantly worse prognosis than group I, which is further confirmed in the public TCGA-LUAD cohort. Differential RNA-seq analysis between group I and group II groups reveals that those genes upregulated in group II group tend to promote cell proliferation and induce cell de-differentiation. We construct the gene co-expression networks and identify group-specific core regulators. Most of these core regulators are linked with group-specific regulatory elements, such as super-enhancers. We further show that CLU is regulated by 3 group I-specific core regulators and works as a novel tumor suppressor in LUAD.

CONCLUSIONS

Our study systematically characterizes the epigenetic alterations during LUAD progression and provides a new classification model that is helpful for predicting patient prognosis.

A Chemo-Genomic Approach Identifies Diverse Epigenetic Therapeutic Vulnerabilities in MYCN-Amplified Neuroblastoma

Although a rare disease, neuroblastoma accounts for the highest proportion of childhood cancer deaths. There is a lack of recurrent somatic mutations in neuroblastoma embryonal tumours, suggesting a possible role for epigenetic alterations in driving this cancer. While an increasing number of reports suggest an association of MYCN with epigenetic machinery, the mechanisms of these interactions are poorly understood in the neuroblastoma setting. Utilising chemo-genomic approaches we revealed global MYCN-epigenetic interactions and identified numerous epigenetic proteins as MYCN targets. The epigenetic regulators HDAC2, CBX8 and CBP (CREBBP) were all MYCN target genes and also putative MYCN interactors. MYCN-related epigenetic genes included SMARCs, HDACs, SMYDs, BRDs and CREBBP. Expression levels of the majority of MYCN-related epigenetic genes showed predictive ability for neuroblastoma patient outcome. Furthermore, a compound library screen targeting epigenetic proteins revealed broad susceptibility of neuroblastoma cells to all classes of epigenetic regulators, belonging to families of bromodomains, HDACs, HATs, histone methyltransferases, DNA methyltransferases and lysin demethylases. Ninety-six percent of the compounds reduced MYCN-amplified neuroblastoma cell viability. We show that the C646 (CBP-bromodomain targeting compound) exhibits switch-like temporal and dose response behaviour and is effective at reducing neuroblastoma viability. Responsiveness correlates with MYCN expression, with MYCN-amplified cells being more susceptible to C646 treatment. Thus, exploiting the broad vulnerability of neuroblastoma cells to epigenetic targeting compounds represents an exciting strategy in neuroblastoma treatment, particularly for high-risk MYCN-amplified tumours.

Epigenetic Target Fishing with Accurate Machine Learning Models

Epigenetic targets are of significant importance in drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represents many structure-activity relationships that have not been exploited thus far to develop predictive models to support medicinal chemistry efforts. Herein, we report the first large-scale study of 26 318 compounds with a quantitative measure of biological activity for 55 protein targets with epigenetic activity. We built predictive models with high accuracy for small molecules' epigenetic target profiling through a systematic comparison of the machine learning models trained on different molecular fingerprints. The models were thoroughly validated, showing mean precisions of up to 0.952 for the epigenetic target prediction task. Our results indicate that the models reported herein have considerable potential to identify small molecules with epigenetic activity. Therefore, our results were implemented as a freely accessible web application.

Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications

Epigenetics is mainly comprised of features that regulate genomic interactions thereby playing a crucial role in a vast array of biological processes. Epigenetic mechanisms such as DNA methylation and histone modifications influence gene expression by modulating the packaging of DNA in the nucleus. A plethora of studies have emphasized the importance of analyzing epigenetics data through genome-wide studies and high-throughput approaches, thereby providing key insights towards epigenetics-based diseases such as cancer. Recent advancements have been made towards translating epigenetics research into a high throughput approach such as genome-scale profiling. Amongst all, bioinformatics plays a pivotal role in achieving epigenetics-related computational studies. Despite significant advancements towards epigenomic profiling, it is challenging to understand how various epigenetic modifications such as chromatin modifications and DNA methylation regulate gene expression. Next-generation sequencing (NGS) provides accurate and parallel sequencing thereby allowing researchers to comprehend epigenomic profiling. In this review, we summarize different computational methods such as machine learning and other bioinformatics tools, publicly available databases and resources to identify key modifications associated with epigenetic machinery. Additionally, the review also focuses on understanding recent methodologies related to epigenome profiling using NGS methods ranging from library preparation, different sequencing platforms and analytical techniques to evaluate various epigenetic modifications such as DNA methylation and histone modifications. We also provide detailed information on bioinformatics tools and computational strategies responsible for analyzing large scale data in epigenetics.

Genetic Determinism Exists for the Global DNA Methylation Rate in Sheep

Recent studies showed that epigenetic marks, including DNA methylation, influence production and adaptive traits in plants and animals. So far, most studies dealing with genetics and epigenetics considered DNA methylation sites independently. However, the genetic basis of the global DNA methylation rate (GDMR) remains unknown. The main objective of the present study was to investigate genetic determinism of GDMR in sheep. The experiment was conducted on 1,047 Romane sheep allocated into 10 half-sib families. After weaning, all the lambs were phenotyped for global GDMR in blood as well as for production and adaptive traits. GDMR was measured by LUminometric Methylation Analysis (LUMA) using a pyrosequencing approach. Association analyses were conducted on some of the lambs (n = 775) genotyped by using the Illumina OvineSNP50 BeadChip. Blood GDMR varied among the animals (average 70.7 ± 6.0%). Female lambs had significantly higher GDMR than male lambs. Inter-individual variability of blood GDMR had an additive genetic component and heritability was moderate (h² = 0.20 ± 0.05). No significant genetic correlation was found between GDMR and growth or carcass traits, birthcoat, or social behaviors. Association analyses revealed 28 QTLs associated with blood GDMR. Seven genomic regions on chromosomes 1, 5, 11, 17, 24, and 26 were of most interest due to either high significant associations with GDMR or to the relevance of genes located close to the QTLs. QTL effects were moderate. Genomic regions associated with GDMR harbored several genes not yet described as being involved in DNA methylation, but some are already known to play an active role in gene expression. In addition, some candidate genes, CHD1, NCO3A, KDM8, KAT7, and KAT6A have previously been described to be involved in epigenetic modifications. In conclusion, the results of the present study indicate that blood GDMR in domestic sheep is under polygenic influence and provide new insights into DNA methylation genetic determinism.

Targeting EHMT2/ G9a for cancer therapy: Progress and perspective

Euchromatic histone lysine methyltransferase-2, also known as G9a, is a ubiquitously expressed SET domain-containing histone lysine methyltransferase linked with both facultative and constitutive heterochromatin formation and transcriptional repression. It is an essential developmental gene and reported to play role in embryonic development, establishment of proviral silencing in ES cells, tumor cell growth, metastasis, T-cell immune response, cocaine induced neural plasticity and cognition and adaptive behavior. It is mainly responsible for carrying out mono, di and tri methylation of histone H3K9 in euchromatin. G9a levels are elevated in many cancers and its selective inhibition is known to reduce the cell growth and induce autophagy, apoptosis and senescence. We carried out a thorough search of online literature databases including Pubmed, Scopus, Journal websites, Clinical trials etc to gather the maximum possible information related to the G9a. The main messages from the cited papers are presented in a systematic manner. Chemical structures were drawn by Chemdraw software. In this review, we shed light on current understanding of structure and biological activity of G9a, the molecular events directing its targeting to genomic regions and its post-translational modification. Finally, we discuss the current strategies to target G9a in different cancers and evaluate the available compounds and agents used to inhibit G9a functions. The review provides the present status and future directions of research in targeting G9a and provides the basis to persuade the development of novel strategies to target G9a -related effects in cancer cells.

Epidrug Repurposing: Discovering New Faces of Old Acquaintances in Cancer Therapy

Gene mutations are strongly associated with tumor progression and are well known in cancer development. However, recently discovered epigenetic alterations have shown the potential to greatly influence tumoral response to therapy regimens. Such epigenetic alterations have proven to be dynamic, and thus could be restored. Due to their reversible nature, the promising opportunity to improve chemotherapy response using epigenetic therapy has arisen. Beyond helping to understand the biology of the disease, the use of modern clinical epigenetics is being incorporated into the management of the cancer patient. Potential epidrug candidates can be found through a process known as drug repositioning or repurposing, a promising strategy for the discovery of novel potential targets in already approved drugs. At present, novel epidrug candidates have been identified in preclinical studies and some others are currently being tested in clinical trials, ready to be repositioned. This epidrug repurposing could circumvent the classic paradigm where the main focus is the development of agents with one indication only, while giving patients lower cost therapies and a novel precision medical approach to optimize treatment efficacy and reduce toxicity. This review focuses on the main approved epidrugs, and their druggable targets, that are currently being used in cancer therapy. Also, we highlight the importance of epidrug repurposing by the rediscovery of known chemical entities that may enhance epigenetic therapy in cancer, contributing to the development of precision medicine in oncology.

Recent progress on cheminformatics approaches to epigenetic drug discovery

The ability of epigenetic markers to affect genome function has enabled transformative changes in drug discovery, especially in cancer and other emerging therapeutic areas. Concordant with the introduction of the term 'epi-informatics', the size of the epigenetically relevant chemical space has grown substantially and so did the number of applications of cheminformatic methods to epigenetics. Recent progress in epi-informatics has improved our understanding of the structure-epigenetic activity relationships and boosted the development of models predicting novel epigenetic agents. Herein, we review the advances in computational approaches to drug discovery of small molecules with epigenetic modulation profiles, summarize the current chemogenomics data available for epigenetic targets, and provide a perspective on the greater utility of biomedical knowledge mining as a means to advance the epigenetic drug discovery.

Genomic Biomarkers and Underlying Mechanism of Benefit from BCG Immunotherapy in Non-Muscle Invasive Bladder Cancer

BACKGROUND: Optimal therapy for high-risk non-muscle invasive bladder cancer (NMIBC) includes intravesical instillation of Bacillus Calmette-Guérin (BCG). However, about 25-45% of patients do not benefit from BCG immunotherapy, and there is no biomarker to guide therapy. Also, many questions regarding BCG mechanisms of action remain unanswered. OBJECTIVE: To identify genomic biomarkers and characterize the underlying mechanism of benefit from BCG in NMIBC. PATIENTS AND METHODS: Pre-treatment archival index-tumors of 35 patients with NMIBC treated with BCG were analyzed by whole-exome sequencing (WES). Tumor mutation burden (TMB) and neoantigen load (NAL) were correlated with BCG response rate (RR) and recurrence-free survival (RFS). The presence of deleterious mutations in DNA damage response (DDR) genes was also compared between BCG-responsive (BCG-R, N = 17) and unresponsive (BCG-UR, N = 18) subgroups. RESULTS: TMB and NAL were higher in BCG-R compared to BCG-UR patients (median TMB 4.9 vs. 2.8 mutations/Mb, P = 0.017 and median NAL 100 vs. 65 neoantigens, P = 0.032). Improved RR and RFS were observed in patients with high vs. low TMB (RR 71% vs. 28%, P = 0.011 and mRFS 38.0 vs. 15.0 months, P = 0.009) and with high vs. low NAL (RR 71% vs. 28%, P = 0.011 and mRFS 36.0 vs. 18.5 months, P = 0.016). The presence of deleterious mutations in DDR genes was associated with improved RFS (mRFS 35.5 vs. 11.0 months, P = 0.017). CONCLUSIONS: In our cohort, improved outcomes after BCG immunotherapy were observed in patients with high TMB, high NAL and deleterious mutations in DDR genes. BCG may induce tumor-specific immune response by enhancing the recognition of neoantigens.

PhenoModifier: a genetic modifier database for elucidating the genetic basis of human phenotypic variation

From clinical observations to large-scale sequencing studies, the phenotypic impact of genetic modifiers is evident. To better understand the full spectrum of the genetic contribution to human disease, concerted efforts are needed to construct a useful modifier resource for interpreting the information from sequencing data. Here, we present the PhenoModifier (https://www.biosino.org/PhenoModifier), a manually curated database that provides a comprehensive overview of human genetic modifiers. By manually curating over ten thousand published articles, 3078 records of modifier information were entered into the current version of PhenoModifier, related to 288 different disorders, 2126 genetic modifier variants and 843 distinct modifier genes. To help users probe further into the mechanism of their interested modifier genes, we extended the yeast genetic interaction data and yeast quantitative trait loci to the human and we also integrated GWAS data into the PhenoModifier to assist users in evaluating all possible phenotypes associated with a modifier allele. As the first comprehensive resource of human genetic modifiers, PhenoModifier provides a more complete spectrum of genetic factors contributing to human phenotypic variation. The portal has a broad scientific and clinical scope, spanning activities relevant to variant interpretation for research purposes as well as clinical decision making.

Computer-aided biomarker discovery for precision medicine: data resources, models and applications

Biomarkers are a class of measurable and evaluable indicators with the potential to predict disease initiation and progression. In contrast to disease-associated factors, biomarkers hold the promise to capture the changeable signatures of biological states. With methodological advances, computer-aided biomarker discovery has now become a burgeoning paradigm in the field of biomedical science. In recent years, the 'big data' term has accumulated for the systematical investigation of complex biological phenomena and promoted the flourishing of computational methods for systems-level biomarker screening. Compared with routine wet-lab experiments, bioinformatics approaches are more efficient to decode disease pathogenesis under a holistic framework, which is propitious to identify biomarkers ranging from single molecules to molecular networks for disease diagnosis, prognosis and therapy. In this review, the concept and characteristics of typical biomarker types, e.g. single molecular biomarkers, module/network biomarkers, cross-level biomarkers, etc., are explicated on the guidance of systems biology. Then, publicly available data resources together with some well-constructed biomarker databases and knowledge bases are introduced. Biomarker identification models using mathematical, network and machine learning theories are sequentially discussed. Based on network substructural and functional evidences, a novel bioinformatics model is particularly highlighted for microRNA biomarker discovery. This article aims to give deep insights into the advantages and challenges of current computational approaches for biomarker detection, and to light up the future wisdom toward precision medicine and nation-wide healthcare.

KMT1 family methyltransferases regulate heterochromatin-nuclear periphery tethering via histone and non-histone protein methylation

Euchromatic histone methyltransferases (EHMTs), members of the KMT1 family, methylate histone and non-histone proteins. Here, we uncover a novel role for EHMTs in regulating heterochromatin anchorage to the nuclear periphery (NP) via non-histone methylation. We show that EHMTs methylate and stabilize LaminB1 (LMNB1), which associates with the H3K9me2-marked peripheral heterochromatin. Loss of LMNB1 methylation or EHMTs abrogates heterochromatin anchorage at the NP We further demonstrate that the loss of EHMTs induces many hallmarks of aging including global reduction of H3K27methyl marks and altered nuclear morphology. Consistent with this, we observe a gradual depletion of EHMTs, which correlates with loss of methylated LMNB1 and peripheral heterochromatin in aging human fibroblasts. Restoration of EHMT expression reverts peripheral heterochromatin defects in aged cells. Collectively, our work elucidates a new mechanism by which EHMTs regulate heterochromatin domain organization and reveals their impact on fundamental changes associated with the intrinsic aging process.

Long Non-coding RNA in Neuronal Development and Neurological Disorders

Long non-coding RNAs (lncRNAs) are transcripts which are usually more than 200 nt in length, and which do not have the protein-coding capacity. LncRNAs can be categorized based on their generation from distinct DNA elements, or derived from specific RNA processing pathways. During the past several decades, dramatic progress has been made in understanding the regulatory functions of lncRNAs in diverse biological processes, including RNA processing and editing, cell fate determination, dosage compensation, genomic imprinting and development etc. Dysregulation of lncRNAs is involved in multiple human diseases, especially neurological disorders. In this review, we summarize the recent progress made with regards to the function of lncRNAs and associated molecular mechanisms, focusing on neuronal development and neurological disorders.

Defining a Characteristic Gene Expression Set Responsible for Cancer Stem Cell-Like Features in a Sub-Population of Ewing Sarcoma Cells CADO-ES1

One of the still open questions in Ewing sarcoma, a rare bone tumor with weak therapeutic options, is to identify the tumor-driving cell (sub) population and to understand the specifics in the biological network of these cells. This basic scientific insight might foster the development of more specific therapeutic target patterns. The experimental approach is based on a side population (SP) of Ewing cells, based on the model cell line CADO-ES1. The SP is established by flow cytometry and defined by the idea that tumor stem-like cells can be identified by the time-course in clearing a given artificial dye. The SP was characterized by a higher colony forming activity, by a higher differentiation potential, by higher resistance to cytotoxic drugs, and by morphology. Several SP and non-SP cell fractions and bone marrow-derived mesenchymal stem cell reference were analyzed by short read sequencing of the full transcriptome. The double-differential analysis leads to an altered expression structure of SP cells centered around the AP-1 and APC/c complex. The SP cells share only a limited proportion of the full mesenchymal stem cell stemness set of genes. This is in line with the expectation that tumor stem-like cells share only a limited subset of stemness features which are relevant for tumor survival.

Current situation and future usage of anticancer drug databases

Cancer is a deadly disease with increasing incidence and mortality rates and affects the life quality of millions of people per year. The past 15 years have witnessed the rapid development of targeted therapy for cancer treatment, with numerous anticancer drugs, drug targets and related gene mutations been identified. The demand for better anticancer drugs and the advances in database technologies have propelled the development of databases related to anticancer drugs. These databases provide systematic collections of integrative information either directly on anticancer drugs or on a specific type of anticancer drugs with their own emphases on different aspects, such as drug-target interactions, the relationship between mutations in drug targets and drug resistance/sensitivity, drug-drug interactions, natural products with anticancer activity, anticancer peptides, synthetic lethality pairs and histone deacetylase inhibitors. We focus on a holistic view of the current situation and future usage of databases related to anticancer drugs and further discuss their strengths and weaknesses, in the hope of facilitating the discovery of new anticancer drugs with better clinical outcomes.

Heterogeneity in mechanisms of emergent resistance in pediatric T-cell acute lymphoblastic leukemia

Relapse in pediatric T-cell acute lymphoblastic leukemia (T-ALL) remains a significant clinical problem and is thought to be associated with clonal selection during treatment. In this study we used an established pre-clinical model of induction therapy to increase our understanding of the effect of engraftment and chemotherapy on clonal selection and acquisition of drug resistance in vivo. Immune-deficient mice were engrafted with patient diagnostic specimens and exposed to a repeated combination therapy consisting of vincristine, dexamethasone, L-asparaginase and daunorubicin. Any re-emergence of disease following therapy was shown to be associated with resistance to dexamethasone, no resistance was observed to the other three drugs. Immunoglobulin/T-cell receptor gene rearrangements closely matched those in respective diagnosis and relapse patient specimens, highlighting that these clonal markers do not fully reflect the biological changes associated with drug resistance. Gene expression profiling revealed the significant underlying heterogeneity of dexamethasone-resistant xenografts. Alterations were observed in a large number of biological pathways, yet no dominant signature was common to all lines. These findings indicate that the biological changes associated with T-ALL relapse and resistance are stochastic and highly individual, and underline the importance of using sophisticated molecular techniques or single cell analyses in developing personalized approaches to therapy.

Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine

Nowadays, the personalized approach to health care and cancer care in particular is becoming more and more popular and is taking an important place in the translational medicine paradigm. In some cases, detection of the patient-specific individual mutations that point to a targeted therapy has already become a routine practice for clinical oncologists. Wider panels of genetic markers are also on the market which cover a greater number of possible oncogenes including those with lower reliability of resulting medical conclusions. In light of the large availability of high-throughput technologies, it is very tempting to use complete patient-specific New Generation Sequencing (NGS) or other "omics" data for cancer treatment guidance. However, there are still no gold standard methods and protocols to evaluate them. Here we will discuss the clinical utility of each of the data types and describe a systems biology approach adapted for single patient measurements. We will try to summarize the current state of the field focusing on the clinically relevant case-studies and practical aspects of data processing.

EZH2-, CHD4-, and IDH-linked epigenetic perturbation and its association with survival in glioma patients

Glioma is a complex disease with limited treatment options. Recent advances have identified isocitrate dehydrogenase (IDH) mutations in up to 80% lower grade gliomas (LGG) and in 76% secondary glioblastomas (GBM). IDH mutations are also seen in 10%-20% of acute myeloid leukemia (AML). In AML, it was determined that mutations of IDH and other genes involving epigenetic regulations are early events, emerging in the pre-leukemic stem cells (pre-LSCs) stage, whereas mutations in genes propagating oncogenic signal are late events in leukemia. IDH mutations are also early events in glioma, occurring before TP53 mutation, 1p/19q deletion, etc. Despite these advances in glioma research, studies into other molecular alterations have lagged considerably. In this study, we analyzed currently available databases. We identified EZH2, KMT2C, and CHD4 as important genes in glioma in addition to the known gene IDH1/2. We also showed that genomic alterations of PIK3CA, CDKN2A, CDK4, FIP1L1, or FUBP1 collaborate with IDH mutations to negatively affect patients' survival in LGG. In LGG patients with TP53 mutations or IDH1/2 mutations, additional genomic alterations of EZH2, KMC2C, and CHD4 individually or in combination were associated with a markedly decreased disease-free survival than patients without such alterations. Alterations of EZH2, KMT2C, and CHD4 at genetic level or protein level could perturb epigenetic program, leading to malignant transformation in glioma. By reviewing current literature on both AML and glioma and performing bioinformatics analysis on available datasets, we developed a hypothetical model on the tumorigenesis from premalignant stem cells to glioma.

Exploring the epigenetic drug discovery landscape

INTRODUCTION

Epigenetic modification has been implicated in a wide range of diseases and the ability to modulate such systems is a lucrative therapeutic strategy in drug discovery. Areas covered: This article focuses on the concepts and drug discovery aspects of epigenomics. This is achieved by providing a survey of the following concepts: (i) factors influencing epigenetics, (ii) diseases arising from epigenetics, (iii) epigenetic enzymes as druggable targets along with coverage of existing FDA-approved drugs and pharmacological agents, and (iv) drug repurposing/repositioning as a means for rapid discovery of pharmacological agents targeting epigenetics. Expert opinion: Despite significant interests in targeting epigenetic modifiers as a therapeutic route, certain classes of target proteins are heavily studied while some are less characterized. Thus, such orphan target proteins are not yet druggable with limited report of active modulators. Current research points towards a great future with novel drugs directed to the many complex multifactorial diseases of humans, which are still often poorly understood and difficult to treat.

Targeting HDAC3 in CREBBP-Mutant Lymphomas Counterstrikes Unopposed Enhancer Deacetylation of B-cell Signaling and Immune Response Genes

The cellular phenotype of B-cell lymphomas arising from B cells undergoing germinal center reactions, such as follicular lymphoma and diffuse large B-cell lymphoma, is strongly shaped by mutations in chromatin-modifying genes. The work presented by Jiang and colleagues addresses how somatic mutations in CREBBP disable acetylation and cause unopposed deacetylation by BCL6/SMRT/HDAC3 complexes on enhancers of B-cell signaling and immune response genes. This opens a therapeutic avenue toward targeted inhibition of CREBBP-mutant lymphomas by HDAC inhibitors. Cancer Discov; 7(1); 14-6. ©2017 AACRSee related article by Jiang et al., p. 38.

Interactions Between Genetics, Lifestyle, and Environmental Factors for Healthcare

The occurrence and progression of diseases are strongly associated with a combination of genetic, lifestyle, and environmental factors. Understanding the interplay between genetic and nongenetic components provides deep insights into disease pathogenesis and promotes personalized strategies for people healthcare. Recently, the paradigm of systems medicine, which integrates biomedical data and knowledge at multidimensional levels, is considered to be an optimal way for disease management and clinical decision-making in the era of precision medicine. In this chapter, epigenetic-mediated genetics-lifestyle-environment interactions within specific diseases and different ethnic groups are systematically discussed, and data sources, computational models, and translational platforms for systems medicine research are sequentially presented. Moreover, feasible suggestions on precision healthcare and healthy longevity are kindly proposed based on the comprehensive review of current studies.