Meibomian Gland Carcinoma (MGC) is a highly malignant eyelid tumor with a poor prognosis. This study investigates the molecular mechanisms underlying MGC, focusing on the abnormal expression of E2F transcription factor 2 (E2F2), often observed in tumors and potentially linked to DNA methylation.

E2F2 expression was measured in MGC cells and tissues. Tissue samples from 3 normal meibomian glands (MG) and 36 MGC patients were used to construct a tissue microarray. Functional assays were performed by modifying E2F2 expression, including CCK8, wound healing, Transwell, and analysis of epithelial-mesenchymal transition (EMT)-related markers. Flow cytometry was used to assess cell apoptosis and cell cycle. RNA sequencing was conducted to identify differential genes after treating MGC cells with the methylation inhibitor 5-aza-2'-deoxycytidine (5-aza-2-dc), to explore the relationship between E2F2 downregulation in MGC and methylation.

E2F2 expression was significantly lower in MGC cells compared to normal MG cells. Immunohistochemical analysis showed low E2F2 expression in MGC. Specifically, immunohistochemical staining results have revealed a negative correlation trend between E2F2 and Ki-67 expression, as well as a positive correlation trend between E2F2 and P21, P27 expression. E2F2 knockdown increased MGC cell proliferation, migration, and invasion. Flow cytometry revealed that E2F2 knockdown reduced apoptosis, decreased the G0/G1 phase, and increased the S phase, while E2F2 overexpression produced opposite effects. RNA sequencing revealed that a total of 87 genes were differentially expressed in the 5-aza-2-dc experimental group compared to the control group, with 72 mRNAs showing upregulated expression and 15 mRNAs showing downregulated expression. Bioinformatics analysis results indicated that the functions of these differentially expressed genes were concentrated, and the biological processes mainly involved DNA replication, among others. The signaling pathways associated with these genes primarily included DNA replication and the cell cycle. RNA sequencing identified differential gene expression after methylation inhibition in MGC cells with 5-aza-2-dc, demonstrating that demethylation significantly upregulated E2F2. MSP assays confirmed reduced methylation levels. Additionally, inhibiting gene methylation in MGC cells suppressed proliferation, migration, and invasion.

E2F2 presents a promising therapeutic target for MGC. Overexpression of E2F2 and methylation inhibition in MGC cells may reverse E2F2 gene silencing, inhibiting malignant progression. These findings provide new perspectives for targeted therapies and precise, individualized treatment in MGC.

One of the key challenges in defeating advanced tumors is the ability of cancer cells to evade the selective pressure imposed by chemotherapy, targeted therapies, immunotherapy and cellular therapies. Both genetic and epigenetic alterations contribute to the development of resistance, allowing cancer cells to survive initially effective treatments. In this narration, we explore how genetic and epigenetic regulatory mechanisms influence the state of tumor cells and their responsiveness to different therapeutic strategies. We further propose that an altered balance between cell growth and cell death is a fundamental driver of drug resistance. Cell death programs exist in various forms, shaped by cell type, triggering factors, and microenvironmental conditions. These processes are governed by temporal and spatial constraints and appear to be more heterogeneous than previously understood. To capture the intricate interplay between death-inducing signals and survival mechanisms, we introduce the concept of Death-ision. This framework highlights the dynamic nature of cell death regulation, determining whether specific cancer cell clones evade or succumb to therapy. Building on this understanding offers promising strategies to counteract resistant clones and enhance therapeutic efficacy. For instance, combining DNMT inhibitors with immune checkpoint blockade may counteract YAP1-driven resistance or the use of transcriptional CDK inhibitors could prevent or overcome chemotherapy resistance. Death-ision aims to provide a deeper understanding of the diversity and evolution of cell death programs, not only at diagnosis but also throughout disease progression and treatment adaptation.

Recent advances in screening programs and the development of innovative therapeutic strategies have significantly improved the clinical outcomes of cancer patients. However, many patients still experience treatment failure, primarily due to inherent or acquired drug resistance mechanisms. This challenge underscores the urgent need for novel therapeutic targets for the effective treatment of malignancies, as well as cancer-specific biomarkers to enhance early diagnosis and guide interventions. Epigenetic mechanisms, including DNA methylation, have recently garnered growing interest as key regulators of gene expression under both physiological and pathological conditions. Although epigenetic dysregulations are reliable tumor hallmarks, DNA methylation is still not routinely integrated into clinical practice, highlighting the need for further research to translate preclinical findings from the bench to the bedside. On these bases, the present review aims to illustrate the state of the art regarding the role of DNA methylation in cancer, describing the technologies currently available for DNA methylation profiling. Furthermore, the latest evidence on the application of DNA methylation hotspots in cancer diagnosis and prognosis, as well as the impact of epidrugs in cancer care, is discussed to provide a comprehensive overview of the potential clinical relevance of DNA methylation in advancing personalized medicine.

Genomic analyses of cell-free DNA (cfDNA) in plasma are enabling noninvasive blood-based biomarker approaches to cancer detection and disease monitoring. Current approaches for identification of circulating tumour DNA typically use targeted tumour-specific mutations or methylation analyses. An emerging approach is based on the recognition of altered genome-wide cfDNA fragmentation in patients with cancer. Recent studies have revealed a multitude of characteristics that can affect the compendium of cfDNA fragments across the genome, collectively called the 'cfDNA fragmentome'. These changes result from genomic, epigenomic, transcriptomic and chromatin states of an individual and affect the size, position, coverage, mutation, structural and methylation characteristics of cfDNA. Identifying and monitoring these changes has the potential to improve early detection of cancer, especially using highly sensitive multi-feature machine learning approaches that would be amenable to broad use in populations at increased risk. This Review highlights the rapidly evolving field of genome-wide analyses of cfDNA characteristics, their comparison to existing cfDNA methods, and recent related innovations at the intersection of large-scale sequencing and artificial intelligence. As the breadth of clinical applications of cfDNA fragmentome methods have enormous public health implications for cancer screening and personalized approaches for clinical management of patients with cancer, we outline the challenges and opportunities ahead.

Gastrointestinal (GI) cancers impose a significant disease burden, underscoring the critical importance of accurate prognosis prediction and treatment response evaluation. DNA methylation, one of the most extensively studied epigenetic modifications, has gained prominence due to its reliable measurement across various sample types. Numerous studies have reported that DNA methylation was linked to the diagnosis, prognosis and treatment response in malignancies, including GI cancers. While its diagnostic role in GI cancers has been comprehensively reviewed. Recent research has increasingly highlighted its potential in prognosis prediction and treatment response evaluation. However, no existing reviews have exclusively focused on these two aspects. In this review, we retrieved relevant studies and included 230 of them in our discussion, thereby providing an overview of the clinical applicability of aberrant DNA methylation in these two fields among patients with esophageal, gastric, colorectal, pancreatic cancers, and hepatocellular carcinomas. Additionally, we discuss the limitations of the current literature and propose directions for future research. Specifically, we emphasize the need for standardized DNA methylation methodologies and advocate for the integration of gene panels, rather than single genes, to address tumor heterogeneity more effectively.

In this study, we propose an alternative approach for stratifying genome-scale DNA methylation profiles of gastrointestinal (GI) adenocarcinomas based on a robust analytical framework. A set of 978 GI adenocarcinomas and 120 adjacent normal tissues from public repositories was quality controlled and analyzed. Hierarchical consensus clustering of the tumors, based on differential epigenetic variability between malignant and normal samples, identified six distinct subtypes defined either by a pan-GI or a lower GI-specific phenotype. In addition to methylation levels, aberrant methylation frequencies and the degree of DNA methylation instability contributed to the characterization of each subtype. We found significant differences in the outcome of patients, with the poorest overall survival seen for those belonging to a pan-GI subtype with infrequent aberrant methylation. In conclusion, our standardized approach contributes to a refined characterization of the epigenetic heterogeneity in GI adenocarcinomas, offering insights into subtype-specific methylation with the potential to support prognostication.

Human endogenous retroviruses (HERVs) comprise approximately 8% of the human genome, integrated into the dynamic regulatory network of cellular potency during early embryonic development. In recent studies, resurgent the transcriptional activity of HERVs has been frequently observed in many types of human cancers, suggesting their potential functions in the occurrence and progression of malignancy. However, a dedicated web resource for querying the relationship between the activation of HERVs and cancer development is lacking. Here, we construct a database to explore the sequence information, expression profiles, survival prognosis, and genetic interactions of HERVs in diverse cancer types. Our database currently contains RNA sequencing data of 580 HERVs across 16,246 samples, including that of 6478 tumoral and 634 normal tissues, 932 cancer cell lines, as well as 151 early embryonic and 8051 human adult tissues. The primary goal is to provide an easily accessible and user-friendly database for professionals in the fields of bioinformatics, pathology, pharmacology, and related areas, enabling them to efficiently screen the activity of HERVs of interest in normal and cancerous tissues and evaluate the clinical relevance. The ERVcancer database is available at http://kyuanlab.com/ervcancer/.

De novo DNA methylation by DNMT3A is a fundamental epigenetic modification for transcriptional regulation. Histone tails and regulatory proteins regulate DNMT3A, and the crosstalk between these epigenetic mechanisms ensures appropriate DNA methylation patterning. Based on findings showing that Fos ecRNA inhibits DNMT3A activity in neurons, we sought to characterize the contribution of this regulatory RNA in the modulation of DNMT3A in the presence of regulatory proteins and histone tails.

We show that Fos ecRNA and mRNA strongly correlate in primary cortical neurons on a single cell level and provide evidence that Fos ecRNA modulation of DNMT3A at these actively transcribed sites occurs in a sequence-independent manner. Further characterization of the Fos ecRNA-DNMT3A interaction showed that Fos-1 ecRNA binds the DNMT3A tetramer interface and clinically relevant DNMT3A substitutions that disrupt the inhibition of DNMT3A activity by Fos-1 ecRNA are restored by the formation of heterotetramers with DNMT3L. Lastly, using DNMT3L and Fos ecRNA in the presence of synthetic histone H3 tails or reconstituted polynucleosomes, we found that regulatory RNAs play dominant roles in the modulation of DNMT3A activity.

Our results are consistent with a model for RNA regulation of DNMT3A that involves localized production of short RNAs binding to a nonspecific site on the protein, rather than formation of localized RNA/DNA structures. We propose that regulatory RNAs play a dominant role in the regulation of DNMT3A catalytic activity at sites with increased production of regulatory RNAs.

Poly (ADP-ribose) polymerase inhibitors (PARPi) are approved for Breast Cancer gene (BRCA)-mutant HER2- breast cancer, and there is clinical interest in expanding indications to include homologous recombination deficient (HRD) breast cancers. Yet, response in these populations remains variable, suggesting clinical utility in developing a better biomarker to select patients for PARPi and predict response. Here, we evaluate a radiolabeled PARPi, [18F]FluorThanatrace ([18F]FTT), as a functional biomarker of PARPi response in breast cancer.

A single-arm prospective observational trial was conducted at the University of Pennsylvania. [18F]FTT-PET uptake was measured in 24 women with untreated primary breast cancer and correlated with tumor HRD score. In a separate cohort of ten subjects with metastatic HER- breast cancer, [18F]FTT-PET uptake was measured at baseline and after a short interval on a PARPi (a measure of drug-target engagement) and correlated to progression free survival (PFS).

Here we show that baseline [18F]FTT-PET uptake does not correlate to HRD tissue score, supporting that [18F]FTT provides distinct information from genetic features. Baseline [18F]FTT-PET uptake and the change in uptake from baseline to after PARPi initiation significantly correlates to PFS in woman with breast cancer who received a PARPi (ρ = 0.74, P = 0.023 and ρ = -0.86, P = 0.012, respectively).

These early results suggest the potential of [18F]FTT-PET to select patients for PARPi treatment and monitor in vivo pharmacodynamics after therapy start. Absence of association with HRD scores supports [18F]FTT uptake as a novel measure that may be leveraged as a biomarker. Further studies are warranted.

Advances in multi-omics datasets and analytical methods have revolutionized cancer research, offering a comprehensive, pan-cancer perspective. Pan-cancer studies identify shared mechanisms and unique traits across different cancer types, which are reshaping diagnostic and treatment strategies. However, continued innovation is required to refine these approaches and deepen our understanding of cancer biology and medicine. This review summarized key findings from pan-cancer research and  explored their potential to drive future advancements in oncology.

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related mortality, primarily due to late stage at diagnosis. This review examines the multifaceted applications of liquid biopsy and circulating tumor DNA (ctDNA) analysis in the diagnosis and management of PDAC. We review the current literature on the technological advancements in liquid biopsy analysis such as next generation sequencing (NGS) and digital droplet PCR (ddPCR) as well as multi-omics technologies, highlighting their potential for accurate molecular subtyping through ctDNA analysis. This review highlights the significant role of ctDNA in the assessment of tumor behavior, disease subtyping, prediction and monitoring of treatment response, and evaluation of minimal residual disease. We discuss the implications of integrating liquid biopsy techniques into clinical practice as well as its challenges and limitations. By drawing insights from recent studies, this review aims to provide a comprehensive overview of how liquid biopsy and ctDNA analysis can enhance early disease management strategies in PDAC. We underscore the need for additional prospective studies and clinical trials to validate its feasibility and accuracy in order to establish clinical utility, with the ultimate goal of routine incorporation into practice to improve patient outcomes and transform the treatment landscape for PDAC.

Pancreatic adenocarcinoma (PAAD) is a highly lethal malignancy with an immunosuppressive microenvironment and a limited immunotherapy response. Cholesterol is necessary for rapid growth of cancer cells, and cholesterol metabolism reprogramming is a hallmark of PAAD. How PAAD cells initiate cholesterol reprogramming to sustain their growth demand and suppressive immunomicroenvironment remains elusive. In this study, we for the first time revealed that PAAD cells overcome cholesterol shortage and immune surveillance via ectopically overexpressing NPC1L1, a cholesterol transporter, but function as a two-pronged checkpoint, which not only directly suppresses TCR activation of CD8+T cells but also hijacks the intracellular cholesterol from CD8+T cells. In vivo, we showed that ezetimibe, an NPC1L1 inhibitor usually for hypercholesterolemia, efficiently prevented PAAD cells from depriving cholesterol of CD8+T cells, and improved the anti-tumor immunity of PAAD to synergize with PD-1 blockade, suggesting NPC1L1 as a promising target to rescue the anti-tumor activity in PAAD.

In cutaneous melanoma, epigenetic dysregulation is implicated in drug resistance and tumor immune escape. However, the epigenetic mechanisms that influence immune escape remain poorly understood. To elucidate how epigenetic dysregulation alters the expression of surface proteins that may be involved in drug targeting and immune escape, we performed a 3-dimensional surfaceome screen in primary melanoma cultures and identified the DNA-methyltransferase inhibitor decitabine as significantly upregulating the costimulatory molecule ICAM-1. By analyzing The Cancer Genome Atlas melanoma dataset, we further propose ICAM-1 upregulation on melanoma cells as a biomarker of a proinflammatory and antitumorigenic signature. Specifically, we showed that DNA-methyltransferase inhibitor administration upregulated the expression of the antigen-presenting machinery, HLA class I/II, as well as the secretion of the proinflammatory chemokines CXCL9 and CXCL10. Our in silico analysis on The Cancer Genome Atlas and ex vivo experiments on human primary melanoma samples revealed that increased ICAM-1 expression positively correlated with increased immunogenicity of human melanoma cells and correlated with increased immune cell infiltration. These findings suggest a therapeutic approach to modulate the immunogenic phenotype of melanoma cells, hence supporting the exploration of DNA-methyltransferase inhibitor as a potential inducer of infiltration in immunologically cold tumors.

Single-cell sequencing-based techniques are revolutionizing all fields of biomedical sciences, including normal kidney development and how this is disturbed in the development of Wilms tumor. The many different techniques and the differences between them can obscure which technique is best used to answer which question. In this review we summarize the techniques currently available, discuss which have been used in kidney development or Wilms tumor context, and which techniques can or should be combined to maximize the increase in biological understanding we can get from them.

Cancer heterogeneity is a major challenge in oncology, complicating diagnosis, prognostication, and treatment. The clinical heterogeneity of cancer, which leads to differential treatment outcomes between patients with histopathologically similar cancers, is attributable to molecular diversity manifesting through genetic, epigenetic, transcriptomic, microenvironmental, and host biology differences. Heterogeneity is observed between patients, individual metastases, and within individual lesions. This review discusses clinical implications of heterogeneity, emphasizing need for personalized approaches to overcome challenges posed by cancer's diverse presentations. Understanding of emerging molecular diagnostic and analytical techniques can provide a view into the multidimensional complexity of cancer heterogeneity. With over 90% of cancer-related deaths associated with metastasis, we additionally explore the role heterogeneity plays in treatment resistance and recurrence of metastatic lesions. Molecular insights from next-generation sequencing, single-cell transcriptomics, liquid biopsy technology, and artificial intelligence will facilitate the development of combination therapy regimens that can potentially induce lasting and even curative treatment outcomes.

DNA methylation is a crucial epigenetic modification that orchestrates chromatin remodelers that suppress transcription, and aberrations in DNA methylation result in a variety of conditions such as cancers and developmental disorders. While it is understood that methylation occurs at CpG-rich DNA regions, it is less understood how distinct methylation profiles are established within various cell types. In this work, we develop a molecular-transport model that depicts the genomic exploration of DNA methyltransferase within a multiscale DNA environment, incorporating biologically relevant factors like methylation rate and CpG density to predict how patterns are established. Our model predicts DNA methylation-state correlation distributions arising from the transport and kinetic properties that are crucial for the establishment of unique methylation profiles. We model the methylation correlation distributions of nine cancerous human cell types to determine how these properties affect the epigenetic profile. Our theory is capable of recapitulating experimental methylation patterns, suggesting the importance of DNA methyltransferase transport in epigenetic regulation. Through this work, we propose a mechanistic description for the establishment of methylation profiles, capturing the key behavioral characteristics of methyltransferase that lead to aberrant methylation.

The mitotic inheritability of DNA methylation as an epigenetic marker in higher-order eukaryotes has been established for >40 years. The DNA methylome and mitotic division interplay is now considered bidirectional and highly intertwined. Various epigenetic writers, erasers, and modulators shape the perceived replicative methylation dynamics. This Review surveys the principles and complexity of mitotic transmission of DNA methylation, emphasizing the awareness of mitotic aging in analyzing DNA methylation dynamics in development and disease. We reviewed how DNA methylation changes alter mitotic proliferation capacity, implicating age-related diseases like cancer. We link replicative epimutation to stem cell dysfunction, inflammatory response, cancer risks, and epigenetic clocks, discussing the causative role of DNA methylation in health and disease.

Multi-cancer early detection (MCED) through a single blood test significantly advances cancer diagnosis. However, most MCED tests rely on a single type of biomarkers, leading to limited sensitivity, particularly for early-stage cancers. We previously developed SPOT-MAS, a multimodal ctDNA-based assay analyzing methylation and fragmentomic profiles to detect five common cancers. Despite its potential, SPOT-MAS exhibited moderate sensitivities for early-stage cancers. This study investigated whether integrating hotspot mutations into SPOT-MAS could enhance its detection rates.

A targeted amplicon sequencing approach was developed to profile 700 hotspot mutations in cell-free DNA and integrated into the SPOT-MAS assay, creating a single-blood draw workflow. This workflow, namely SPOT-MAS Plus was retrospectively validated in a cohort of 255 non-metastatic cancer patients (breast, colorectal, gastric, liver, and lung) and 304 healthy individuals.

Hotspot mutations were detected in 131 of 255 (51.4%) cancer patients, with the highest rates in liver cancer (96.5%), followed by colorectal (59.3%) and lung cancer (53.7%). Lower detection rates were found for cancers with low tumor mutational burden, such as breast (31.3%) and gastric (41.9%) cancers. In contrast, SPOT-MAS demonstrated higher sensitivities for these cancers (51.6% for breast and 62.9% for gastric). The combination of hotspot mutations with SPOT-MAS predictions improved early-stage cancer detection, achieving an overall sensitivity of 78.5% at a specificity of 97.7%. Enhanced sensitivities were observed for colorectal (81.36%) and lung cancer (82.9%).

The integration of genetic and epigenetic alterations into a multimodal assay significantly enhances the early detection of various cancers. Further validation in larger cohorts is necessary to support broader clinical applications.

DNA methylation (DNAm) influences both sex differences and cancer development, yet the mechanisms connecting these factors remain unclear.

Utilizing data from The Cancer Genome Atlas, we conducted a comprehensive analysis of sex-related DNAm effects in nine non-reproductive cancers, compared to paired normal adjacent tissues (NATs), and validated the results using independent datasets. First, we assessed the extent of sex differential DNAm between cancers and NATs to explore how sex-related DNAm differences change in cancerous tissues. Next, we employed a multivariate adaptive shrinkage approach to model the covariance of cancer-related DNAm effects between sexes, aiming to elucidate how sex impacts aberrant DNAm patterns in cancers. Finally, we investigated correlations between the methylome and transcriptome to identify key signals driving sex-biased DNAm regulation in cancers.

Our analysis revealed a significant attenuation of sex differences in DNAm within cancerous tissues compared to baseline differences in normal tissues. We identified 3,452 CpGs (Pbonf < 0.05) associated with this reduction, with 72% of the linked genes involved in X chromosome inactivation. Through covariance analysis, we demonstrated that sex differences in cancer are predominantly driven by variations in the magnitude of shared DNAm signals, referred to as "amplification." Based on these patterns, we classified cancers into female- and male-biased groups and identified key CpGs exhibiting sex-specific amplification. These CpGs were enriched in binding sites of critical transcription factors, including P53, SOX2, and CTCF. Integrative multi-omics analyses uncovered 48 CpG-gene-cancer trios for females and 380 for males, showing similar magnitude differences in DNAm and gene expression, pointing to a sex-specific regulatory role of DNAm in cancer risk. Notably, several genes regulated by these trios were previously identified as drug targets for cancers, highlighting their potential as sex-specific therapeutic targets.

These findings advance our understanding of how sex, DNAm, and gene expression interact in cancer, offering insights into the development of sex-specific biomarkers and precision medicine.

Genome DNA methylation profiling is a promising yet costly method for cancer classification, involving substantial data. We developed an ensemble learning model to identify cancer types using methylation profiles from a limited number of CpG sites.

Analyzing methylation data from 890 samples across 10 cancer types from the TCGA database, we utilized ANOVA and Gain Ratio to select the most significant CpG sites, then employed Gradient Boosting to reduce these to just 100 sites.

This approach maintained high accuracy across multiple machine learning models, with classification accuracy rates between 87.7% and 93.5% for methods including Extreme Gradient Boosting, CatBoost, and Random Forest. This method effectively minimizes the number of features needed without losing performance, helping to classify primary organs and uncover subgroups within specific cancers like breast and lung.

Using a gradient boosting feature selector shows potential for streamlining methylation-based cancer classification.

The intricate expression patterns and oncogenic attributes of COL11A1 across different cancer types remain largely elusive. This study used several public databases (TCGA, GTEx, and CCLE) to investigate the pan-cancer landscape of COL11A1 expression, its prognostic implications, interplay with the immune microenvironment, and enriched signaling cascades. Concurrently, western blot analyses were performed to verify COL11A1 expression in lung adenocarcinoma (LUAD) cell lines and clinical samples. In addition, COL11A1 knockout cell lines were generated to scrutinize the functional consequences of COL11AI expression on cancer cell behavior by use MTT, colony formation, and scratch wound healing assays. A comprehensive database investigation revealed that COL11A1 was upregulated in a majority of tumor tissues and its expression was highly correlated with a patient's prognosis. Notably, genetic alterations in COL11A1 predominantly occurred as mutations, while its DNA methylation status inversely mirrored gene expression levels across multiple promoter regions. Our findings suggest that COL11A1 helps to modulate the tumor immune landscape and potentially acts through the epithelial-mesenchymal transition (EMT) pathway to exert its oncogenic function. Western blot analyses further substantiated the specific upregulation of COL11A1 in LUAD cell lines and tissues, suggesting a close association with the EMT process. Ablation of COL11A1 in cancer cells significantly reduced their proliferative, clonogenic, and migratory abilities, underscoring the functional significance of COL11A1 in tumor cell behavior. Collectively, this research revealed the prevalent overexpression of COL11A1 in pan-cancer tissues, its profound prognostic and microenvironmental correlations, and the mechanistic underpinnings of its tumor-promoting effects as mediated via EMT signaling. Our findings suggest that COL11A1 could serve as a prognostic and diagnostic biomarker and therapeutic target for cancer.

Alterations in DNA methylation profiles are typically found in cancer cells, combining genome-wide hypomethylation with hypermethylation of specific regions, such as CpG islands, which are normally unmethylated. Driving effects in cancer development have been associated with alteration of DNA methylation in certain regions, inducing, for example, the repression of tumor suppressor genes or the activation of oncogenes and retrotransposons. These alterations represent prime candidates for the development of specific markers for the detection, diagnosis and prognosis of cancer. In particular, these markers, distributed along the genome, provide a wealth of information that offers potential for innovation in the field of liquid biopsy, in particular thanks to the emergence of artificial intelligence for diagnostic purposes. This could overcome the limitations related to sensitivities and specificities, which remain too low for the most difficult applications in oncology: the detection of cancers at an early stage, the monitoring of residual disease and the analysis of brain tumors. In addition, targeting the enzymatic processes that control the epigenome offers new therapeutic strategies that could reverse the regulatory anomalies of these altered epigenomes.

Aberrant DNA methylation contributes to gene expression deregulation in cancer. However, these alterations' precise regulatory role and clinical implications are still not fully understood. In this study, we performed expression-methylation Quantitative Trait Loci (emQTL) analysis to identify deregulated cancer-driving transcriptional networks linked to CpG demethylation pan-cancer. By analyzing 33 cancer types from The Cancer Genome Atlas, we identified and confirmed significant correlations between CpG methylation and gene expression (emQTL) in cis and trans, both across and within cancer types. Bipartite network analysis of the emQTL revealed groups of CpGs and genes related to important biological processes involved in carcinogenesis including proliferation, metabolism and hormone-signaling. These bipartite communities were characterized by loss of enhancer methylation in specific transcription factor binding regions (TFBRs) and the CpGs were topologically linked to upregulated genes through chromatin loops. Penalized Cox regression analysis showed a significant prognostic impact of the pan-cancer emQTL in many cancer types. Taken together, our integrative pan-cancer analysis reveals a common architecture where hallmark cancer-driving functions are affected by the loss of enhancer methylation and may be epigenetically regulated.

High levels of LLT1 expression have been found in several cancers, where it interacts with CD161 on NK cells to facilitate tumor immune escape. Targeting LLT1 could potentially relieve this inhibitory signal and enhance anti-tumor responses mediated through NK cells. Using the 'The Cancer Genome Atlas' (TCGA) database, we investigated the role of LLT1 in the tumor microenvironment (TME) across various cancers. Identifying such biomarkers could create new therapeutic options for patients in addition to complementing existing immunotherapies.

LLT1 expression was evaluated in 33 cancers using TCGA transcriptome data. Univariate Cox regression analysis was employed to assess the correlation of LLT1 expression with patient survival. The relationship between LLT1 expression with immune infiltrates, immune gene signatures, and cancer genomic biomarkers (TMB, MSI, and MMR) was also investigated. Immunofluorescence studies were conducted to validate LLT1 expression in tumors. Furthermore, using the CRI iAtlas data, we evaluated LLT1 distribution and its correlation with other immune checkpoint genes in patients non-responsive to existing immune checkpoint therapies across multiple solid cancers.

High expression of LLT1 was observed in 12 cancers, including BRCA, CHOL, ESCA, GBM, HNSC, KIRC, KIRP, LIHC, LUAD, STAD, SARC, and PCPG. In certain cancers like COAD, KICH, and KIRC, high LLT1 expression was associated with poor prognosis. Further analysis revealed that upregulated LLT1 was associated with an abundance of NK and T cell infiltrates in the TME, as well as exhaustive immune biomarkers, and inversely associated with pro-inflammatory and tumor suppressor signatures. High LLT1 expression is also positively correlated with genomic biomarkers in certain cancers. Immunofluorescence studies confirmed moderate to high LLT1 expression in immune-resistant prostate cancer, glioma, ovarian cancer, and immune-sensitive liver cancer cell lines. An independent assessment of clinical cohorts from CRI iAtlas showed a correlation of upregulated LLT1 with multiple immunosuppressive genes in patients non-responsive to current ICIs.

The biomarker analysis revealed a clear association between elevated LLT1 expression and an immunosuppressive TME in patient cohorts from TCGA and clinical databases. Therefore, this study provides a foundation for utilizing LLT1 as a potential target to improve clinical responses in ICI non-responsive patients with upregulated LLT1.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, characterized by its aggressive progression and dismal prognosis. Advances in epigenetic profiling, specifically DNA methylation analysis, have significantly deepened our understanding of PDAC pathogenesis. This review synthesizes findings from recent genome-wide DNA methylation studies, which have delineated a complex DNA methylation landscape differentiating between normal and cancerous pancreatic tissues, as well as across various stages and molecular subtypes of PDAC. These studies identified specific differentially methylated regions (DMRs) that not only enhance our grasp of the epigenetic drivers of PDAC but also offer potential biomarkers for early diagnosis and prognosis, enabling the customization of therapeutic approaches. The review further explores how DNA methylation profiling could facilitate the development of subtype-tailored therapies, potentially improving treatment outcomes based on precise molecular characterizations. Overall, leveraging DNA methylation alterations as functional biomarkers holds promise for advancing our understanding of disease progression and refining PDAC management strategies, which could lead to improved patient outcomes and a deeper comprehension of the disease's underlying biological mechanisms.

Patients with stage II and III cutaneous primary melanoma vary considerably in their risk of melanoma-related death. We explore the ability of methylation profiling to distinguish primary melanoma methylation classes and their associations with clinicopathologic characteristics and survival.

InterMEL is a retrospective case-control study that assembled primary cutaneous melanomas from American Joint Committee on Cancer (AJCC) 8th edition stage II and III patients diagnosed between 1998 and 2015 in the United States and Australia. Cases are patients who died of melanoma within 5 years from original diagnosis. Controls survived longer than 5 years without evidence of melanoma recurrence or relapse. Methylation classes, distinguished by consensus clustering of 850K methylation data, were evaluated for their clinicopathologic characteristics, 5-year survival status, and differentially methylated gene sets.

Among 422 InterMEL melanomas, consensus clustering revealed three primary melanoma methylation classes (MethylClasses): a CpG island methylator phenotype (CIMP) class, an intermediate methylation (IM) class, and a low methylation (LM) class. CIMP and IM were associated with higher AJCC stage (both P = .002), Breslow thickness (CIMP P = .002; IM P = .006), and mitotic index (both P < .001) compared with LM, while IM had higher N stage than CIMP (P = .01) and LM (P = .007). CIMP and IM had a 2-fold higher likelihood of 5-year death from melanoma than LM (CIMP odds ratio [OR], 2.16 [95% CI, 1.18 to 3.96]; IM OR, 2.00 [95% CI, 1.12 to 3.58]) in a multivariable model adjusted for age, sex, log Breslow thickness, ulceration, mitotic index, and N stage. Despite more extensive CpG island hypermethylation in CIMP, CIMP and IM shared similar patterns of differential methylation and gene set enrichment compared with LM.

Melanoma MethylClasses may provide clinical value in predicting 5-year death from melanoma among patients with primary melanoma independent of other clinicopathologic factors.

Epithelial ovarian cancer (EOC) represents a significant health challenge, with high-grade serous ovarian cancer (HGSOC) being the most common subtype. Early detection is hindered by nonspecific symptoms, leading to late-stage diagnoses and poor survival rates. Biomarkers are crucial for early diagnosis and personalized treatment OBJECTIVE: Our goal was to develop a robust statistical procedure to identify a set of differentially methylated probes (DMPs) that would allow differentiation between HGSOC and benign ovarian tumors.

Using the Infinium EPIC Methylation array, we analyzed the methylation profiles of 48 ovarian samples diagnosed with HGSOC, borderline ovarian tumors, or benign ovarian disease. Through a multi-step statistical procedure combining univariate and multivariate logistic regression models, we aimed to identify CpG sites of interest.

We discovered 21 DMPs and developed a predictive model validated in two independent cohorts. Our model, using a distance-to-centroid approach, accurately distinguished between benign and malignant disease. This model can potentially be used in other types of sample material. Moreover, the strategy of the model development and validation can also be used in other disease contexts for diagnostic purposes.

Optimizing prevention and early detection of cancer requires understanding the number, types and timing of driver mutations. To quantify this, we exploited the elevated cancer incidence and mutation rates in germline BRCA1 and BRCA2 (gBRCA1/2) carriers. Using novel statistical models, we identify genomic deletions as the likely rate-limiting mutational processes, with 1-3 deletions required to initiate breast and ovarian tumors. gBRCA1/2-driven hereditary and sporadic tumors undergo convergent evolution to develop a similar set of driver deletions, and deletions explain the elevated cancer risk of gBRCA1/2-carriers. Orthogonal mutation timing analysis identifies deletions of chromosome 17 and 13q as early, recurrent events. Single-cell analyses confirmed deletion rate differences in gBRCA1/2 vs. non-carrier tumors as well as cells engineered to harbor gBRCA1/2. The centrality of deletion-associated chromosomal instability to tumorigenesis shapes interpretation of the somatic evolution of non-malignant tissue and guides strategies for precision prevention and early detection.

We currently face a sharp increase of T-cell acute lymphoblastic leukemia (T-ALL) incidence and a challenge of unmasking its complex etiology. The deoxycytidine analog 5-Aza-2'-deoxycytidine (5-Aza-dC) is currently the most common nucleoside methyltransferase inhibitor. The objective of this study was to clarify the role of 5-Aza-dC in T-ALL cell biological behaviors and phosphatase and tensin homolog deleted on chromosome ten (PTEN) expression.

T-ALL cell lines were divided into the experimental group with 5-Aza-dC solution treatment, and the control group without treatment. PTEN methylation was detected using methylation-specific polymerase chain reaction (MS-PCR). Following the measurement of cell proliferation, viability, apoptosis, invasion, migration, etc., quantitative reverse transcription-polymerase chain reaction (PCR) was conducted to detect PTEN, DNA methyl-transferases (DNMT1), DNMT3a, MBD2, and MeCP2 expressions; Western blot to detect PTEN, PI3K, AKT, and mTOR protein expressions. In addition, rescue experiments to inhibit and restore the expression of PTEN in different groups were performed for further identification of the results in the former parts.

MS-PCR results showed that in Jurkat cells, the target band was amplified using methylated primers for the PTEN gene promoter region; moreover, at 10 μmol/L of 5-Aza-dC for 24 h, PTEN methylation was completely removed without any un-methylated band observed. The experimental group had significantly lower cell proliferation and viability rates, higher apoptosis rates, decreased cell proportion in S phase, reduced invasion and migration; increased PTEN expression, decreased DNMT1, DNMT3a, MBD2, and MeCP2 mRNA expressions; and decreased PI3K, AKT, and mTOR protein expressions than those in the control group (all P < 0.05). Furthermore, according to the rescue experiment, silenced PTEN expression weakened the beneficial roles of 5-Aza-dC treatment, and resulted in significantly higher cell proliferation and viability rates, lower apoptosis rates, increased cell proportion in S phase, increased cell invasion and migration; decreased PTEN expression, elevated DNMT1, DNMT3a, MBD2, and MeCP2 mRNA expressions, and higher PI3K, AKT, and mTOR protein expressions (all P < 0.05). While restored PTEN expression enhanced functions of 5-Aza-dC treatment, leading to obviously lower cell proliferation and viability rates, higher apoptosis rates, increased cell proportion in G1 phase, and reduced cell invasion and migration; as well as increased PTEN expression, decreased DNMT1, DNMT3a, MBD2, and MeCP2 mRNA expressions, and lower PI3K, AKT, and mTOR protein expressions (all P < 0.05).

Demethylation treatment with 5-Aza-dC can inhibit T-ALL cell malignant biological behaviors and enhance the sensitivity to chemotherapy agents possibly, which may be related to the inhibited expressions of DNMT1, DNMT3a, MBD2, and MeCP2, and restored expression activity of PTEN to negatively regulate the PI3K/AKT signal transduction. Our silencing and restoration of PTEN expressions further support our findings, highlighting that demethylation with 5-Aza-dC to restore the anti-tumor activity of the tumor suppressor gene PTEN may be a promising therapeutic option for treating T-ALL.

Although cancer is an age-related disease, how the processes of aging contribute to cancer progression is not well understood. In this study, we uncovered how mouse B cell lymphoma develops as a consequence of a naturally aged system. We show here that this malignancy is associated with an age-associated clonal B cell (ACBC) population that likely originates from age-associated B cells. Driven by c-Myc activation, promoter hypermethylation and somatic mutations, IgM+ ACBCs clonally expand independently of germinal centers and show increased biological age. ACBCs become self-sufficient and support malignancy when transferred into young recipients. Inhibition of mTOR or c-Myc in old mice attenuates pre-malignant changes in B cells during aging. Although the etiology of mouse and human B cell lymphomas is considered distinct, epigenetic changes in transformed mouse B cells are enriched for changes observed in human B cell lymphomas. Together, our findings characterize the spontaneous progression of cancer during aging through both cell-intrinsic and microenvironmental changes and suggest interventions for its prevention.

Adenylate kinases (AKs) are important enzymes involved in cellular energy metabolism. Among AKs, AK5 (adenylate kinase 5), a cytosolic protein, is emerging as a significant contributor to various diseases and cellular processes. This comprehensive review integrates findings from various research groups on AK5 since its discovery, shedding light on its multifaceted roles in nucleotide metabolism, energy regulation, and cellular differentiation. We investigate its implications in a spectrum of diseases, including autoimmune encephalitis, epilepsy, neurodegenerative disorders such as Alzheimer's and Parkinson's, diabetes, lower extremity arterial disease, celiac disease, and various cancers. Notably, AK5's expression levels and methylation status have been associated with cancer progression and patient outcomes, indicating its potential as a prognostic indicator. Furthermore, AK5 is implicated in regulating cellular processes in breast cancer, gastric cancer, colorectal carcinoma, prostate cancer, and colon adenocarcinoma, suggesting its relevance across different cancer types. However, a limitation lies in the need for more robust clinical validation and a deeper understanding of AK5's precise mechanisms in disease pathogenesis, despite its association with various pathophysiological conditions. Nonetheless, AK5 holds promise as a therapeutic target, with emerging evidence suggesting its potential in therapy development.

Helicobacter pylori (H. pylori) infection is critical in the development and occurrence of gastric cancer. H. pylori secretes gamma-glutamyl transferase (GGT), which affects energy metabolism and histone methylation in mesenchymal stem cells. However, its effect on human gastric epithelial cells remains unclear. This study aimed to investigate the effects of GGT on energy metabolism and histone methylation in gastric epithelial cells and determine its role in the development and progression of H. pylori-induced gastric cancer.

A GGT knockout H. pylori strain and mouse gastric cancer model were constructed, and alpha-ketoglutarate (α-KG) was added. The underlying mechanism was investigated using proteomics, immunohistochemistry, Western blotting, and other experimental assays.

H. pylori can colonize the host's stomach and destroy the gastric epithelium. GGT secreted by H. pylori decreased the concentration of glutamine in the stomach and increased H3K9me3 and H3K27me3 expression, which promoted the proliferation and migration of gastric epithelial cells. Additionally, α-KG reversed this effect. GGT increased the tumorigenic ability of nude mice. GGT, secreted by H. pylori, promoted the expression of ribosomal protein L15 (RPL15), while GGT knockout and supplementation with α-KG and trimethylation inhibitors reduced RPL15 expression and Wnt signaling pathway expression.

H. pylori secreted GGT decreased the expression of glutamine and α-KG in gastric epithelial cells, increased the expression of histones H3K9me3 and H3K27me3, and activated the Wnt signaling pathway through RPL15 expression, ultimately changing the biological characteristics of the gastric epithelium and promoting the occurrence of gastric cancer. Altered energy metabolism and histone hypermethylation are important factors involved in this process.

Structural variation heavily influences the molecular landscape of cancer, in part by impacting DNA methylation-mediated transcriptional regulation. Here, using multi-omic datasets involving >2400 pediatric brain and central nervous system tumors of diverse histologies from the Children's Brain Tumor Network, we report hundreds of genes and associated CpG islands (CGIs) for which the nearby presence of somatic structural variant (SV) breakpoints is recurrently associated with altered expression or DNA methylation, respectively, including tumor suppressor genes ATRX and CDKN2A. Altered DNA methylation near enhancers associates with nearby somatic SV breakpoints, including MYC and MYCN. A subset of genes with SV-CGI methylation associations also have expression associations with patient survival, including BCOR, TERT, RCOR2, and PDLIM4. DNA methylation changes in recurrent or progressive tumors compared to the initial tumor within the same patient can predict survival in pediatric and adult cancers. Our comprehensive and pan-histology genomic analyses reveal mechanisms of noncoding alterations impacting cancer genes.

Ubiquitin-like with PHD and RING finger domains 1 (UHRF1) is an epigenetic regulator that plays critical roles in tumours. However, the DNA methylation alteration patterns driven by UHRF1 and the related differentially expressed tumour-related genes remain unclear. In this study, a UHRF1-shRNA MCF-7 cell line was constructed, and whole-genome bisulfite sequencing and RNA sequencing were performed. The DNA methylation alteration landscape was elucidated, and DNA methylation-altered regions (DMRs) were found to be distributed in both gene bodies and adjacent regions. The DMRs were annotated and categorized into 488 hypermethylated/1696 hypomethylated promoters and 1149 hypermethylated/5501 hypomethylated gene bodies. Through an integrated analysis with the RNA sequencing data, 217 methylation-regulated upregulated genes and 288 downregulated genes were identified, and these genes were primarily enriched in nervous system development and cancer signalling pathways. Further analysis revealed 21 downregulated oncogenes and 15 upregulated TSGs. We also showed that UHRF1 silencing inhibited cell proliferation and migration and suppressed tumour growth in vivo. Our study suggested that UHRF1 and the oncogenes or TSGs it regulates might serve as biomarkers and targets for breast cancer treatment.