MethHC: a database of DNA methylation and gene expression in human cancer

Genome wide identification of novel DNA methylation driven prognostic markers in colorectal cancer

Colorectal cancer (CRC) stands as a major contributor to cancer-related fatalities within China. There is an urgent need to identify accurate biomarkers for recurrence predicting in CRC. Reduced representation bisulfite sequencing was used to perform a comparative analysis of methylation profiles in tissue samples from 30 recurrence to 30 non-recurrence patients with CRC. Least absolute shrinkage and selection operator method was performed to select the differential methylation regions (DMRs) and built a DNA methylation classifier for predicting recurrence. Based on the identified top DMRs, a methylation classifier was built and consisted of eight hypermethylated DMRs in CRC. The DNA methylation classifier showed high accuracy for predicting recurrence with an area under the receiver operator characteristic curve of 0.825 (95% CI 0.680-0.970). The Kaplan-Meier survival analysis demonstrated that CRC patients with high methylation risk score, evaluated by the DNA methylation classifier, had poorer survival than low risk score (Hazard Ratio 4.349; 95% CI 1.783-10.61, P = 0.002). And only CRC patients with low methylation risk score could acquire benefit from adjuvant therapy. The DNA methylation classifier has been proved as crucial biomarkers for predicting recurrence and exhibited promising prognostic value after curative surgery in patients with CRC.

A review of big data technology and its application in cancer care

The development of modern medical devices and information technology has led to a rapid growth in the amount of data available for health protection information, with the concept of medical big data emerging globally, along with significant advances in cancer care relying on data-driven approaches. However, outstanding issues such as fragmented data governance, low-quality data specification, and data lock-in still make sharing challenging. Big data technology provides solutions for managing massive heterogeneous data while combining artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL) to better mine the intrinsic connections between data. This paper surveys and organizes recent articles on big data technology and its applications in cancer, dividing them into three different types to outline their primary content and summarize their critical role in assisting cancer care. It then examines the latest research directions in big data technology in cancer and evaluates the current state of development of each type of application. Finally, current challenges and opportunities are discussed, and recommendations are made for the further integration of big data technology into the medical industry in the future.

An epigenetic toolbox for conservation biologists

Ongoing climatic shifts and increasing anthropogenic pressures demand an efficient delineation of conservation units and accurate predictions of populations' resilience and adaptive potential. Molecular tools involving DNA sequencing are nowadays routinely used for these purposes. Yet, most of the existing tools focusing on sequence-level information have shortcomings in detecting signals of short-term ecological relevance. Epigenetic modifications carry valuable information to better link individuals, populations, and species to their environment. Here, we discuss a series of epigenetic monitoring tools that can be directly applied to various conservation contexts, complementing already existing molecular monitoring frameworks. Focusing on DNA sequence-based methods (e.g. DNA methylation, for which the applications are readily available), we demonstrate how (a) the identification of epi-biomarkers associated with age or infection can facilitate the determination of an individual's health status in wild populations; (b) whole epigenome analyses can identify signatures of selection linked to environmental conditions and facilitate estimating the adaptive potential of populations; and (c) epi-eDNA (epigenetic environmental DNA), an epigenetic-based conservation tool, presents a non-invasive sampling method to monitor biological information beyond the mere presence of individuals. Overall, our framework refines conservation strategies, ensuring a comprehensive understanding of species' adaptive potential and persistence on ecologically relevant timescales.

Krüppel-like Factor-9 and Krüppel-like Factor-13: Highly Related, Multi-Functional, Transcriptional Repressors and Activators of Oncogenesis

Specificity Proteins/Krüppel-like Factors (SP/KLF family) are a conserved family of transcriptional regulators. These proteins share three highly conserved, contiguous zinc fingers in their carboxy-terminus, requisite for binding to cis elements in DNA. Each SP/KLF protein has unique primary sequence within its amino-terminal and carboxy-terminal regions, and it is these regions which interact with co-activators, co-repressors, and chromatin-modifying proteins to support the transcriptional activation and repression of target genes. Krüppel-like Factor 9 (KLF9) and Krüppel-like Factor 13 (KLF13) are two of the smallest members of the SP/KLF family, are paralogous, emerged early in metazoan evolution, and are highly conserved. Paradoxically, while most similar in primary sequence, KLF9 and KLF13 display many distinct roles in target cells. In this article, we summarize the work that has identified the roles of KLF9 (and to a lesser degree KLF13) in tumor suppression or promotion via unique effects on differentiation, pro- and anti-inflammatory pathways, oxidative stress, and tumor immune cell infiltration. We also highlight the great diversity of miRNAs, lncRNAs, and circular RNAs which provide mechanisms for the ubiquitous tumor-specific suppression of KLF9 mRNA and protein. Elucidation of KLF9 and KLF13 in cancer biology is likely to provide new inroads to the understanding of oncogenesis and its prevention and treatments.

Comprehensive analysis of TLX2 in pan cancer as a prognostic and immunologic biomarker and validation in ovarian cancer

T cell leukemia homeobox 2 (TLX2) plays an important role in some tumors. Bioinformatics and experimental validation represent a useful way to explore the mechanisms and functions of TLX2 gene in the cancer disease process from a pan cancer perspective. TLX2 was aberrantly expressed in pan cancer and cell lines and correlated with clinical stage. High TLX2 expression was significantly associated with poor overall survival in COAD, KIRC, OC, and UCS. The greatest frequency of TLX2 alterations in pan cancer was amplification. Alterations of NXF2B, MSLNL, PCGF1, INO80B-WBP1, LBX2-AS1, MRPL53, LBX2, TTC31, WDR54, and WBP1 co-occurred in the TLX2 alteration group. PFS was significantly shorter in the TLX2-altered group (n = 6) compared to the TLX2-unaltered group (n = 400). Methylation levels of TLX2 were high in 17 tumors. TLX2 expression was associated with MSI in seven tumors and TMB in five tumors. TLX2 expression was associated with immune infiltration and immune checkpoint genes. TLX2 may be associated with some pathways and chemoresistance. We constructed a possible competing endogenous RNA (ceRNA) network of LINC01010/miR-146a-5p/TLX2 in OC. TLX2 expression was significantly upregulated in ovarian cancer cell lines compared to ovarian epithelial cell lines. Aberrant expression of TLX2 in pan cancer may promote tumorigenesis and progression through different mechanisms. TLX2 may represent an important therapeutic target for human cancers.

Expanding adverse outcome pathways towards one health models for nanosafety

The ever-growing production of nano-enabled products has generated the need for dedicated risk assessment strategies that ensure safety for humans and the environment. Transdisciplinary approaches are needed to support the development of new technologies while respecting environmental limits, as also highlighted by the EU Green Deal Chemicals Strategy for Sustainability and its safe and sustainable by design (SSbD) framework. The One Health concept offers a holistic multiscale approach for the assessment of nanosafety. However, toxicology is not yet capable of explaining the interaction between chemicals and biological systems at the multiscale level and in the context of the One Health framework. Furthermore, there is a disconnect between chemical safety assessment, epidemiology, and other fields of biology that, if unified, would enable the adoption of the One Health model. The development of mechanistic toxicology and the generation of omics data has provided important biological knowledge of the response of individual biological systems to nanomaterials (NMs). On the other hand, epigenetic data have the potential to inform on interspecies mechanisms of adaptation. These data types, however, need to be linked to concepts that support their intuitive interpretation. Adverse Outcome Pathways (AOPs) represent an evolving framework to anchor existing knowledge to chemical risk assessment. In this perspective, we discuss the possibility of integrating multi-level toxicogenomics data, including toxicoepigenetic insights, into the AOP framework. We anticipate that this new direction of toxicogenomics can support the development of One Health models applicable to groups of chemicals and to multiple species in the tree of life.

Efficiently quantifying DNA methylation for bulk- and single-cell bisulfite data

MOTIVATION

DNA CpG methylation (CpGm) has proven to be a crucial epigenetic factor in the mammalian gene regulatory system. Assessment of DNA CpG methylation values via whole-genome bisulfite sequencing (WGBS) is, however, computationally extremely demanding.

RESULTS

We present FAst MEthylation calling (FAME), the first approach to quantify CpGm values directly from bulk or single-cell WGBS reads without intermediate output files. FAME is very fast but as accurate as standard methods, which first produce BS alignment files before computing CpGm values. We present experiments on bulk and single-cell bisulfite datasets in which we show that data analysis can be significantly sped-up and help addressing the current WGBS analysis bottleneck for large-scale datasets without compromising accuracy.

AVAILABILITY AND IMPLEMENTATION

An implementation of FAME is open source and licensed under GPL-3.0 at https://github.com/FischerJo/FAME.

Analysis of the Prognostic and Immunological Role of HSPB1 in Pituitary Adenoma: A Potential Target for Therapy

Background and Objectives: The diagnosis and treatment of pituitary adenomas with cavernous sinus invasion pose significant challenges for clinicians. The objective of this study is to investigate the expression profile and prognostic value of HSPB1 (heat shock protein beta-1) in pituitary adenomas with invasive and non-invasive features. Additionally, we aim to explore the potential relationship between HSPB1 expression and immunological functions in pituitary adenoma. Materials and Methods: A total of 159 pituitary adenoma specimens (73 invasive tumours and 86 non-invasive tumours) underwent whole-transcriptome sequencing. Differentially expressed genes and pathways in invasive and non-invasive tumours were analysed. HSPB1 was subjected to adequate bioinformatics analysis using various databases such as TIMER, Xiantao and TISIDB. We investigated the correlation between HSPB1 expression and immune infiltration in cancers and predicted the target drug of HSPB1 using the TISIDB database. Results: HSPB1 expression was upregulated in invasive pituitary adenomas and affected immune cell infiltration. HSPB1 was significantly highly expressed in most tumours compared to normal tissues. High expression of HSPB1 was significantly associated with poorer overall survival. HSPB1 was involved in the regulation of the immune system in most cancers. The drugs DB11638, DB06094 and DB12695 could act as inhibitors of HSPB1. Conclusions: HSPB1 may serve as an important marker for invasive pituitary adenomas and promote tumour progression by modulating the immune system. Inhibitors of HSPB1 expression are currently available, making it a potential target for therapy in invasive pituitary adenoma.

Large-scale integration of the non-coding RNAs with DNA methylation in human cancers

Characterizing influences of DNA methylation (DNAm) on non-coding RNAs (ncRNAs) is important to understand the mechanisms of gene regulation and cancer outcome. In our study, we describe the results of ncRNA quantitative trait methylation sites (ncQTM) analyses on 8,545 samples from The Cancer Genome Atlas (TCGA), 763 samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and 516 samples from Genotype-Tissue Expression (GTEx) to identify the significant associations between DNAm sites and ncRNAs (miRNA, long non-coding RNA [lncRNA], small nuclear RNA [snRNA], small nucleolar RNA [snoRNA], and rRNA) across 32 cancer types. With more than 22 billion tests, we identify 302,764 cis-ncQTMs (6.28% of all tested) and 79,841,728 trans-ncQTMs (1.15% of all tested). Most DNAm sites (70.6% on average) are in trans association, while only 25.2% DNAm sites are in cis association. Further, we develop a subtype named ncm_cluster based on cancer-specific ncRNAs thatis associated with tumor microenvironment, clinical outcome, and biological pathways. To comprehensively describe the ncQTM patterns, we developed a database named Pancan-ncQTM (http://bigdata.njmu.edu.cn/Pancan-ncQTM/).

NTF4 plays a dual role in breast cancer in mammary tumorigenesis and metastatic progression

Breast cancer metastasis can happen even when the primary tumor is relatively small. But the mechanism for such early metastasis is poorly understood. Herein, we report that neurotrophin 4 (NTF4) plays a dual role in breast cancer proliferation and metastasis. Clinical data showed high levels of NTF4, especially in the early stage, to be associated with poor clinical outcomes, supporting the notion that metastasis, rather than primary cancer, was the major determinant of breast cancer mortality for patients. NTF4 promoted epithelial-mesenchymal transition (EMT), cell motility, and invasiveness of breast cancer cells in vitro and in vivo. Interestingly, NTF4 inhibited cell proliferation while promoting cellular apoptosis in vitro and inhibited xenograft tumorigenicity in vivo. Mechanistically, NTF4 elicited its pro-metastatic effects by activating PRKDC/AKT and ANXA1/NF-κB pathways to stabilize SNAIL protein, therefore decreasing the level of E-cadherin. Conversely, NTF4 increased ANXA1 phosphorylation and sumoylation and the interaction with importin β, leading to nuclear import and retention of ANXA1, which in turn activates the caspase-3 apoptosis cascade. Our findings identified an unexpected dual role for NTF4 in breast cancer which contributes to early metastasis of the disease. Therefore, NTF4 may serve as a prognostic marker and a potential therapeutic target for breast cancer.

Pan-Cancer Analysis of the Oncogenic and Prognostic Role of PKM2: A Potential Target for Survival and Immunotherapy

Background

No pan-cancer study has been conducted till date to explore the comprehensive oncogenic roles of pyruvate kinase M2 (PKM2).

Methods

TCGA, TIMER, GEPIA, UALCAN, STRING, and other databases were used to analyze the expression, prognostic roles, epigenetic variants, and possible oncogenic mechanisms of PKM2. Proteomic sequencing data and PRM were applied to validate.

Results

PKM2 showed higher expression in majority of cancers, the expression being significantly correlated with the clinical stage. Higher expression of PKM2 was associated with lower OS and DFS in several cancers, such as MESO and PAAD. In addition, the epigenetic variation of PKM2, including gene alteration, mutation type and sites, DNA methylation, and phosphorylation, showed diversity in different cancers. All four methods indicated that PKM2 is positively associated with the immune infiltration of tumor-associated fibroblasts, such as in THCA, GBM, and SARC. Further mechanistic exploration suggested that the ribosome pathway might play an essential role in the regulation of PKM2, and interestingly, four out of ten hub genes were found to be highly related to OS in several cancers. Finally, in thyroid cancer specimen, we validated the expression and potential mechanisms by proteomic sequencing and PRM validation.

Conclusion

In the majority of cancers, the higher expression of PKM2 was highly associated with poor prognosis. Further molecular mechanism exploration implied that PKM2 might serve as a potential target for cancer survival and immunotherapy by regulating the ribosome pathway.

DRAGON: Determining Regulatory Associations using Graphical models on multi-Omic Networks

The increasing quantity of multi-omic data, such as methylomic and transcriptomic profiles collected on the same specimen or even on the same cell, provides a unique opportunity to explore the complex interactions that define cell phenotype and govern cellular responses to perturbations. We propose a network approach based on Gaussian Graphical Models (GGMs) that facilitates the joint analysis of paired omics data. This method, called DRAGON (Determining Regulatory Associations using Graphical models on multi-Omic Networks), calibrates its parameters to achieve an optimal trade-off between the network's complexity and estimation accuracy, while explicitly accounting for the characteristics of each of the assessed omics 'layers.' In simulation studies, we show that DRAGON adapts to edge density and feature size differences between omics layers, improving model inference and edge recovery compared to state-of-the-art methods. We further demonstrate in an analysis of joint transcriptome - methylome data from TCGA breast cancer specimens that DRAGON can identify key molecular mechanisms such as gene regulation via promoter methylation. In particular, we identify Transcription Factor AP-2 Beta (TFAP2B) as a potential multi-omic biomarker for basal-type breast cancer. DRAGON is available as open-source code in Python through the Network Zoo package (netZooPy v0.8; netzoo.github.io).

CanMethdb: a database for genome-wide DNA methylation annotation in cancers

MOTIVATION

DNA methylation within gene body and promoters in cancer cells is well documented. An increasing number of studies showed that cytosine-phosphate-guanine (CpG) sites falling within other regulatory elements could also regulate target gene activation, mainly by affecting transcription factors (TFs) binding in human cancers. This led to the urgent need for comprehensively and effectively collecting distinct cis-regulatory elements and TF-binding sites (TFBS) to annotate DNA methylation regulation.

RESULTS

We developed a database (CanMethdb, http://meth.liclab.net/CanMethdb/) that focused on the upstream and downstream annotations for CpG-genes in cancers. This included upstream cis-regulatory elements, especially those involving distal regions to genes, and TFBS annotations for the CpGs and downstream functional annotations for the target genes, computed through integrating abundant DNA methylation and gene expression profiles in diverse cancers. Users could inquire CpG-target gene pairs for a cancer type through inputting a genomic region, a CpG, a gene name, or select hypo/hypermethylated CpG sets. The current version of CanMethdb documented a total of 38 986 060 CpG-target gene pairs (with 6 769 130 unique pairs), involving 385 217 CpGs and 18 044 target genes, abundant cis-regulatory elements and TFs for 33 TCGA cancer types. CanMethdb might help biologists perform in-depth studies of target gene regulations based on DNA methylations in cancer.

AVAILABILITY AND IMPLEMENTATION

The main program is available at https://github.com/chunquanlipathway/CanMethdb.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integrated analysis revealing the role of TET3-mediated MUC13 promoter hypomethylation in hepatocellular carcinogenesis

Aim: To explore the function and underlying mechanism of MUC13 in hepatocellular carcinoma (HCC) oncogenesis. Materials & Methods: Online databases and software were used to perform analyses of expression, methylation and enrichment pathway. Experiments were performed to confirm the results using HCC cells in vitro. Results: MUC13 was upregulated in HCC and liver cancer stem cells (CSCs) and had a positive influence on CSC generation. Further analyses revealed that MUC13 with promoter hypomethylated was regulated by DNA demethylase TET3, which was overexpressed in HCC and liver CSCs. Conclusion: These results strongly suggested that high TET3 expression in liver CSCs may mediate MUC13 upregulation via promoter hypomethylation and thereby contribute to hepatocellular carcinogenesis.

Prediction of the Effect of Methylation in the Promoter Region of ZP2 Gene on Egg Production in Jinghai Yellow Chickens

Egg production in chickens is a quantitative trait. The aim of this study was to investigate the effect of promoter methylation of the Zona pellucida 2 (ZP2) gene on egg production. Real-time fluorescence quantification showed that the expression of the ZP2 gene in the ovaries of 300-day-old Jinghai yellow chickens in the high-laying group was significantly higher than that in the low-laying group (p < 0.01). A series of deletion fragments of the ZP2 gene promoter in Jinghai yellow chickens had different promoter activities in DF-1 cells, and the core region of the ZP2 gene promoter was found to be between −1552 and −1348. Four CpG islands in the promoter region of the ZP2 gene were detected by software prediction. The overall degree of methylation of the ZP2-1 amplified fragment was negatively correlated with mRNA expression to some extent (R = −0.197); the overall degree of methylation of the ZP2-2 amplified fragment was also negatively correlated with mRNA expression to some extent (R = −0.264), in which the methylation of methylcytosine (mC)-9, mC-20, and mC-21 sites was significantly negatively correlated with mRNA expression (p < 0.05). In addition, the mC-20 and mC-21 sites are located on the Sp1 transcription factor binding site, and it is speculated that these two sites may be the main sites for regulating transcription. In summary, the methylation sites mC-20 and mC-21 of the ZP2 gene may inhibit the binding of Sp1 and DNA, affect the transcription of the ZP2 gene, and then affect the number of eggs produced by the Jinghai yellow chickens.

SHF Acts as a Novel Tumor Suppressor in Glioblastoma Multiforme by Disrupting STAT3 Dimerization

Sustained activation of signal transducer and activator of transcription 3 (STAT3) is a critical contributor in tumorigenesis and chemoresistance, thus making it an attractive cancer therapeutic target. Here, SH2 domain-containing adapter protein F (SHF) is identified as a tumor suppressor in glioblastoma Multiforme (GBM) and its negative regulation of STAT3 activity is characterized. Mechanically, SHF selectively binds and inhibits acetylated STAT3 dimerization without affecting STAT3 phosphorylation or acetylation. Additionally, by blocking STAT3-DNMT1 (DNA Methyltransferase 1) interaction, SHF relieves methylation of tumor suppressor genes. The SH2 domain is documented to be essential for SHF's actions on STAT3, and almost entirely replaces the functions of SHF on STAT3 independently. Moreover, the peptide C16 a peptide derived from the STAT3-binding sites of SHF inhibits STAT3 dimerization and STAT3/DNMT1 interaction, and achieves remarkable growth inhibition in GBM cells in vitro and in vivo. These findings strongly identify targeting of the SHF/STAT3 interaction as a promising strategy for developing an optimal STAT3 inhibitor and provide early evidence of the potential clinical efficacy of STAT3 inhibitors such as C16 in GBM.

Complement downregulation promotes an inflammatory signature that renders colorectal cancer susceptible to immunotherapy

BACKGROUND AND AIMS

The role of inflammatory immune responses in colorectal cancer (CRC) development and response to therapy is a matter of intense debate. While inflammation is a known driver of CRC, inflammatory immune infiltrates are a positive prognostic factor in CRC and predispose to response to immune checkpoint blockade (ICB) therapy. Unfortunately, over 85% of CRC cases are primarily unresponsive to ICB due to the absence of an immune infiltrate, and even the cases that show an initial immune infiltration can become refractory to ICB. The identification of therapy supportive immune responses in the field has been partially hindered by the sparsity of suitable mouse models to recapitulate the human disease. In this study, we aimed to understand how the dysregulation of the complement anaphylatoxin C3a receptor (C3aR), observed in subsets of patients with CRC, affects the immune responses, the development of CRC, and response to ICB therapy.

METHODS

We use a comprehensive approach encompassing analysis of publicly available human CRC datasets, inflammation-driven and newly generated spontaneous mouse models of CRC, and multiplatform high-dimensional analysis of immune responses using microbiota sequencing, RNA sequencing, and mass cytometry.

RESULTS

We found that patients' regulation of the complement C3aR is associated with epigenetic modifications. Specifically, downregulation of C3ar1 in human CRC promotes a tumor microenvironment characterized by the accumulation of innate and adaptive immune cells that support antitumor immunity. In addition, in vivo studies in our newly generated mouse model revealed that the lack of C3a in the colon activates a microbiota-mediated proinflammatory program which promotes the development of tumors with an immune signature that renders them responsive to the ICB therapy.

CONCLUSIONS

Our findings reveal that C3aR may act as a previously unrecognized checkpoint to enhance antitumor immunity in CRC. C3aR can thus be exploited to overcome ICB resistance in a larger group of patients with CRC.

Integrative analysis of DNA methylation and gene expression data for the diagnosis and underlying mechanism of Parkinson’s disease

Background

Parkinson’s disease (PD) is the second most common progressive neurodegenerative disorder and the leading cause of disability in the daily activities. In the management of PD, accurate and specific biomarkers in blood for the early diagnosis of PD are urgently needed. DNA methylation is one of the main epigenetic mechanisms and associated with the gene expression and disease initiation of PD. We aimed to construct a methylation signature for the diagnosis of PD patients, and explore the potential value of DNA methylation in therapeutic options.

Materials and methods

Whole blood DNA methylation and gene expression data of PD patients as well as healthy controls were extracted from Gene Expression Omnibus database. Next, differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between PD patients and healthy controls were identified. Least absolute shrinkage and selection operator cox regression analysis was carried out to construct a diagnostic signature based on the overlapped genes. And, the receiver operating characteristic (ROC) curves were drawn and the area under the curve (AUC) was used to assess the diagnostic performance of the signature in both the training and testing datasets. Finally, gene ontology and gene set enrichment analysis were subsequently carried out to explore the underlying mechanisms.

Results

We obtained a total of 9,596 DMGs, 1,058 DEGs, and 237 overlapped genes in the whole blood between PD patients and healthy controls. Eight methylation-driven genes (HIST1H4L, CDC42EP3, KIT, GNLY, SLC22A1, GCM1, INO80B, and ARHGAP26) were identified to construct the gene expression signature. The AUCs in predicting PD patients were 0.84 and 0.76 in training dataset and testing dataset, respectively. Additionally, eight methylation-altered CpGs were also identified to construct the CpGs signature which showed a similarly robust diagnostic capability, with AUCs of 0.8 and 0.73 in training dataset and testing dataset, respectively.

Conclusion

We conducted an integrated analysis of the gene expression and DNA methylation data, and constructed a methylation-driven genes signature and a methylation-altered CpGs signature to distinguish the patients with PD from healthy controls. Both of them had a robust prediction power and provide a new insight into personalized diagnostic and therapeutic strategies for PD.

Lycium barbarum polysaccharide modulates gut microbiota to alleviate rheumatoid arthritis in a rat model

Rheumatoid arthritis (RA) seriously impairs the quality of life of sufferers. It has been shown that Lycium barbarum polysaccharide (LBP), a natural active indigestible ingredient with medicinal and edible functions, can effectively relieve RA, however, whether this effect is related to gut microbiota is not known. This study aimed to explore the RA alleviating mechanism of LBP mediated by gut microbiota using a collagen-induced arthritis rat model. The results showed that LBP significantly changed the gut microflora structure accompanied with the RA alleviation. Specifically, a LBP intervention reduced the relative abundance of Lachnospiraceae_NK4A136_group and uncultured_bacterium_f_Ruminococcaceae and significantly increased the abundance of Romboutsia, Lactobacillus, Dubosiella and Faecalibaculum. The mRNA contents of several colonic epithelial genes including Dpep3, Gstm6, Slc27a2, Col11a2, Sycp2, SNORA22, Tnni1, Gpnmb, Mypn and Acsl6, which are potentially associated to RA, were down-regulated due to the DNA hypermethylation, possibly caused by the elevating content of a bacterial metabolite S-adenosyl methionine (SAM). In conclusion, our current study suggests that LBP alleviated RA by reshaping the composition of intestinal microflora which may generate SAM, inducing DNA hypermethylation of RA-related genes in the host intestinal epithelium and subsequently reducing their expression.

ATP and Adenosine Metabolism in Cancer: Exploitation for Therapeutic Gain

Adenosine is an evolutionary ancient metabolic regulator linking energy state to physiologic processes, including immunomodulation and cell proliferation. Tumors create an adenosine-rich immunosuppressive microenvironment through the increased release of ATP from dying and stressed cells and its ectoenzymatic conversion into adenosine. Therefore, the adenosine pathway becomes an important therapeutic target to improve the effectiveness of immune therapies. Prior research has focused largely on the two major ectonucleotidases, ectonucleoside triphosphate diphosphohydrolase 1/cluster of differentiation (CD)39 and ecto-5'-nucleotidase/CD73, which catalyze the breakdown of extracellular ATP into adenosine, and on the subsequent activation of different subtypes of adenosine receptors with mixed findings of antitumor and protumor effects. New findings, needed for more effective therapeutic approaches, require consideration of redundant pathways controlling intratumoral adenosine levels, including the alternative NAD-inactivating pathway through the CD38-ectonucleotide pyrophosphatase phosphodiesterase (ENPP)1-CD73 axis, the counteracting ATP-regenerating ectoenzymatic pathway, and cellular adenosine uptake and its phosphorylation by adenosine kinase. This review provides a holistic view of extracellular and intracellular adenosine metabolism as an integrated complex network and summarizes recent data on the underlying mechanisms through which adenosine and its precursors ATP and ADP control cancer immunosurveillance, tumor angiogenesis, lymphangiogenesis, cancer-associated thrombosis, blood flow, and tumor perfusion. Special attention is given to differences and commonalities in the purinome of different cancers, heterogeneity of the tumor microenvironment, subcellular compartmentalization of the adenosine system, and novel roles of purine-converting enzymes as targets for cancer therapy. SIGNIFICANCE STATEMENT: The discovery of the role of adenosine as immune checkpoint regulator in cancer has led to the development of novel therapeutic strategies targeting extracellular adenosine metabolism and signaling in multiple clinical trials and preclinical models. Here we identify major gaps in knowledge that need to be filled to improve the therapeutic gain from agents targeting key components of the adenosine metabolic network and, on this basis, provide a holistic view of the cancer purinome as a complex and integrated network.

KIF23 is a potential biomarker of diffuse large B cell lymphoma: Analysis based on bioinformatics and immunohistochemistry

Diffuse Large B Cell Lymphoma (DLBCL), the most common form of blood cancer. The genetic and clinical heterogeneity of DLBCL poses a major barrier to diagnosis and treatment. Hence, we aim to identify potential biomarkers for DLBCL.Differentially expressed genes were screened between DLBCL and the corresponding normal tissues. Kyoto Encyclopedia of Genes and Genomes and Gene oncology analyses were performed to obtain an insight into these differentially expressed genes. PPI network was constructed to identify hub genes. survival analysis was applied to evaluate the prognostic value of those hub genes. DNA methylation analysis was implemented to explore the epigenetic dysregulation of genes in DLBCL.In this study, Kinesin family member 23 (KIF23) showed higher expression in DLBCL and was identified as a risk factor in DLBCL. The immunohistochemistry experiment further confirmed this finding. Subsequently, the univariate and multivariate analysis indicated that KIF23 might be an independent adverse factor in DLBCL. Upregulation of KIF23 might be a risk factor for the overall survival of patients who received an R-CHOP regimen, in late-stage, whatever with or without extranodal sites. Higher expression of KIF23 also significantly reduced 3, 5, 10-year overall survival. Furthermore, functional enrichment analyses (Kyoto Encyclopedia of Genes and Genomes, Gene oncology, and Gene Set Enrichment Analysis) showed that KIF23 was mainly involved in cell cycle, nuclear division, PI3K/AKT/mTOR, TGF-beta, and Wnt/beta-catenin pathway in DLBCL. Finally, results of DNA methylation analysis indicated that hypomethylation in KIF23's promoter region might be the result of its higher expression in DLBCL.The findings of this study suggested that KIF23 is a potential biomarker for the diagnosis and prognosis of DLBCL. However, further studies were needed to validate these findings.

Tumor Expression Quantitative Trait Methylation Screening Reveals Distinct CpG Panels for Deconvolving Cancer Immune Signatures

DNA methylation signatures in tumors could serve as reliable biomarkers that are accessible in archival tissues for tracking the epigenetic dynamics shaped by both cancer cells and the tumor microenvironment. However, given the ultrahigh dimensionality and noncollapsible nature of the data, it remains challenging to screen all CpG sites to identify the most promising marker panels. In this article, we introduce the concept of tumor-based expression quantitative trait methylation (eQTM) for the prioritization and systematic mining of predictive biomarkers. In melanoma as a disease model, eQTM CpGs and genes represent new and efficient candidate targets to be investigated for both prognostic and immune status monitoring purposes. Three cis-eQTM CpGs (cg07786657, cg12446199, and cg00027570) were strongly associated with and can serve as surrogate biomarkers for the tumor immune cytolytic activity score (CYT). In addition, multiple eQTM genes could be further exploited for predicting immunoregulatory phenotypes. A targeted gene panel analysis identified one eQTM in TCF7 (cg25947408) as a novel candidate biomarker for uncoupling overall T-cell differentiation and exhaustion status in a tumor. The prognostic significance of this eQTM as an independent signature to CYT was validated by both The Cancer Genome Atlas and Moffitt melanoma cohort data. Overall, eQTMs represent a mechanistically distinct class of potential biomarkers that can be used to predict patient prognosis and immune status.

SIGNIFICANCE

This study provides a novel and promising approach to identify targeted epigenetic biomarkers in cancer and will spur further analysis in tumor immune phenotyping.

Construction of an APE1-Mediated Cascade Signal Amplification Platform for Homogeneously Sensitive and Rapid Measurement of DNA Methyltransferase in Escherichia coli Cells

DNA methylation is an essential genomic epigenetic behavior in both eukaryotes and prokaryotes. Deregulation of DNA methyltransferase (Dam MTase) can change the DNA methylation level and cause various diseases. Herein, we develop an apurinic/apyrimidinic endonuclease 1 (APE1)-mediated cascade signal amplification platform for homogeneously sensitive and rapid measurement of Dam MTase in Escherichia coli cells. This assay involves a partial double-stranded DNA (dsDNA) substrate and two hairpin signal probes (HP1 and HP2) that are modified with Cy5 and BHQ2 at two ends, respectively. When Dam MTase is present, it methylates the dsDNA substrate, and subsequently, endonuclease DpnI cleaves the methylated substrate, yielding trigger probe 1. Hybridization of trigger probe 1 with HP1 forms a partial dsDNA containing an apurinic/apyrimidinic (AP) site, which is cleaved by APE1 to induce the cyclic cleavage of HP1 and the production of abundant trigger probe 2. Subsequent hybridization of trigger probe 2 with HP2 forms a partial dsDNA with an AP site, inducing the cyclic cleavage of HP2 by APE1. Consequently, cyclic cleavage of HP1 and HP2 induces the generation of abundant Cy5 molecules, which are easily measured by single-molecule imaging. This assay can be performed homogeneously and rapidly within 2 h, which is the shortest among the reported amplification-based assays. Moreover, it exhibits good selectivity and high sensitivity, and it can discriminate Dam MTase from other enzymes and screen inhibitors. Importantly, it can accurately measure the Dam MTase activity in serum and E. coli cells, with promising applications in clinical diagnosis and drug discovery.

ImmuMethy, a database of DNA methylation plasticity at a single cytosine resolution in human blood and immune cells

Differential DNA methylation is a feature of numerous physiological and pathological processes. However, the extent to which single-base cytosine methylation modifies cellular responses to various stimuli has not been well characterized. In this study, we carried out a systematic analysis of methylome data derived from human blood and immune cells and constructed the ImmuMethy database. ImmuMethy allows interrogation of DNA methylation plasticity (MPL) at the single cytosine level. MPL, which refers to the variability of DNA methylation, is quantitatively measured in multiple ways, such as quartiles and standard deviations. ImmuMethy comprises over 36 000 samples from the Human Methylation450 and MethylationEPIC BeadChips platforms and provides multiple applications, such as an overview of methylation status and plasticity, differential methylation analysis, identification of methylation markers and sample stratification. An analysis of all datasets revealed that DNA methylation is generally stable, with minimal changes in beta values. This further supports the characteristics of DNA methylation homeostasis. Based on the beta value distribution, we identified three types of methylation sites: methylation tendency sites, unmethylation tendency sites and dual tendency or nonbiased methylation sites. These sites represent different methylation tendentiousness of DNA methylation across samples. The occurrence of multiple methylation tendencies in a site means split methylation, which generally corresponds to high MPL. Inverted methylation tendencies from methylation tendency sites to unmethylation tendency sites, or vice versa, represent strong differential methylation in response to conditions. All these sites can be identified in ImmuMethy, making it a useful tool for omics-based data-driven knowledge discovery.

Database URL: http://immudb.bjmu.edu.cn/immumethy/

Sinomenine increases the methylation level at specific GCG site in mPGES-1 promoter to facilitate its specific inhibitory effect on mPGES-1

Prostaglandin E₂ (PGE₂) in cancer and inflammatory diseases is a key mediator of disease progression. Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used to inhibit the expression of PGE₂ by depressing cyclooxygenase (COX) in inflammatory treatments. However, the inhibition to COXs may cause serious side effects. Thus, it is urgent to develop new anti-inflammatory drugs aiming new targets to inhibit PGE₂ production. Microsomal prostaglandin E synthase 1 (mPGES-1) catalyzes the final step of PGE₂ biosynthesis. Therefore, the selective inhibition of mPGES-1 has become a promising strategy in the treatments of cancer and inflammatory diseases. Our previous studies confirmed that sinomenine (SIN) is a specific mPGES-1 inhibitor. However, the exact mechanism by which SIN inhibits mPGES-1 remains unknown. This study aimed to explain the regulation effect of SIN to mPGES-1 gene expression by its DNA methylation induction effect. We found that the demethylating agent 5-azacytidine (5-AzaC) reversed the inhibitory effect of SIN to mPGES-1. Besides, SIN selectively increased the methylation level of the promoter region in the mPGES-1 gene while the pretreatment of 5-AzaC suppressed this effect. The results also shows that pretreatment with SIN increased the methylation level of specific GCG sites in the promoter region of mPGES-1. This specific methylation site may become a new biomarker for predicting and diagnosing RA and cancer with high expression of mPGES-1. Also, our research provides new ideas and solutions for clinical diagnosis and treatment of diseases related to mPGES-1 and for targeted methylation strategy in drug development.

The Mechanism and Prognostic Value of DNA Polymerase δ Subunits in Hepatocellular Carcinoma: Implications for Precision Therapy

PURPOSE

Polymerase δ (POLD) proteins is a pivotal B-family DNA polymerase in the process of genome replication and repair and are comprised of POLD1-4. The predictive value of POLDs in hepatocellular carcinoma (HCC) has not been evaluated until now.

PATIENTS AND METHODS

A total of 369 hepatocellular carcinoma samples and 50 adjacent normal samples were enrolled from the TCGA-LIHC database, and the GSE10186 database was also used. Transcription, methylation and genetic alteration status of HCC patients were evaluated by GEPIA, Kaplan-Meier plotter, cBioPortal, MethHC, MethSurv. SurvExpress was employed to generate the overall prognosis prediction signature of POLDs. POLDs coexpressed genes were explored and enriched in potential pathways. K-M curves were generated to compare the different survival results in different groups, while ROC curves were used to validate the efficiency of the POLD signature.

RESULTS

All four POLD subunits were highly expressed in HCC tumor tissues. POLD1-3 and increased mRNA levels were also positively associated with advanced tumor stage and OS prognosis. Methylation in the promoter of POLDs affects mRNA expression and OS, especially for some specific CpG sites. Meanwhile, POLDs could preferably predict the prognosis for patients who suffered from a high gene mutation burden. We evaluated the combined prognostic predictive value of four POLD subunits in both the TCGA-LIHC and GSE10186 databases and recognized the statistically significant HR of the high-risk group, along with the reliable predictive value. The coexpressed gene sets and annotation results showed that the POLD coexpressed genes were mostly associated with DNA repair and cell cycle regulation pathways.

CONCLUSION

POLD is an essential predictive factor for the prognosis of HCC. The united signature could precisely identify unfavorable clinical outcome of HCC.

Over-Expression and Prognostic Significance of FN1, Correlating With Immune Infiltrates in Thyroid Cancer

Background

Thyroid cancer (THCA) is a malignancy affecting the endocrine system, which currently has no effective treatment due to a limited number of suitable drugs and prognostic markers.

Methods

Three Gene Expression Omnibus (GEO) datasets were selected to identify differentially expressed genes (DEGs) between THCA and normal thyroid samples using GEO2R tools of National Center for Biotechnology Information. We identified hub gene FN1 using functional enrichment and protein-protein interaction network analyses. Subsequently, we evaluated the importance of gene expression on clinical prognosis using The Cancer Genome Atlas (TCGA) database and GEO datasets. MEXPRESS was used to investigate the correlation between gene expression and DNA methylation; the correlations between FN1 and cancer immune infiltrates were investigated using CIBERSORT. In addition, we assessed the effect of silencing FN1 expression, using an in vitro cellular model of THCA. Immunohistochemical(IHC) was used to elevate the correlation between CD276 and FN1.

Results

FN1 expression was highly correlated with progression-free survival and moderately to strongly correlated with the infiltration levels of M2 macrophages and resting memory CD4+ T cells, as well as with CD276 expression. We suggest promoter hypermethylation as the mechanism underlying the observed changes in FN1 expression, as 20 CpG sites in 507 THCA cases in TCGA database showed a negative correlation with FN1 expression. In addition, silencing FN1 expression suppressed clonogenicity, motility, invasiveness, and the expression of CD276 in vitro. The correlation between FN1 and CD276 was further confirmed by immunohistochemical.

Conclusion

Our findings show that FN1 expression levels correlate with prognosis and immune infiltration levels in THCA, suggesting that FN1 expression be used as an immunity-related biomarker and therapeutic target in THCA.

2-Hydroxyglutarate destabilizes chromatin regulatory landscape and lineage fidelity to promote cellular heterogeneity

The epigenome delineates lineage-specific transcriptional programs and restricts cell plasticity to prevent non-physiological cell fate transitions. Although cell diversification fosters tumor evolution and therapy resistance, upstream mechanisms that regulate the stability and plasticity of the cancer epigenome remain elusive. Here we show that 2-hydroxyglutarate (2HG) not only suppresses DNA repair but also mediates the high-plasticity chromatin landscape. A combination of single-cell epigenomics and multi-omics approaches demonstrates that 2HG disarranges otherwise well-preserved stable nucleosome positioning and promotes cell-to-cell variability. 2HG induces loss of motif accessibility to the luminal-defining transcriptional factors FOXA1, FOXP1, and GATA3 and a shift from luminal to basal-like gene expression. Breast tumors with high 2HG exhibit enhanced heterogeneity with undifferentiated epigenomic signatures linked to adverse prognosis. Further, ascorbate-2-phosphate (A2P) eradicates heterogeneity and impairs growth of high 2HG-producing breast cancer cells. These findings suggest 2HG as a key determinant of cancer plasticity and provide a rational strategy to counteract tumor cell evolution.

Kusi et al. show that the oncometabolite 2-hydroxyglutarate (2HG) initiates cell-level epigenome fluctuations in the chromatin regulatory landscape, accompanied by loss of lineage fidelity. Breast tumors with high 2HG accumulation exhibit enhanced cellular heterogeneity with undifferentiated stem-like epigenomic signatures. The findings suggest metabolic derangement as a molecular origin of breast cancer heterogeneity.

The EWAS Catalog: a database of epigenome-wide association studies

Epigenome-wide association studies (EWAS) seek to quantify associations between traits/exposures and DNA methylation measured at thousands or millions of CpG sites across the genome. In recent years, the increase in availability of DNA methylation measures in population-based cohorts and case-control studies has resulted in a dramatic expansion of the number of EWAS being performed and published. To make this rich source of results more accessible, we have manually curated a database of CpG-trait associations (with p<1x10 ^-4) from published EWAS, each assaying over 100,000 CpGs in at least 100 individuals. From January 7, 2022, The EWAS Catalog contained 1,737,746 associations from 2,686 EWAS. This includes 1,345,398 associations from 342 peer-reviewed publications. In addition, it also contains summary statistics for 392,348 associations from 427 EWAS, performed on data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Gene Expression Omnibus (GEO). The database is accompanied by a web-based tool and R package, giving researchers the opportunity to query EWAS associations quickly and easily, and gain insight into the molecular underpinnings of disease as well as the impact of traits and exposures on the DNA methylome. The EWAS Catalog is available at http://www.ewascatalog.org.

The EWAS Catalog: a database of epigenome-wide association studies

Epigenome-wide association studies (EWAS) seek to quantify associations between traits/exposures and DNA methylation measured at thousands or millions of CpG sites across the genome. In recent years, the increase in availability of DNA methylation measures in population-based cohorts and case-control studies has resulted in a dramatic expansion of the number of EWAS being performed and published. To make this rich source of results more accessible, we have manually curated a database of CpG-trait associations (with p<1x10 ^-4) from published EWAS, each assaying over 100,000 CpGs in at least 100 individuals. From January 7, 2022, The EWAS Catalog contained 1,737,746 associations from 2,686 EWAS. This includes 1,345,398 associations from 342 peer-reviewed publications. In addition, it also contains summary statistics for 392,348 associations from 427 EWAS, performed on data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Gene Expression Omnibus (GEO). The database is accompanied by a web-based tool and R package, giving researchers the opportunity to query EWAS associations quickly and easily, and gain insight into the molecular underpinnings of disease as well as the impact of traits and exposures on the DNA methylome. The EWAS Catalog data extraction team continue to update the database monthly and we encourage any EWAS authors to upload their summary statistics to our website. Details of how to upload data can be found here: http://www.ewascatalog.org/upload. The EWAS Catalog is available at http://www.ewascatalog.org.

The EWAS Catalog: a database of epigenome-wide association studies

Epigenome-wide association studies (EWAS) seek to quantify associations between traits/exposures and DNA methylation measured at thousands or millions of CpG sites across the genome. In recent years, the increase in availability of DNA methylation measures in population-based cohorts and case-control studies has resulted in a dramatic expansion of the number of EWAS being performed and published. To make this rich source of results more accessible, we have manually curated a database of CpG-trait associations (with p<1x10 ^-4) from published EWAS, each assaying over 100,000 CpGs in at least 100 individuals. From January 7, 2022, The EWAS Catalog contained 1,737,746 associations from 2,686 EWAS. This includes 1,345,398 associations from 342 peer-reviewed publications. In addition, it also contains summary statistics for 392,348 associations from 427 EWAS, performed on data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Gene Expression Omnibus (GEO). The database is accompanied by a web-based tool and R package, giving researchers the opportunity to query EWAS associations quickly and easily, and gain insight into the molecular underpinnings of disease as well as the impact of traits and exposures on the DNA methylome. The EWAS Catalog data extraction team continue to update the database monthly and we encourage any EWAS authors to upload their summary statistics to our website. Details of how to upload data can be found here: http://www.ewascatalog.org/upload. The EWAS Catalog is available at http://www.ewascatalog.org.

An integrated analysis of DNA promoter methylation, microRNA regulation, and gene expression in gastric adenocarcinoma

Background

Gastric adenocarcinoma (GAC), a common type of gastric cancer, poses a significant public health threat worldwide. This study aimed to determine the transcriptional regulatory mechanisms of GAC.

Methods

HTSeq-FPKM raw data were obtained from The Cancer Genome Atlas Stomach Adenocarcinoma data collection. Subsequently, the limma package in R was used to identify differentially expressed genes (DEGs). Differentially methylated genes (DMGs), DEGs, and differentially expressed microRNAs (miRNAs) in normal, and tumor tissues of the same patients were screened and compared using R software tools. A functional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) for various DEGs, DMGs, promoter methylation, and miRNAs. DEG-specific methylation and transcription factors were analyzed using ENCODE ChIP-seq.

Results

DEGs were centrally modified by the histone trimethylation of lysine 27 on histone H3 (H3K27me3). Upstream transcription factors of DEGs were enriched in different ChIP-seq clusters, such as Forkhead Box M1, E2F Transcription Factor 4, and suppressor of zest 12. Integrated regulatory networks of DEGs, promoter methylation, and miRNAs were constructed. Two miRNAs (hsa-mir-1 and hsa-mir-133a) and four DEGs (A disintegrin and metalloproteinase domain 12, transcription factor AP-2 alpha, solute carrier family 5 member 7, and cadherin 19) separately played important roles in the integrated regulatory network. Therefore, these DEGs, DMGs, promoter methylation, and miRNAs may play an important role in GAC pathogenesis.

Conclusions

In summary, the present study results provide insights into the oncogenesis and progression of GAC, thus accelerating the development of novel targeted GAC therapies.

Loss of FBXO31-mediated degradation of DUSP6 dysregulates ERK and PI3K-AKT signaling and promotes prostate tumorigenesis

FBXO31 is the substrate receptor of one of many CUL1-RING ubiquitin ligase (CRL1) complexes. Here, we show that low FBXO31 mRNA levels are associated with high pre-operative prostate-specific antigen (PSA) levels and Gleason grade in human prostate cancer. Mechanistically, the ubiquitin ligase CRL1FBXO31 promotes the ubiquitylation-mediated degradation of DUSP6, a dual specificity phosphatase that dephosphorylates and inactivates the extracellular-signal-regulated kinase-1 and -2 (ERK1/2). Depletion of FBXO31 stabilizes DUSP6, suppresses ERK signaling, and activates the PI3K-AKT signaling cascade. Moreover, deletion of FBXO31 promotes tumor development in a mouse orthotopic model of prostate cancer. Treatment with BCI, a small molecule inhibitor of DUSP6, suppresses AKT activation and prevents tumor formation, suggesting that the FBXO31 tumor suppressor activity is dependent on DUSP6. Taken together, our studies highlight the relevance of the FBXO31-DUSP6 axis in the regulation of ERK- and PI3K-AKT-mediated signaling pathways, as well as its therapeutic potential in prostate cancer.

Silencing of MBD2 and EZH2 inhibits the proliferation of colorectal carcinoma cells by rescuing the expression of SFRP

The secreted frizzled related proteins (SFRPs) are extracellular inhibitors of WNT pathway signaling. Methyl-CpG binding domain protein 2 (MBD2) and enhancer of zeste homolog 2 (EZH2) are core members of the methylated DNA binding domain (MBD) and polycomb group (PcG) protein families for epigenetic regulation, respectively. This study aimed to ascertain the potential role of MBD2 and EZH2 proteins in colorectal cancer (CRC) and its effects on the expression of SFRP. Bioinformatics, real-time quantitative polymerase chain reaction (qPCR) and western blot analysis were used to detect the expression of MBD2, EZH2, and SFRP in CRC cell lines and tissues. The functions of MBD2 and EZH2 in regards to cell proliferation, cell cycle distribution, apoptosis and invasion were examined in CRC cell lines. Methylation-specific PCR (MSP) was used to detect the methylation status of the SFRP promoter. The results revealed that the mRNA expression levels of SFRP were significantly decreased in CRC tissues and cell lines compared to these levels in the adjacent tissues and NCM460, respectively. However, the mRNA levels of EZH2 and MBD2 genes were highly expressed in CRC cell lines. We found that reducing MBD2 and EZH2 expression together remarkably inhibited and decreased the proliferation, migration and invasion abilities of the CRC cell lines compared to reducing one of each. Flow cytometric analysis showed that knockdown of MBD2 and EZH2 together in CRC affected cell apoptosis and the cell cycle progression more effectively than knockdown of one of each. The mRNA expression of SFRP1 was reactivated by silencing of MBD2 but not EZH2 in SW480 and HCT116 cells. SFRP4 and SFRP5 mRNA expression was reactivated by silencing of EZH2 but not MBD2 only in SW480 cells. However, depletion of both MBD2 and EZH2 restored SFRP1, SFRP2, SFRP4, and SFRP5 mRNA expression more effectively in CRC cells. Interestingly, there was no significant change in the methylation status of SFRP1, SFRP2, SFRP4, and SFRP5 gene promoter between before and after interference with MBD2, EZH2, and both. In conclusion, our results suggest that silencing of MBD2 and EZH2 simultaneously was able to rescue the expression of SFRP and inhibit the proliferation of CRC cells more effectively. However, the underlying regulatory mechanism system of MBD2 and EZH2 for SFRP in CRC requires further research.

Air pollution-induced epigenetic changes: disease development and a possible link with hypersensitivity pneumonitis

Air pollution is a serious threat to our health and has become one of the major causes of many diseases including cardiovascular disease, respiratory disease, and cancer. The association between air pollution and various diseases has long been a topic of research interest. However, it remains unclear how air pollution actually impacts health by modulating several important cellular functions. Recently, some evidence has emerged about air pollution-induced epigenetic changes, which are linked with the etiology of various human diseases. Among several epigenetic modifications, DNA methylation represents the most prominent epigenetic alteration underlying the air pollution-induced pathogenic mechanism. Several other types of epigenetic changes, such as histone modifications, miRNA, and non-coding RNA expression, have also been found to have been linked with air pollution. Hypersensitivity pneumonitis (HP), one of the most prevalent forms of interstitial lung diseases (ILDs), is triggered by the inhalation of certain organic and inorganic substances. HP is characterized by inflammation in the tissues around the lungs' airways and may lead to irreversible lung scarring over time. This review, in addition to other diseases, attempts to understand whether certain pollutants influence HP development through such epigenetic modifications.

Integrated analysis of Solute carrier family-2 members reveals SLC2A4 as an independent favorable prognostic biomarker for breast cancer

Most of Solute carrier family-2 (SLC2) members play a key role of facilitative transporters, and glucose transporter (GLUT) proteins encoded by SLC2s can transport hexoses or polyols. However, the function and mechanism of SLC2s remain unclear in human cancers. Here, we explored the dysregulated expression, prognostic values, epigenetic, genetic alterations, and biomolecular network of SLC2s in human cancers. According to the data from public-omicsrepository, SLC2A4 (GLUT4) was found to be significantly downregulated in most cancers, and higher messenger RNA (mRNA) expression of SLC2A4 significantly associated with better prognosis of breast cancer (BRCA) patients. Moreover, DNA hypermethylation in the promoter of SLC2A4 may affect the regulation of its mRNA expression, and SLC2A4 was strongly correlated with pathways, including the translocation of SLC2A4 to the plasma membrane and PID INSULIN PATHWAY. In conclusion, these results provide insight into SLC2s in human cancers and suggest that SLC2A4 could be an unfavorable prognostic biomarker for the survival of BRCA patients.

Identification of the molecular function of tripartite motif containing 58 in human lung cancer

Lung cancer is a major public health problem worldwide, with a high associated incidence and mortality. In the present study, novel epigenetic signatures were identified through genome-wide DNA methylation microarrays. The results revealed that tripartite motif containing 58 (TRIM58), a potential tumor suppressor gene exhibited high methylation and low expression in lung cancer tissue samples compared with normal tissues. Receiver operating characteristic curve analysis demonstrated that TRIM58 may be a promising early diagnostic indicator of lung cancer. In addition, the present study analyzed the role of TRIM58 in tumorigenesis and development in lung cancer A549 cells. Wound healing assay and transwell migration assay were used to investigate cell migration, and flow cytometry analysis was used to detect apoptosis. Silencing TRIM58 accelerated the proliferation and migration of lung cancer cells. In contrast, the overexpression of TRIM58 significantly inhibited the proliferation and migration of lung cancer cells and promoted apoptosis. Gene set enrichment analysis revealed that TRIM58 expression was negatively correlated with MYC targets, G₂M checkpoints and the mTORC1 signaling pathway. These results of the present study suggested that TRIM58, a potential tumor suppressor gene may serve as a novel diagnostic biomarker and therapeutic target in human lung cancer.

Integrated Bioinformatics Analysis of DNA Methylation Biomarkers in Thyroid Cancer Based on TCGA Database

Previous studies have reported a cluster of aberrant promoter methylation changes associated with silencing of tumor suppressor genes in thyroid cancer (TC), but these results of individual genes are far from enough. In this work, we aimed to investigate the onset and pattern of methylation changes during the progression of TC by informatics analysis. We downloaded the DNA methylation and RNA sequencing datasets from The Cancer Genome Atlas focusing on TC. Abnormally methylated differentially expressed genes (DEGs) were sorted and pathways were analyzed. The KEGG and GO were then used to perform enrichment and functional analysis of identified pathways and genes. Gene-drug interaction network and human protein atlas were applied to obtain feature DNA methylation biomarkers. In total, we identified 2170 methylation-driven DEGs, including 1054 hypermethylatedlow-expression DEGs and 1116 hypomethylated-high-expression DEGs at the screening step. Further analysis screened total of eight feature DNA methylation biomarkers (RXRG, MET, PDGFRA, FCGR3A, VEGFA, CSF1R, FCGR1A and C1QA). Pathway analysis showed that aberrantly methylated DEGs mainly associated with transcriptional misregulation in cancer, MAPK signaling, and intrinsic apoptotic signaling in TC. Taken together, we have identified novel aberrantly methylated genes and pathways linked to TC, which might serve as novel biomarkers for precision diagnosis and disease treatment.

IUSMMT: Survival mediation analysis of gene expression with multiple DNA methylation exposures and its application to cancers of TCGA

Effective and powerful survival mediation models are currently lacking. To partly fill such knowledge gap, we particularly focus on the mediation analysis that includes multiple DNA methylations acting as exposures, one gene expression as the mediator and one survival time as the outcome. We proposed IUSMMT (intersection-union survival mixture-adjusted mediation test) to effectively examine the existence of mediation effect by fitting an empirical three-component mixture null distribution. With extensive simulation studies, we demonstrated the advantage of IUSMMT over existing methods. We applied IUSMMT to ten TCGA cancers and identified multiple genes that exhibited mediating effects. We further revealed that most of the identified regions, in which genes behaved as active mediators, were cancer type-specific and exhibited a full mediation from DNA methylation CpG sites to the survival risk of various types of cancers. Overall, IUSMMT represents an effective and powerful alternative for survival mediation analysis; our results also provide new insights into the functional role of DNA methylation and gene expression in cancer progression/prognosis and demonstrate potential therapeutic targets for future clinical practice.

DNA methylation biomarkers for diagnosis of primary liver cancer and distinguishing hepatocellular carcinoma from intrahepatic cholangiocarcinoma

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the two most common pathology subtypes of primary liver cancer (PLC). Identifying DNA methylation biomarkers for diagnosis of PLC and further distinguishing HCC from ICC plays a vital role in subsequent treatment options selection. To obtain potential diagnostic DNA methylation sites for PLC, differentially methylated CpG (DMC) sites were first screened by comparing the methylation data between normal liver samples and PLC samples (ICC samples and HCC samples). A random forest algorithm was then used to select specific DMC sites with top Gini value. To avoid overfitting, another cohort was taken as an external validation for evaluating the area under curves (AUCs) of different DMC sites combination. A similar model construction strategy was applied to distinguish HCC from ICC. In addition, we identified DNA Methylation-Driven Genes in HCC and ICC via MethylMix method and performed pathway analysis by utilizing MetaCore. Finally, we not only performed methylator phenotype based on independent prognostic sites but also analyzed the correlations between methylator phenotype and clinical factors in HCC and ICC, respectively. To diagnose PLC, we developed a model based on three PLC-specific methylation sites (cg24035245, cg21072795, and cg00261162), whose sensitivity and specificity achieved 98.8%,94.8% in training set and 97.3%,81% in validation set. Then, to further divide the PLC samples into HCC and ICC, we established another mode through three methylation sites (cg17769836, cg17591574, and cg07823562), HCC accuracy and ICC accuracy achieved 95.8%, 89.8% in the training set and 96.8%,85.4% in the validation set. In HCC, the enrichment pathways were mainly related to protein folding, oxidative stress, and glutathione metabolism. While in ICC, immune response, embryonic hepatocyte maturation were the top pathways. Both in HCC and ICC, methylator phenotype correlated well with overall survival time and clinical factors involved in tumor progression. In summary, our study provides the biomarkers based on methylation sites not only for the diagnosis of PLC but also for distinguishing HCC from ICC.

Differential Regulation of Lacto-/Neolacto- Glycosphingolipid Biosynthesis Pathway Reveals Transcription Factors as Potential Candidates in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive breast cancer with limited treatment options. Glycosylation has been implicated in cancer development, but TNBC-specific glycosylation pathways have not been examined. Here, we applied bioinformatic analyses on public datasets to discover TNBC-specific glycogenes and pathways, as well as their upstream regulatory mechanisms. Unsupervised clustering of 345 glycogene expressions in breast cancer datasets revealed a relative homogenous expression pattern in basal-like TNBC subtype. Differential expression analyses of the 345 glycogenes between basal-like TNBC (hereafter termed TNBC) and other BC subtypes, or normal controls, revealed 84 differential glycogenes in TNBC. Pathway enrichment showed two common TNBC-enriched pathways across all three datasets, cell cycle and lacto-/neolacto- glycosphingolipid (GSL) biosynthesis, while a total of four glycosylation-related pathways were significantly enriched in TNBC. We applied a selection criterion of the top 50% differential anabolic/catabolic glycogenes in the enriched pathways to define 34 TNBC-specific glycogenes. The lacto-/neolacto- GSL biosynthesis pathway was the most highly enriched, with seven glycogenes all up-regulated in TNBC. This data led us to investigate the hypothesis that a common upstream mechanism in TNBC up-regulates the lacto-/neolacto-GSL biosynthesis pathway. Using public multi-omic datasets, we excluded the involvement of copy-number alteration and DNA methylation, but identified three transcription factors (AR, GATA3 and ZNG622) that each target three candidate genes in the lacto-/neolacto- GSL biosynthesis pathway. Interestingly, a subset of TNBC has been reported to express AR and GATA3, and AR antagonists are being trialed for TNBC. Our findings suggest that AR and GATA3 may contribute to TNBC via GSL regulation, and provide a list of candidate glycogenes for further investigation.

Knockdown of Forkhead box A1 suppresses the tumorigenesis and progression of human colon cancer cells through regulating the phosphatase and tensin homolog/Akt pathway

Background

This study aimed to evaluate the role and the underlying mechanisms of Forkhead box A1 (encoded by FOXA1) in colon cancer.

Methods

We analyzed FOXA1 mRNA and protein expression in colon cancer tissues and cell lines. We also silenced FOXA1 expression in HCT116 and SW480 cells to evaluate the effects on cell proliferation, cell cycle, migration, and invasion by using MTT, colony formation, flow cytometry, and the Transwell assay, respectively.

Results

FOXA1 immunostaining was higher in colon cancer tissues than adjacent healthy tissues. FOXA1 mRNA and protein expression was significantly increased in human colon cancer cells compared with a normal colonic cell line. FOXA1 expression was also significantly higher in colorectal cancer tissues from TCGA data sets and was associated with worse prognosis in the R2 database. FOXA1 expression was negatively correlated with the extent of its methylation, and its knockdown reduced proliferation, migration, and invasion, and induced G2/M phase arrest in HCT116 and SW480 cells by suppressing the phosphatase and tensin homolog/Akt signaling pathway and inhibiting epithelial–mesenchymal transition.

Conclusion

FOXA1 may act as an oncogene in colon cancer tumorigenesis and development.

Adenosine kinase: An epigenetic modulator in development and disease

Adenosine kinase (ADK) is the key regulator of adenosine and catalyzes the metabolism of adenosine to 5'-adenosine monophosphate. The enzyme exists in two isoforms: a long isoform (ADK-long, ADK-L) and a short isoform (ADK-short, ADK-S). The two isoforms are developmentally regulated and are differentially expressed in distinct subcellular compartments with ADK-L localized in the nucleus and ADK-S localized in the cytoplasm. The nuclear localization of ADK-L and its biochemical link to the transmethylation pathway suggest a specific role for gene regulation via epigenetic mechanisms. Recent evidence reveals an adenosine receptor-independent role of ADK in determining the global methylation status of DNA and thereby contributing to epigenomic regulation. Here we summarize recent progress in understanding the biochemical interactions between adenosine metabolism by ADK-L and epigenetic modifications linked to transmethylation reactions. This review will provide a comprehensive overview of ADK-associated changes in DNA methylation in developmental, as well as in pathological conditions including brain injury, epilepsy, vascular diseases, cancer, and diabetes. Challenges in investigating the epigenetic role of ADK for therapeutic gains are briefly discussed.

Downregulated ZNF132 predicts unfavorable outcomes in breast Cancer via Hypermethylation modification

BACKGROUND

An important mechanism that promoter methylation-mediated gene silencing for gene inactivation is identified in human tumorigenesis. Methylated genes have been found in breast cancer (BC) and beneficial biomarkers for early diagnosis. Prognostic assessment of breast cancer remain little known. Zinc finger protein 132 (ZNF132) is downregulated by promoter methylation in prostate cancer and esophageal squamous cell carcinoma. However, no study provides information on the status of ZNF132, analyzes diagnosis and prognostic significance of ZNF132 in BC.

METHODS

In the present study, the expression of ZNF132 mRNA and protein level was determined based on the Cancer Genome Atlas (TCGA) RNA-Seq database and clinical samples analysis and multiple cancer cell lines verification. P rognostic significance of ZNF132 in BC was assessed using the Kaplan-Meier plotter. Molecular mechanisms exploration of ZNF132 in BC was performed using the multiple bioinformatic tools. Hypermethylated status of ZNF132 in BC cell lines was confirmed via Methylation specific polymerase chain reaction (MSP) analysis.

RESULTS

The expression of ZNF132 both the mRNA and protein levels was downregulated in BC tissues. These results were obtained based on TCGA database and clinical sample analysis. Survival analysis from the Kaplan-Meier plotter revealed that the lower level of ZNF132 was associated with a shorter Relapse Free Survival (RFS) time. Receiver operating characteristic curve (ROC) of 0.887 confirmed ZNF132 had powerful sensitivity and specificity to distinguish between BC and adjacent normal tissues. Bioinformatic analysis showed that 6% ((58/960)) alterations of ZNF132 were identified from cBioPortal. ZNF132 participated in multiple biological pathways based on the Gene Set Enrichment Analysis (GSEA) database including the regulation of cell cycle and glycolysis. Finally, MSP analysis demonstrated that ZNF132 was hypermethylated in a panel of breast cancer cell lines and 5-aza-2'-deoxycytidine (5-Aza-dC) treatment restored ZNF132 expression in partial cell lines.

CONCLUSIONS

Results revealed that hypermethylation of ZNF132 contributed to its downregulated expression and could be identified as a new diagnostic and prognostic marker in BC.

CSK-homologous kinase (CHK/MATK) is a potential colorectal cancer tumour suppressor gene epigenetically silenced by promoter methylation

Hyperactivation of SRC-family protein kinases (SFKs) contributes to the initiation and progression of human colorectal cancer (CRC). Since oncogenic mutations of SFK genes are rare in human CRC, we investigated if SFK hyperactivation is linked to dysregulation of their upstream inhibitors, C-terminal SRC kinase (CSK) and its homolog CSK-homologous kinase (CHK/MATK). We demonstrate that expression of CHK/MATK but not CSK was significantly downregulated in CRC cell lines and primary tumours compared to normal colonic tissue. Investigation of the mechanism by which CHK/MATK expression is down-regulated in CRC cells uncovered hypermethylation of the CHK/MATK promoter in CRC cell lines and primary tumours. Promoter methylation of CHK/MATK was also observed in several other tumour types. Consistent with epigenetic silencing of CHK/MATK, genetic deletion or pharmacological inhibition of DNA methyltransferases increased CHK/MATK mRNA expression in CHK/MATK-methylated colon cancer cell lines. SFKs were hyperactivated in CHK/MATK-methylated CRC cells despite expressing enzymatically active CSK, suggesting loss of CHK/MATK contributes to SFK hyperactivation. Re-expression of CHK/MATK in CRC cell lines led to reduction in SFK activity via a non-catalytic mechanism, a reduction in anchorage-independent growth, cell proliferation and migration in vitro, and a reduction in tumour growth and metastasis in a zebrafish embryo xenotransplantation model in vivo, collectively identifying CHK/MATK as a novel putative tumour suppressor gene in CRC. Furthermore, our discovery that CHK/MATK hypermethylation occurs in the majority of tumours warrants its further investigation as a diagnostic marker of CRC.

Identification of METTL3 as an Adverse Prognostic Biomarker in Hepatocellular Carcinoma

INTRODUCTION

N6-methyladenosine (m6A), the most prominent mRNA modification, plays a critical role in many physiological and pathological processes. However, the roles of m6A RNA modification in hepatocellular carcinoma (HCC) remain largely unknown.

MATERIALS AND METHODS

We investigated the mRNA expression and clinical significance of m6A-related genes using data from The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma cohort. Mutation, copy number variation (CNV), methylation, differential expression, and gene ontology analyses, gene set enrichment analysis and the construction of a competing endogenous RNA (ceRNA) regulatory network were performed to investigate the underlying mechanisms of the aberrant expression of m6A-related genes.

RESULTS

m6A-related genes were frequently dysregulated in cancers but with a cancer-specific pattern. METTL3, YTHDF2, and ZC3H13 were found to be independent prognostic factors of overall survival (OS); however, only METTL3 was found to be an independent prognostic factor of recurrence-free survival (RFS). Joint effects analysis showed the predictive capacity of combining METTL3, YTHDF2, and ZC3H13 for HCC OS. Then the potential mechanisms of METTL3 were further explored due to its prognostic role in both OS and RFS. CNV and DNA methylation, but not somatic mutations, might contribute to the abnormal upregulation of METTL3 in HCC. Significantly altered genes, microRNAs, and lncRNAs were identified, and a ceRNA regulatory network was constructed to explain the upregulation of METTL3 in HCC.

CONCLUSIONS

Our study identified several m6A-related genes, especially METTL3, that could be potential prognostic biomarkers in HCC.

High IRF8 expression correlates with CD8 T cell infiltration and is a predictive biomarker of therapy response in ER-negative breast cancer

Background

Characterization of breast cancer (BC) through the determination of conventional markers such as ER, PR, HER2, and Ki67 has been useful as a predictive and therapeutic tool. Also, assessment of tumor-infiltrating lymphocytes has been proposed as an important prognostic aspect to be considered in certain BC subtypes. However, there is still a need to identify additional biomarkers that could add precision in distinguishing therapeutic response of individual patients. To this end, we focused in the expression of interferon regulatory factor 8 (IRF8) in BC cells. IRF8 is a transcription factor which plays a well-determined role in myeloid cells and that seems to have multiple antitumoral roles: it has tumor suppressor functions; it acts downstream IFN/STAT1, required for the success of some therapeutic regimes, and its expression in neoplastic cells seems to depend on a cross talk between the immune contexture and the tumor cells.

The goal of the present study was to examine the relationship between IRF8 with the therapeutic response and the immune contexture in BC, since its clinical significance in this type of cancer has not been thoroughly addressed.

Methods

We identified the relationship between IRF8 expression and the clinical outcome of BC patients and validated IRF8 as predictive biomarker by using public databases and then performed in silico analysis. To correlate the expression of IRF8 with the immune infiltrate in BC samples, we performed quantitative multiplex immunohistochemistry.

Results

IRF8 expression can precisely predict the complete pathological response to monoclonal antibody therapy or to select combinations of chemotherapy such as FAC (fluorouracil, adriamycin, and cytoxan) in ER-negative BC subtypes. Analysis of immune cell infiltration indicates there is a strong correlation between activated and effector CD8⁺ T cell infiltration and tumoral IRF8 expression.

Conclusions

We propose IRF8 expression as a potent biomarker not only for prognosis, but also for predicting therapy response in ER-negative BC phenotypes. Its expression in neoplastic cells also correlates with CD8⁺ T cell activation and infiltration. Therefore, our results justify new efforts towards understanding mechanisms regulating IRF8 expression and how they can be therapeutically manipulated.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01418-7.

The roles of MASPIN expression and subcellular localization in non-small cell lung cancer

Accumulating studies have confirmed that mammary serine protease inhibitor (MASPIN) plays an essential role in non-small cell lung cancer (NSCLC). However, results are still controversial or inconsistent. In the present study, we attempted to identify the clinical significance of MASPIN and its potential molecular roles in NSCLC. The correlation of MASPIN with prognosis and clinicopathological characteristics was assessed by meta-analysis. Additionally, the potential molecular mechanisms of MASPIN in NSCLC was also investigated through several online databases. A total of 2220 NSCLC patients from 12 high quality studies were included and the results indicated that up-regulated MASPIN nucleus and cytoplasm expression was associated with poor overall survival (OS) (hazard ratio (HR) = 1.43, 95% confidence interval (CI) = 1.01–2.04, P<0.05), elevated MASPIN cytoplasm expression was associated with poor OS (HR = 1.45, 95% CI = 1.01–2.07, P<0.05), disease-free survival (DFS) (HR = 1.95, 95% CI = 1.31–2.88, P=0.001), and disease-specific survival (DSS) (HR = 2.17, 95% CI = 1.18–3.99, P=0.013). MASPIN both nucleus and cytoplasm location were associated with clinicopathological characteristics. Bioinformatics analysis validated the above results and suggested that human serpin family B member 5 (SERPINB5) hypomethylated levels were negatively correlated with its mRNA expression. Bioinformatics analysis also revealed the 85 most frequently altered neighboring genes of SERPINB5, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed 20 GO terms and 3 KEGG pathways with statistical significance. MASPIN had a statistically negative correlation with NSCLC prognosis, functioning as an oncoprotein by hypomethylation and influencing specific pathways involving the 85 genes identified herein. MASPIN might be a promising prognostic signature in NSCLC.

Development of a novel prognostic signature for predicting the overall survival of bladder cancer patients

Background: Bladder cancer is one of the most common malignancies. So far, no effective biomarker for bladder cancer prognosis has been identified. Aberrant DNA methylation is frequently observed in the bladder cancer and holds considerable promise as a biomarker for predicting the overall survival (OS) of patients. Materials and methods: We downloaded the DNA methylation and transcriptome data for bladder cancer from The Cancer Genome Atlas (TCGA), a public database, screened hypo-methylated and up-regulated genes, similarly, hyper-methylation with low expression genes, then retrieved the relevant methylation sites. Cox regression analysis was used to identify a nine-methylation site signature of a training group. Predictive ability was validated in a test group by receiver operating characteristic (ROC) analysis. Results: We identified nine bladder cancer-specific methylation sites as potential prognostic biomarkers and established a risk score system based on the methylation site signature to evaluate the OS. The performance of the signature was accurate, with area under curve was 0.73 in the training group and 0.71 in the test group. Taking clinical features into consideration, we constructed a nomogram consisting of the nine-methylation site signature and patients’ clinical variables, and found that the signature was an independent risk factor. Conclusions: Overall, the significant nine methylation sites could be novel prediction biomarkers, which could aid in treatment and also predict the overall survival likelihoods of bladder cancer patients.