An integrated epigenomic-transcriptomic landscape of lung cancer reveals novel methylation driver genes of diagnostic and therapeutic relevance

Exploring extrahepatic metastasis of hepatocellular carcinoma based on methylation driver genes and establishing a prognostic model for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC), theseventh most common cancer worldwide, is characterized by a high mortality rate, advanced diagnosis, and susceptibility to extrahepatic metastasis. Numerous studies have shown that DNA methylation is a crucial factor in epigenetic modifications and regulation of carcinogenesis.

METHODS

HCC patient data were sourced from the TCGA dataset as a training set, while GSE116174 was used as an external validation set for verification. Differential methylation and expression analyses were performed on HCC samples with and without extrahepatic metastasis. In the intersecting genes, the relationship between methylation and expression levels of the intersecting genes was analyzed. Genes with a correlation coefficient≥|0.30| and P<0.05 were identified as methylation driver genes. Cox regression analysis was conducted to identify genes associated with HCC prognosis and establish a risk score. Subsequently, a prognostic model was established and validated using Cox regression analysis incorporating the risk score and other clinical factors. Using immunohistochemistry to evaluate the expression of DHX58 and EIF5A2 in HCC tissues with and without extrahepatic metastasis. Immunoinfiltration analysis was performed on the HCC samples using CIBERSORT.

RESULTS

Our research identified eight methylation driver genes for HCC extrahepatic metastasis, of which two genes (DHX58 and EIF5A2) were associated with HCC patient prognosis. And the study further constructed and validated the risk score and prognostic model. Immunoinfiltration analysis showed that M0 macrophage abundance was correlated with the prognosis of HCC patients. Immunohistochemistry revealed differences in DHX58 and EIF5A2 expression between HCC tissues with and without extrahepatic metastasis, consistent with our bioinformatics findings.

Discrimination of Lung Cancer and Benign Lung Diseases Using BALF Exosome DNA Methylation Profile

Benign lung diseases are common and often do not require specific treatment, but they pose challenges in the distinguishing of them from lung cancer during low-dose computed tomography (LDCT). This study presents a comprehensive methylation analysis using real-time PCR for minimally invasive diagnoses of lung cancer via employing BALF exosome DNA. A panel of seven epigenetic biomarkers was identified, exhibiting specific methylation patterns in lung cancer BALF exosome DNA. This panel achieved an area under the curve (AUC) of 0.97, with sensitivity and specificity rates of 88.24% and 97.14%, respectively. Each biomarker showed significantly higher mean methylation levels (MMLs) in both non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) compared to non-cancer groups, with fold changes from 1.7 to 13.36. The MMLs of the biomarkers were found to be moderately elevated with increasing patient age and smoking history, regardless of sex. A strong correlation was found between the MMLs and NSCLC stage progression, with detection sensitivities of 79% for early stages and 92% for advanced stages. In the validation cohort, the model demonstrated an AUC of 0.95, with 94% sensitivity and specificity. Sensitivity for early-stage NSCLC detection improved from 88.00% to 92.00% when smoking history was included as an additional risk factor.

Research advances on signaling pathways regulating the polarization of tumor-associated macrophages in lung cancer microenvironment

Lung cancer (LC) is one of the most common cancer worldwide. Tumor-associated macrophages (TAMs) are important component of the tumor microenvironment (TME) and are closely related to the stages of tumor occurrence, development, and metastasis. Macrophages are plastic and can differentiate into different phenotypes and functions under the influence of different signaling pathways in TME. The classically activated (M1-like) and alternatively activated (M2-like) represent the two polarization states of macrophages. M1 macrophages exhibit anti-tumor functions, while M2 macrophages are considered to support tumor cell survival and metastasis. Macrophage polarization involves complex signaling pathways, and blocking or regulating these signaling pathways to enhance macrophages' anti-tumor effects has become a research hotspot in recent years. At the same time, there have been new discoveries regarding the modulation of TAMs towards an anti-tumor phenotype by synthetic and natural drug components. Nanotechnology can better achieve combination therapy and targeted delivery of drugs, maximizing the efficacy of the drugs while minimizing side effects. Up to now, nanomedicines targeting the delivery of various active substances for reprogramming TAMs have made significant progress. In this review, we primarily provided a comprehensive overview of the signaling crosstalk between TAMs and various cells in the LC microenvironment. Additionally, the latest advancements in novel drugs and nano-based drug delivery systems (NDDSs) that target macrophages were also reviewed. Finally, we discussed the prospects of macrophages as therapeutic targets and the barriers to clinical translation.

Wemics: A Single-Base Resolution Methylation Quantification Method for Enhanced Prediction of Epigenetic Regulation

DNA methylation, an epigenetic mechanism that alters gene expression without changing DNA sequence, is essential for organism development and key biological processes like genomic imprinting and X-chromosome inactivation. Despite tremendous efforts in DNA methylation research, accurate quantification of cytosine methylation remains a challenge. Here, a single-base methylation quantification approach is introduced by weighting methylation of consecutive CpG sites (Wemics) in genomic regions. Wemics quantification of DNA methylation better predicts its regulatory impact on gene transcription and identifies differentially methylated regions (DMRs) with more biological relevance. Most Wemics-quantified DMRs in lung cancer are epigenetically conserved and recurrently occurred in other primary cancers from The Cancer Genome Atlas (TCGA), and their aberrant alterations can serve as promising pan-cancer diagnostic markers. It is further revealed that these detected DMRs are enriched in transcription factor (TF) binding motifs, and methylation of these TF binding motifs and TF expression synergistically regulate target gene expression. Using Wemics on epigenomic-transcriptomic data from the large lung cancer cohort, a dozen novel genes with oncogenic potential are discovered that are upregulated by hypomethylation but overlooked by other quantification methods. These findings increase the understanding of the epigenetic mechanism by which DNA methylation regulates gene expression.

Comprehensive Analysis of TICRR in Hepatocellular Carcinoma Based on Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is one of the leading cause of cancer-associated death in the world. However, due to the complexity of HCC, it is urgent for us to find a reliable and accurate biomarker for HCC gene therapy.TopBP1-interacting checkpoint and replication regulator (TICRR), known as Treslin in vertebrate and sld3 in yeast, is involved in the tumorigenesis, progression, matastasis, diagnosis, and predicting prognosis of HCC. Disappointingly, the mechanism of TICRR expression in HCC is still not described in detail and requires further analysis. In this study, TCGA ( www.tcga-data.nci.nih.gov/tcga/ ) datasets and GEO ( www.ncbi.nlm.nih.gov/geo ) datasets were used to analyze the expression of TICRR in HCC, the relevance of TICRR mRNA expression and clinicopathological characteristics in patients with HCC, and the relationship between TICRR expression and immune infiltration level in Patients with HCC. Based on MethSurv database, the impact of TICRR in patients with HCC was investigated. In addition, GO/KEGG enrichment analysis of TICRR co-expression was performed using the R package. TICRR was found drastically highly expressed in a variety of cancer types including HCC.ROC curve analysis showed that TICRR had higher accuracy in predicting HCC compared with AFP. The expression level of TICRR was marked positively correlated with tumor stage and prognosis in Patients with HCC.GO/KEGG enrichment analysis showed that TICRR was associated with cell division and cell cycle as well as p53 signaling pathway. In addition, patients with high TICRR methylation of cg05841809, cg09403165, and cg03312532 CpG sites were significantly correlated with poor prognosis of HCC. This study demonstrated that increased TICRR expression in HCC might play an important role in the tumorigenesis, progression, diagnosis, and predicting prognosis of HCC. Therefore, TICRR might be used as a promising diagnostic and prognostic biomarker for HCC gene therapy.

Exploring the interplay between methylation patterns and non-coding RNAs in non-small cell lung cancer: Implications for pathogenesis and therapeutic targets

Lung cancer is a global public health issue, with non-small cell lung cancer (NSCLC) accounting for 80-85 % of cases. With over two million new diagnoses annually, understanding the complex evolution of this disease is crucial. The development of lung cancer involves a complex interplay of genetic, epigenetic, and environmental factors, leading the key oncogenes and tumor suppressor genes to disorder, and activating the cancer related signaling pathway. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNA (lncRNAs), and circular RNA (circRNAs) are unique RNA transcripts with diverse biological functions. These ncRNAs are generated through genome transcription and play essential roles in cellular processes. Epigenetic modifications such as DNA methylation, N6-methyladenosine (m6A) modification, and histone methylation have gained significant attention in NSCLC research. The complexity of the interactions among these methylation modifications and ncRNAs contribute to the precise regulation of NSCLC development. This review comprehensively summarizes the associations between ncRNAs and different methylation modifications and discusses their effects on NSCLC. By elucidating these relationships, we aim to advance our understanding of NSCLC pathogenesis and identify potential therapeutic targets for this devastating disease.

Identification of colon cancer subtypes based on multi-omics data-construction of methylation markers for immunotherapy

Background

Being the most widely used biomarker for immunotherapy, the microsatellite status has limitations in identifying all patients who benefit in clinical practice. It is essential to identify additional biomarkers to guide immunotherapy. Aberrant DNA methylation is consistently associated with changes in the anti-tumor immune response, which can promote tumor progression. This study aims to explore immunotherapy biomarkers for colon cancers from the perspective of DNA methylation.

Methods

The related data (RNA sequencing data and DNA methylation data) were obtained from The Cancer Genome Atlas (TCGA) and UCSC XENA database. Methylation-driven genes (MDGs) were identified through the Pearson correlation analysis. Unsupervised consensus clustering was conducted using these MDGs to identify distinct clusters of colon cancers. Subsequently, we evaluated the immune status and predicted the efficacy of immunotherapy by tumor immune dysfunction and exclusion (Tide) score. Finally, The Quantitative Differentially Methylated Regions (QDMR) software was used to identify the specific DNA methylation markers within particular clusters.

Results

A total of 282 MDGs were identified by integrating the DNA methylation and RNA-seq data. Consensus clustering using the K-means algorithm revealed that the optimal number of clusters was 4. It was revealed that the composition of the tumor immune microenvironment (TIME) in Cluster 1 was significantly different from others, and it exhibited a higher level of tumor mutation burdens (TMB) and stronger anti-tumor immune activity. Furthermore, we identified three specific hypermethylation genes that defined Cluster 1 (PCDH20, APCDD1, COCH). Receiver operating characteristic (ROC) curves demonstrated that these specific markers could effectively distinguish Cluster 1 from other clusters, with an AUC of 0.947 (95% CI 0.903-0.990). Finally, we selected clinical samples for immunohistochemical validation.

Conclusion

In conclusion, through the analysis of DNA methylation, consensus clustering of colon cancer could effectively identify the cluster that benefit from immunotherapy along with specific methylation biomarkers.

Systematic analysis of DNA methylation-mediated TF dysregulation on lncRNAs reveals critical roles in tumor immunity

Emerging evidence suggests that DNA methylation affects transcriptional regulation and expression perturbations of long non-coding RNAs (lncRNAs) in cancer. However, a comprehensive investigation into the transcriptional control of DNA methylation-mediated dysregulation of transcription factors (TFs) on lncRNAs has been lacking. Here, we integrated the transcriptome, methylome, and regulatome across 21 human cancers and systematically identified the transcriptional regulation of DNA methylation-mediated TF dysregulations (DMTDs) on lncRNAs. Our findings reveal that TF regulation of lncRNAs is significantly impacted by DNA methylation. Comparative analysis of DMTDs on mRNAs revealed a conserved pattern of TFs involvement. Pan-cancer Methylation TFs (MethTFs) and Methylation LncRNAs (MethLncRNAs) were identified, and were found to be closely associated with cancer hallmarks and clinical features. In-depth analysis of co-expressed mRNAs with pan-cancer MethLncRNAs unveiled frequent disruptions in cancer immunity, particularly in the context of inflammatory response. Furthermore, we identified five immune-related network modules that contribute to immune cell infiltration in cancer. Immune-related subtypes were subsequently classified, characterized by high levels of immune cell infiltration, expression of immunomodulatory genes, and relevant immune cytolytic activity score, major histocompatibility complex score, response to chemotherapy, and prognosis. Our findings provide valuable insights into cancer immunity from the epigenetic and transcriptional regulation perspective.

Methylomics and cancer: the current state of methylation profiling and marker development for clinical care

Epigenetic modifications have long been recognized as an essential level in transcriptional regulation linking behavior and environmental conditions or stimuli with biological processes and disease development. Among them, methylation is the most abundant of these reversible epigenetic marks, predominantly occurring on DNA, RNA, and histones. Methylation modification is intimately involved in regulating gene transcription and cell differentiation, while aberrant methylation status has been linked with cancer development in several malignancies. Early detection and precise restoration of dysregulated methylation form the basis for several epigenetics-based therapeutic strategies. In this review, we summarize the current basic understanding of the regulation and mechanisms responsible for methylation modification and cover several cutting-edge research techniques for detecting methylation across the genome and transcriptome. We then explore recent advances in clinical diagnostic applications of methylation markers of various cancers and address the current state and future prospects of methylation modifications in therapies for different diseases, especially comparing pharmacological methylase/demethylase inhibitors with the CRISPRoff/on methylation editing systems. This review thus provides a resource for understanding the emerging role of epigenetic methylation in cancer, the use of methylation-based biomarkers in cancer detection, and novel methylation-targeted drugs.

E-value: a superior alternative to P-value and its adjustments in DNA methylation studies

DNA methylation plays a crucial role in transcriptional regulation. Reduced representation bisulfite sequencing (RRBS) is a technique of increasing use for analyzing genome-wide methylation profiles. Many computational tools such as Metilene, MethylKit, BiSeq and DMRfinder have been developed to use RRBS data for the detection of the differentially methylated regions (DMRs) potentially involved in epigenetic regulations of gene expression. For DMR detection tools, as for countless other medical applications, P-values and their adjustments are among the most standard reporting statistics used to assess the statistical significance of biological findings. However, P-values are coming under increasing criticism relating to their questionable accuracy and relatively high levels of false positive or negative indications. Here, we propose a method to calculate E-values, as likelihood ratios falling into the null hypothesis over the entire parameter space, for DMR detection in RRBS data. We also provide the R package 'metevalue' as a user-friendly interface to implement E-value calculations into various DMR detection tools. To evaluate the performance of E-values, we generated various RRBS benchmarking datasets using our simulator 'RRBSsim' with eight samples in each experimental group. Our comprehensive benchmarking analyses showed that using E-values not only significantly improved accuracy, area under ROC curve and power, over that of P-values or adjusted P-values, but also reduced false discovery rates and type I errors. In applications using real RRBS data of CRL rats and a clinical trial on low-salt diet, the use of E-values detected biologically more relevant DMRs and also improved the negative association between DNA methylation and gene expression.

Integrated models of blood protein and metabolite enhance the diagnostic accuracy for Non-Small Cell Lung Cancer

BACKGROUND

For early screening and diagnosis of non-small cell lung cancer (NSCLC), a robust model based on plasma proteomics and metabolomics is required for accurate and accessible non-invasive detection. Here we aim to combine TMT-LC-MS/MS and machine-learning algorithms to establish models with high specificity and sensitivity, and summarize a generalized model building scheme.

METHODS

TMT-LC-MS/MS was used to discover the differentially expressed proteins (DEPs) in the plasma of NSCLC patients. Plasma proteomics-guided metabolites were selected for clinical evaluation in 110 NSCLC patients who were going to receive therapies, 108 benign pulmonary diseases (BPD) patients, and 100 healthy controls (HC). The data were randomly split into training set and test set in a ratio of 80:20. Three supervised learning algorithms were applied to the training set for models fitting. The best performance models were evaluated with the test data set.

RESULTS

Differential plasma proteomics and metabolic pathways analyses revealed that the majority of DEPs in NSCLC were enriched in the pathways of complement and coagulation cascades, cholesterol and bile acids metabolism. Moreover, 10 DEPs, 14 amino acids, 15 bile acids, as well as 6 classic tumor biomarkers in blood were quantified using clinically validated assays. Finally, we obtained a high-performance screening model using logistic regression algorithm with AUC of 0.96, sensitivity of 92%, and specificity of 89%, and a diagnostic model with AUC of 0.871, sensitivity of 86%, and specificity of 78%. In the test set, the screening model achieved accuracy of 90%, sensitivity of 91%, and specificity of 90%, and the diagnostic model achieved accuracy of 82%, sensitivity of 77%, and specificity of 86%.

CONCLUSIONS

Integrated analysis of DEPs, amino acid, and bile acid features based on plasma proteomics-guided metabolite profiling, together with classical tumor biomarkers, provided a much more accurate detection model for screening and differential diagnosis of NSCLC. In addition, this new mathematical modeling based on plasma proteomics-guided metabolite profiling will be used for evaluation of therapeutic efficacy and long-term recurrence prediction of NSCLC.

A novel tumor 4-driver gene signature for the prognosis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC), the main type of liver cancer, is the second most lethal tumor worldwide, with a 5-year survival rate of only 18%. Driver genes facilitate cancer cell growth and spread in the tumor microenvironment. Here, a comprehensive driver gene signature for the prognosis of HCC was developed.

Methods

HCC driver genes were analyzed comprehensively to develop a better prognostic signature. The dataset of HCC patients included mRNA sequencing data and clinical information from the TCGA, the ICGC, and the Guangxi Medical University Cancer Hospital cohorts. First, LASSO was performed to develop a prognostic signature for differentially expressed driver genes in the TCGA cohort. Then, the robustness of the signature was assessed using survival and time-dependent ROC curves. Furthermore, independent predictors were determined using univariate and multivariate Cox regression analyses. Stepwise multi-Cox regression analysis was employed to identify significant variables for the construction of a nomogram that predicts survival rates. Functional analysis by Spearman correlation analysis, enrichment analysis (GO, KEGG, and GSEA), and immunoassay (ssGSEA and xCell) were performed.

Result

A 4-driver gene signature (CLTC, DNMT3A, GMPS, and NRAS) was successfully constructed and showed excellent predictive efficiency in three cohorts. The nomogram indicated high predictive accuracy for the 1-, 3-, and 5-year prognoses of HCC patients, which included clinical information and risk score. Enrichment analysis revealed that driver genes were involved in regulating oncogenic processes, including the cell cycle and metabolic pathways, which were associated with the progression of HCC. ssGSEA and xCell showed differences in immune infiltration and the immune microenvironment between the two risk groups.

Conclusion

The 4-driver gene signature is closely associated with the survival prediction of HCC and is expected to provide new insights into targeted therapy for HCC patients.

A Systematic Review of Progress toward Unlocking the Power of Epigenetics in NSCLC: Latest Updates and Perspectives

Epigenetic research has the potential to improve our understanding of the pathogenesis of cancer, specifically non-small-cell lung cancer, and support our efforts to personalize the management of the disease. Epigenetic alterations are expected to have relevance for early detection, diagnosis, outcome prediction, and tumor response to therapy. Additionally, epi-drugs as therapeutic modalities may lead to the recovery of genes delaying tumor growth, thus increasing survival rates, and may be effective against tumors without druggable mutations. Epigenetic changes involve DNA methylation, histone modifications, and the activity of non-coding RNAs, causing gene expression changes and their mutual interactions. This systematic review, based on 110 studies, gives a comprehensive overview of new perspectives on diagnostic (28 studies) and prognostic (25 studies) epigenetic biomarkers, as well as epigenetic treatment options (57 studies) for non-small-cell lung cancer. This paper outlines the crosstalk between epigenetic and genetic factors as well as elucidates clinical contexts including epigenetic treatments, such as dietary supplements and food additives, which serve as anti-carcinogenic compounds and regulators of cellular epigenetics and which are used to reduce toxicity. Furthermore, a future-oriented exploration of epigenetic studies in NSCLC is presented. The findings suggest that additional studies are necessary to comprehend the mechanisms of epigenetic changes and investigate biomarkers, response rates, and tailored combinations of treatments. In the future, epigenetics could have the potential to become an integral part of diagnostics, prognostics, and personalized treatment in NSCLC.

Iroquois Family Genes in Gastric Carcinogenesis: A Comprehensive Review

Gastric cancer (GC) is the fifth leading cause of cancer-associated death worldwide, accounting for 768,793 related deaths and 1,089,103 new cases in 2020. Despite diagnostic advances, GC is often detected in late stages. Through a systematic literature search, this study focuses on the associations between the Iroquois gene family and GC. Accumulating evidence indicates that Iroquois genes are involved in the regulation of various physiological and pathological processes, including cancer. To date, information about Iroquois genes in GC is very limited. In recent years, the expression and function of Iroquois genes examined in different models have suggested that they play important roles in cell and cancer biology, since they were identified to be related to important signaling pathways, such as wingless, hedgehog, mitogen-activated proteins, fibroblast growth factor, TGFβ, and the PI3K/Akt and NF-kB pathways. In cancer, depending on the tumor, Iroquois genes can act as oncogenes or tumor suppressor genes. However, in GC, they seem to mostly act as tumor suppressor genes and can be regulated by several mechanisms, including methylation, microRNAs and important GC-related pathogens. In this review, we provide an up-to-date review of the current knowledge regarding Iroquois family genes in GC.

Insights into the role of long non-coding RNAs in DNA methylation mediated transcriptional regulation

DNA methylation is one of the most important epigenetic mechanisms that governing regulation of gene expression, aberrant DNA methylation patterns are strongly associated with human malignancies. Long non-coding RNAs (lncRNAs) have being discovered as a significant regulator on gene expression at the epigenetic level. Emerging evidences have indicated the intricate regulatory effects between lncRNAs and DNA methylation. On one hand, transcription of lncRNAs are controlled by the promoter methylation, which is similar to protein coding genes, on the other hand, lncRNA could interact with enzymes involved in DNA methylation to affect the methylation pattern of downstream genes, thus regulating their expression. In addition, circular RNAs (circRNAs) being an important class of noncoding RNA are also found to participate in this complex regulatory network. In this review, we summarize recent research progress on this crosstalk between lncRNA, circRNA, and DNA methylation as well as their potential functions in complex diseases including cancer. This work reveals a hidden layer for gene transcriptional regulation and enhances our understanding for epigenetics regarding detailed mechanisms on lncRNA regulatory function in human cancers.

Liquid biopsies based on DNA methylation as biomarkers for the detection and prognosis of lung cancer

Lung cancer (LC) is the main cause of cancer-related mortality. Most LC patients are diagnosed in an advanced stage when the symptoms are obvious, and the prognosis is quite poor. Although low-dose computed tomography (LDCT) is a routine clinical examination for early detection of LC, the false-positive rate is over 90%. As one of the intensely studied epigenetic modifications, DNA methylation plays a key role in various diseases, including cancer and other diseases. Hypermethylation in tumor suppressor genes or hypomethylation in oncogenes is an important event in tumorigenesis. Remarkably, DNA methylation usually occurs in the very early stage of malignant tumors. Thus, DNA methylation analysis may provide some useful information about the early detection of LC. In recent years, liquid biopsy has developed rapidly. Liquid biopsy can detect and monitor both primary and metastatic malignant tumors and can reflect tumor heterogeneity. Moreover, it is a minimally invasive procedure, and it causes less pain for patients. This review summarized various liquid biopsies based on DNA methylation for LC. At first, we briefly discussed some emerging technologies for DNA methylation analysis. Subsequently, we outlined cell-free DNA (cfDNA), sputum, bronchoalveolar lavage fluid, bronchial aspirates, and bronchial washings DNA methylation-based liquid biopsy for the early detection of LC. Finally, the prognostic value of DNA methylation in cfDNA and sputum and the diagnostic value of other DNA methylation-based liquid biopsies for LC were also analyzed.

Extracellular Vesicle (EVs) Associated Non-Coding RNAs in Lung Cancer and Therapeutics

Lung cancer is one of the most lethal forms of cancer, with a very high mortality rate. The precise pathophysiology of lung cancer is not well understood, and pertinent information regarding the initiation and progression of lung cancer is currently a crucial area of scientific investigation. Enhanced knowledge about the disease will lead to the development of potent therapeutic interventions. Extracellular vesicles (EVs) are membrane-bound heterogeneous populations of cellular entities that are abundantly produced by all cells in the human body, including the tumor cells. A defined class of EVs called small Extracellular Vesicles (sEVs or exosomes) carries key biomolecules such as RNA, DNA, Proteins and Lipids. Exosomes, therefore, mediate physiological activities and intracellular communication between various cells, including constituent cells of the tumor microenvironment, namely stromal cells, immunological cells, and tumor cells. In recent years, a surge in studying tumor-associated non-coding RNAs (ncRNAs) has been observed. Subsequently, studies have also reported that exosomes abundantly carry different species of ncRNAs and these exosomal ncRNAs are functionally involved in cancer initiation and progression. Here, we discuss the function of exosomal ncRNAs, such as miRNAs and long non-coding RNAs, in the pathophysiology of lung tumors. Further, the future application of exosomal-ncRNAs in clinics as biomarkers and therapeutic targets in lung cancer is also discussed due to the multifaceted influence of exosomes on cellular physiology.

Identification of N7-methylguanosine related signature for prognosis and immunotherapy efficacy prediction in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is one of the most frequent causes of tumor-related mortality worldwide. Recently, the role of N7-methylguanosine (m7G) in tumors has begun to receive attention, but no investigation on the impact of m7G on LUAD. This study aims to elucidate the significance of m7G on the prognosis and immunotherapy in LUAD.

Methods

Consensus clustering was employed to determine the molecular subtype according to m7G-related regulators extracted from The Cancer Genome Atlas (TCGA) database. Survival, clinicopathological features and tumor mutational burden (TMB) analysis were applied to research molecular characteristics of each subtype. Subsequently, “limma” package was used to screen differentially expressed genes (DEGs) between subtypes. In the TCGA train cohort (n = 245), a prognostic signature was established by univariate Cox regression, lasso regression and multivariate Cox regression analysis according to DEGs and survival analysis was employed to assess the prognosis. Then the prognostic value of the signature was verified by TCGA test cohort (n = 245), TCGA entire cohort (n = 490) and GSE31210 cohort (n = 226). Moreover, the association among immune infiltration, clinical features and the signature was investigated. The immune checkpoints, TMB and tumor immune dysfunction and exclusion (TIDE) were applied to predict the immunotherapy response.

Results

Two novel molecular subtypes (C1 and C2) of LUAD were identified. Compared to C2 subtype, C1 subtype had poorer prognosis and higher TMB. Subsequently, the signature (called the “m7G score”) was constructed according to four key genes (E2F7, FAM83A, PITX3, and HOXA13). The distribution of m7G score were significantly different between two molecular subtypes. The patients with lower m7G score had better prognosis in TCGA train cohort and three verification cohort. The m7G score was intensively related to immune infiltration. Compared with the lower score, the higher m7G score was related to remarkable upregulation of the PD-1 and PD-L1, the higher TMB and the lower TIDE score.

Conclusion

This study established a m7G-related signature for predicting prognosis and immunotherapy in LUAD, which may contribute to the development of new therapeutic strategies for LUAD.

Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease

The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.

Hypermethylation-Mediated Silencing of CIDEA, MAL and PCDH17 Tumour Suppressor Genes in Canine DLBCL: From Multi-Omics Analyses to Mechanistic Studies

Gene expression is controlled by epigenetic deregulation, a hallmark of cancer. The DNA methylome of canine diffuse large B-cell lymphoma (cDLBCL), the most frequent malignancy of B-lymphocytes in dog, has recently been investigated, suggesting that aberrant hypermethylation of CpG loci is associated with gene silencing. Here, we used a multi-omics approach (DNA methylome, transcriptome and copy number variations) combined with functional in vitro assays, to identify putative tumour suppressor genes subjected to DNA methylation in cDLBCL. Using four cDLBCL primary cell cultures and CLBL-1 cells, we found that CiDEA, MAL and PCDH17, which were significantly suppressed in DLBCL samples, were hypermethylated and also responsive (at the DNA, mRNA and protein level) to pharmacological unmasking with hypomethylating drugs and histone deacetylase inhibitors. The regulatory mechanism underneath the methylation-dependent inhibition of those target genes expression was then investigated through luciferase and in vitro methylation assays. In the most responsive CpG-rich regions, an in silico analysis allowed the prediction of putative transcription factor binding sites influenced by DNA methylation. Interestingly, regulatory elements for AP2, MZF1, NF-kB, PAX5 and SP1 were commonly identified in all three genes. This study provides a foundation for characterisation and experimental validation of novel epigenetically-dysregulated pathways in cDLBCL.

Regulation of micro-RNA, epigenetic factor by natural products for the treatment of cancers: Mechanistic insight and translational Association

From onset to progression, cancer is a ailment that might take years to grow. All common epithelial malignancies, have a long latency period, frequently 20 years or more, different gene may contain uncountable mutations if they are clinically detectable. MicroRNAs (miRNAs) are around 22nt non-coding RNAs that control gene expression sequence-specifically through translational inhibition or messenger degradation of RNA (mRNA). Epigenetic processes of miRNA control genetic variants through genomic DNA methylation, post-translation histone modification, rework of the chromatin, and microRNAs. The field of miRNAs has opened a new era in understanding small non-coding RNAs since discovering their fundamental mechanisms of action. MiRNAs have been found in viruses, plants, and animals through molecular cloning and bioinformatics approaches. Phytochemicals can invert the epigenetic aberrations, a leading cause of the cancers of various organs, and act as an inhibitor of these changes. The advantage of phytochemicals is that they only function on cells that cause cancer without affecting normal cells. Phytochemicals appear to play a significant character in modulating miRNA expression, which is linked to variations in oncogenes, tumor suppressors, and cancer-derived protein production, according to several studies. In addition to standard anti-oxidant or anti-inflammatory properties, the initial epigenetic changes associated with cancer prevention may be modulated by many polyphenols. In correlation with miRNA and epigenetic factors to treat cancer some of the phytochemicals, including polyphenols, curcumin, resveratrol, indole-3-carbinol are studied in this article.

Analysis of 5-Methylcytosine Regulators and DNA Methylation-Driven Genes in Colon Cancer

Background: Epigenetic-driven events are important molecular mechanisms of carcinogenesis. The 5-methylcytosine (5mC) regulators play important roles in the methylation-driven gene expression. However, the effect of the 5mC regulators on the oncogenic pathways in colon cancer (CC) remains unclear. Also, the clinical value of such epigenetic-driven events needs further research.

Methods: The transcriptome and matching epigenetic data were obtained from The Cancer Genome Atlas dataset. The gene set variation analysis identified the oncogenic pathways adjusted by 5mC regulators. The “edgeR” and “methylmix” package identified the differential expression genes of DNA methylation-driven genes. The correlation between 5mC regulators or transcription factors and shortlisted genes was investigated by calculating the Spearman's rank correlation coefficient. Among them, the genes related to diagnosis were screened out based on differential gene expression in extracellular vesicles (EVs) by the “limma” package and histology by immunohistochemistry. Then, a risk signature was constructed by fitting the generalized linear model and validated by the receiver operating characteristic curve.

Results: MYC targets pathway and phosphatidylinositol-3-kinase–AKT–mammalian target of rapamycin signaling pathway were identified as the hallmark-related pathways associated with 5mC regulators. Also, the P53 pathway was subject to the influence of regulators' expression. A five methylation-driven gene signature (FIRRE, MYBL2, TGFBI, AXIN2, and SLC35D3) was developed as the biomarker for CC diagnosis. Meanwhile, those genes positively related to 5mC regulators and interacted with their relevant or transcription factors.

Conclusion: In general, 5mC regulators are positively related to each other and DNA methylation-driven genes, with the relationship of multiple active and inhibitory pathways related to cancer. Meanwhile, the signature (FIRRE, MYBL2, TGFBI, AXIN2, and SLC35D3) can prefigure prospective diagnosis in CC.

DNA Methylation in Lung Cancer: Mechanisms and Associations with Histological Subtypes, Molecular Alterations, and Major Epidemiological Factors

Lung cancer is the major leading cause of cancer-related mortality worldwide. Multiple epigenetic factors-in particular, DNA methylation-have been associated with the development of lung cancer. In this review, we summarize the current knowledge on DNA methylation alterations in lung tumorigenesis, as well as their associations with different histological subtypes, common cancer driver gene mutations (e.g., KRAS, EGFR, and TP53), and major epidemiological risk factors (e.g., sex, smoking status, race/ethnicity). Understanding the mechanisms of DNA methylation regulation and their associations with various risk factors can provide further insights into carcinogenesis, and create future avenues for prevention and personalized treatments. In addition, we also highlight outstanding questions regarding DNA methylation in lung cancer to be elucidated in future studies.