DNA methylation and cancer diagnosis

Benchmarking strategies for CNV calling from whole genome bisulfite data in humans

It's important to dissect the relationship between copy number variations (CNVs) and DNA methylation, because both greatly change the dosages of genes and are responsible for diverse human cancers. Although whole genome bisulfite sequencing (WGBS) informs CNVs and DNA methylation, no study has provided a systematic benchmark for detecting CNVs from WGBS data. Herein, based on simulated and real WGBS datasets of 84.62 billion reads, we undertook 714 CNV detections to comprehensively benchmark the performance of 35 strategies, 5 alignment algorithms (bismarkbt2, bsbolt, bsmap, bwameth, and walt) wrapping with 7 CNV detection applications (BreakDancer, cn.mops, CNVkit, CNVnator, DELLY, GASV and Pindel). The results highlighted a subset of strategies that accurately called CNVs depending on numbers, lengths, precision, recall, and F1 scores of CNV detections. We found that bwameth-DELLY and bwameth-BreakDancer were the best strategies for calling deletions, and walt-CNVnator and bismarkbt2-CNVnator were the best strategies for calling duplications. These works provided investigators with useful information to accurately explore CNVs from WGBS data in humans.

Hypermethylation of miR-129-2-3p inhibits esophageal cancer proliferation and migration by down-regulating PPP6C expression

OBJECTIVE

MicroRNAs (miRNAs) play crucial roles in gene regulation, and their dysregulation is associated with various diseases, including cancer. Abnormal DNA methylation can alter gene expression and influence carcinogenesis. DNA methylation-based biomarkers are emerging as promising tools for early cancer diagnosis. This study aimed to investigate the role of miR-129-2-3p in esophageal cancer (EC) and explore its potential as a diagnostic biomarker.

METHODS

To achieve these objectives, we employed multi-sample MethylTarget technology to assess the methylation status of miR-129-2-3p in EC tissues. The diagnostic value of miR-129-2-3p was evaluated using logistic regression and receiver operating characteristic (ROC) curve analysis. Functional assays were conducted to examine the effects of miR-129-2-3p overexpression on EC cell proliferation and migration. Luciferase reporter assays were performed to confirm Protein Phosphatase 6 Catalytic Subunit (PPP6C) as a direct target of miR-129-2-3p. Finally, the impact of PPP6C overexpression on the inhibitory effects induced by miR-129-2-3p was assessed.

RESULTS

We found that miR-129-2-3p is hypermethylated in EC tissues. Diagnostic analysis revealed that miR-129-2-3p had a sensitivity of 0.884, a specificity of 0.659, and an area under the curve (AUC) of 0.799. Overexpression of miR-129-2-3p significantly suppressed EC cell proliferation and migration. Furthermore, PPP6C was identified as a direct target of miR-129-2-3p, and its expression was suppressed. The elevation of PPP6C counteracted the inhibitory effects of miR-129-2-3p on EC cell proliferation and migration.

CONCLUSION

Hypermethylated miR-129-2-3p inhibits EC cell proliferation and migration by downregulating PPP6C expression, suggesting that miR-129-2-3p may serve as a potential diagnostic biomarker for EC.

Role of glutaminyl-peptide cyclo-transferase-like protein (QPCTL) in cancer: From molecular mechanisms to immunotherapy

Glutaminyl-peptide cyclotransferase-like protein (QPCTL) is a newly discovered enzyme that has sparked interest owing to its possible role in cancer genesis and progression. Initially discovered as a post-translational modification regulator of protein maturation, QPCTL has emerged as a key participant in cancer biology. Recent research has linked QPCTL to numerous essential cancer-related processes, including cell proliferation, migration, invasion, and apoptosis. Furthermore, QPCTL expression changes have been seen in a variety of cancer types, underlining its potential as a diagnostic and prognostic marker. The molecular mechanisms behind QPCTL's participation in cancer will be examined in this review. We investigate its involvement in the control of signaling pathways and the modification of cellular activities that are important in cancer. We also examine the clinical importance of QPCTL, including as its relationship with tumor development, metastasis, and response to treatment. We also discuss the possible therapeutic implications of targeting QPCTL in cancer therapy. QPCTL is a prospective target for the development of innovative anticancer treatments due to its participation in several cancer-associated pathways.

The thyroid hormone activating enzyme, DIO2, is a potential pan-cancer biomarker and immunotherapy target

PURPOSE

Type 2 deiodinase (D2), encoded by DIO2 gene, catalyzes the activation of the prohormone thyroxine (T4) into the bioactive hormone triiodothyronine (T3) in peripheral tissues, thereby regulating the intracellular Thyroid Hormone (TH) availability. Recently, several studies have demonstrated that a drastic increase in the peripheral activation of TH, via D2, fosters tumor progression, metastasis, and immunity.

METHODS

To further prove the clinical relevance of D2 in human cancer, based on public Database of The Cancer Genome Atlas (TCGA), we conducted a pan-cancer analysis of DIO2 expression in various cancer types and investigated the association of DIO2 expression with the tumor microenvironment (TME) components and immune cell infiltration, along with the DIO2 genetic alteration types.

RESULTS

Although with different expression levels between the various cancer types, the pan-cancer analysis showed that DIO2 was highly expressed in most tumors and related to the progression of some tumor types. Furthermore, DIO2 expression was also significantly correlated with TME components, immune cell infiltration, and immunoinhibitory and immunostimulatory gene subsets.

CONCLUSION

The relevance of this study is that it adds a clinical relevance to the recent demonstrations that D2 accelerates tumor invasion in animal models and poses DIO2 gene as a potential prognostic marker in various human cancers.

Cellular therapeutic potential of genetically engineered stem cells in cancer treatment

Traditional therapeutic approaches in the treatment of cancer have many side effects and are often ineffective and non-specific, leading to the development of therapy-resistant tumour cells. Recently, numerous discoveries about stem cells have given a new outlook on their application in oncology. Stem cells are unique because of their biological attributes, including self-renewal, differentiation in different types of specialized cells and synthesis of molecules that interplay with tumour niche. They are already used as an effective therapeutic option for haematological malignancies, such as multiple myeloma and leukaemia. The main goal of this study is to investigate the possible applications of different types of stem cells in cancer treatment and to summarize novel advances, as well as the limitations of their application in cancer treatment. Research and clinical trials that are underway revealed and confirmed the enormous potential of regenerative medicine in the treatment of cancer, especially when combined with different nanomaterials. Nanoengineering of stem cells has been the focus of novel studies in the area of regenerative medicine, such as the production of nanoshells and nanocarriers that enhance the transport and uptake of stem cells in their targeted tumour niche and enable the effective monitoring of stem cell effects on tumour cells. Although nanotechnology has a lot of limitations, it provides new opportunities for the development of effective and innovative stem cell therapies.

CRISPR-Cas-based biosensors for the detection of cancer biomarkers

Along with discovering cancer biomarkers, non-invasive detection methods have played a critical role in early cancer diagnosis and prognostic improvement. Some traditional detection methods have been used for detecting cancer biomarkers, but they are time-consuming and involve materials and human costs. With great flexibility, sensitivity and specificity, the clustered regularly interspaced short palindromic repeats (CRISPR)-associated system provides a wide range of application prospects in this field. Herein, we introduce the background of the CRISPR-Cas (CRISPR-associated) system and comprehensively summarize the diagnosis strategies of cancer mediated by the CRISPR-Cas system, including four kinds of biochemical-based markers: nucleic acid, enzyme, tumor-specific protein and exosome. Furthermore, we discuss the challenges in implementing the CRISPR-Cas system in clinical applications.

Evaluation of Multigene Methylation for Blood-Based Detection of Colorectal Cancer

Background: Early screening for colorectal cancer (CRC) has the potential to improve patient prognosis, but current screening methods are limited. In this prospective study, we aimed to evaluate the multigene (Septin9, SDC2, KCNQ5, and IKZF1) detection in patient plasma for CRC diagnosis. Methods: Overall, 67 participants were enrolled, including 31 patients with CRC, 17 patients with colorectal polyp, and 19 normal controls who underwent colonoscopy. Carcinoembryonic antigen (CEA) and Septin9, SDC2, KCNQ5, and IKZF1 methylation tests were performed. Sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve were used to evaluate the diagnostic value of each biomarker. The association between positive rates of methylated Septin9, SDC2, KCNQ5, and IKZF1 and the clinicopathological characteristics of CRC was also analyzed. Results: The positive rate of multigene methylation detection was 87.1% (27/31) in patients with CRC, which was higher than single indicators: CEA (51.61%, 16/31), Septin9 (41.94%, 13/31), SDC2 (41.94%, 13/31), KCNQ5 (58.06%, 18/31), and IKZF1 (32.26%, 10/31). In the colorectal polyp group, the rate of multigene methylation detection is 88.24% (15/17), which was also higher than single indicator: CEA (17.65%, 3/17), Septin9 (11.76%, 2/17), SDC2 (64.71%, 11/17), KCNQ5 (58.82%, 10/17), and IKZF1 (35.29%, 6/17). The ROC curves further showed better diagnostic value of the multigene test for CRC than any single gene. Correlation analysis found that the positive rate of the test was not affected by patients' clinicopathologic characteristics. Conclusion: The combination of methylated Septin9, SDC2, KCNQ5, and IKZF1 tests is preferable to individual gene tests for patients with CRC and polyp.

Crosstalk of methylation and tamoxifen in breast cancer (Review)

Tamoxifen is a widely used anti‑estrogen drug in the endocrine therapy of breast cancer (BC). It blocks estrogen signaling by competitively binding to estrogen receptor α (ERα), thereby inhibiting the growth of BC cells. However, with the long‑term application of tamoxifen, a subset of patients with BC have shown resistance to tamoxifen, which leads to low overall survival and progression‑free survival. The molecular mechanism of resistance is mainly due to downregulation of ERα expression and abnormal activation of the PI3K/AKT/mTOR signaling pathway. Moreover, the downregulation of targeted gene expression mediated by DNA methylation is an important regulatory mode to control protein expression. In the present review, methylation and tamoxifen are briefly introduced, followed by a focus on the effect of methylation on tamoxifen resistance and sensitivity. Finally, the clinical application of methylation for tamoxifen is described, including its use as a prognostic indicator. Finally, it is hypothesized that when methylation is used in combination with tamoxifen, it could recover the resistance of tamoxifen.

Shifting the Cancer Screening Paradigm: Developing a Multi-Biomarker Class Approach to Multi-Cancer Early Detection Testing

Guideline-recommended screening programs exist for only a few cancer types. Although all these programs are understood to lead to reductions in cancer-related mortality, standard-of-care screening tests vary in accuracy, adherence and effectiveness. Recent advances in high-throughput technologies and machine learning have facilitated the development of blood-based multi-cancer cancer early detection (MCED) tests. MCED tests are positioned to be complementary to standard-of-care screening and they may broaden screening availability, especially for individuals who are not adherent with current screening programs and for individuals who may harbor cancers with no available screening options. In this article, we outline some key features that should be considered for study design and MCED test development, provide an example of the developmental pathway undertaken for an emerging multi-biomarker class MCED test and propose a clinical algorithm for an imaging-based diagnostic resolution strategy following MCED testing.

Identification of a Biomarker Panel from Genome-Wide Methylation to Detect Early HPV-Associated Oropharyngeal Cancer

As oropharyngeal cancer (OPC) associated with human papillomavirus (HPV) increases in men, the need for a screening test to diagnose OPC early is crucial. This study agnostically identified differentially methylated CpG sites to identify additional biomarkers to improve screening for early OPC.DNA was extracted from oral gargles of 89 early cases and 108 frequency matched healthy controls, and processed for genome-wide methylation using the Illumina Infinium MethylationEPIC BeadChip. Selected sites were combined with our prior methylation data in the EPB41L3 gene (CpG sites 438, 427, and 425) and oral HPV16 and HPV18 status were considered as binary variables (positive/negative). Lasso regression identified CpG sites strongly associated with early OPC. ROC curves with AUC were generated. The panel was validated utilizing bootstrap resampling.Machine learning analyses identified 14 markers that are significantly associated with early OPC, including one EPB41L3 CpG site (438) and oral HPV16 status. A final model was trained on all available samples using the discovered panel and was able to predict early OPC compared with controls with an AUC of 0.970 on the training set. In the bootstrap validation sets, the average AUC was 0.935, indicating adequate internal validity.Our data suggest that this panel can detect OPC early, however external validation of this panel is needed. Further refinement of a panel of biomarkers to diagnose OPC earlier is urgently needed to prevent complex treatment of OPC and associated comorbidities, while reducing risk of recurrence.

PREVENTION RELEVANCE

This study identified biomarkers using genome-wide methylation to create a panel capable of discerning early oropharyngeal cancer (OPC) from those without OPC. Such a biomarker panel would be an effective tool to detect OPC early and prevent complications of treatment associated with later diagnosis.

Brain Tumor Classification by Methylation Profile

The goal of the methylation classifier in brain tumor classification is to accurately classify tumors based on their methylation profiles. Accurate brain tumor diagnosis is the first step for healthcare professionals to predict tumor prognosis and establish personalized treatment plans for patients. The methylation classifier can be used to perform classification on tumor samples with diagnostic difficulties due to ambiguous histology or mismatch between histopathology and molecular signatures, i.e., not otherwise specified (NOS) cases or not elsewhere classified (NEC) cases, aiding in pathological decision-making. Here, the authors elucidate upon the application of a methylation classifier as a tool to mitigate the inherent complexities associated with the pathological evaluation of brain tumors, even when pathologists are experts in histopathological diagnosis and have access to enough molecular genetic information. Also, it should be emphasized that methylome cannot classify all types of brain tumors, and it often produces erroneous matches even with high matching scores, so, excessive trust is prohibited. The primary issue is the considerable difficulty in obtaining reference data regarding the methylation profile of each type of brain tumor. This challenge is further amplified when dealing with recently identified novel types or subtypes of brain tumors, as such data are not readily accessible through open databases or authors of publications. An additional obstacle arises from the fact that methylation classifiers are primarily research-based, leading to the unavailability of charging patients. It is important to note that the application of methylation classifiers may require specialized laboratory techniques and expertise in DNA methylation analysis.

The interactions between DNA methylation machinery and long non-coding RNAs in tumor progression and drug resistance

DNA methylation is one of the main epigenetic mechanisms in cancer development and progression. Aberrant DNA methylation of CpG islands within promoter regions contributes to the dysregulation of various tumor suppressors and oncogenes; this leads to the appearance of malignant features, including rapid proliferation, metastasis, stemness, and drug resistance. The discovery of two important protein families, DNA methyltransferases (DNMTs) and Ten-eleven translocation (TET) dioxygenases, respectively, which are responsible for deregulated transcription of genes that play pivotal roles in tumorigenesis, led to further understanding of DNA methylation-related pathways. But how these enzymes can target specific genes in different malignancies; recent studies have highlighted the considerable role of Long Non-coding RNAs (LncRNAs). LncRNAs recruit these enzymes to promoter regions of genes and mediate their functions, showing great potential as therapeutic agents targeting the epigenetic regulation of various genes. Considering the importance of combining the current treatment methods, especially chemotherapies, with DNA methylation inhibitors in improving patients' outcomes, this review aimed to summarize the recent findings about the interaction between DNA methylation machinery and LncRNAs in regulating genes involved in tumorigenesis and drug resistance. So, these studies could provide insights toward developing novel strategies for cancer-targeted therapy.

CCNF is a potential pancancer biomarker and immunotherapy target

Background

CCNF catalyzes the transfer of ubiquitin molecules from E2 ubiquitin-conjugating enzymes to target proteins, thereby regulating the G1/S or G2/M transition of tumor cells. Thus far, CCNF expression and its potential as a pancancer biomarker and immunotherapy target have not been reported.

Methods

TCGA datasets and the R language were used to analyze the pancancer gene expression, protein expression, and methylation levels of CCNF; the relationship of CCNF expression with overall survival (OS), recurrence-free survival (RFS), immune matrix scores, sex and race; and the mechanisms for posttranscriptional regulation of CCNF.

Results

CCNF expression analysis showed that CCNF mRNA expression was higher in cancer tissues than in normal tissues in the BRCA, CHOL, COAD, ESCA, HNSC, LUAD, LUSC, READ, STAD, and UCEC; CCNF protein expression was also high in many cancer tissues, indicating that it could be an important predictive factor for OS and RFS. CCNF overexpression may be caused by CCNF hypomethylation. CCNF expression was also found to be significantly different between patients grouped based on sex and race. Overexpression of CCNF reduces immune and stromal cell infiltration in many cancers. Posttranscriptional regulation analysis showed that miR-98-5p negatively regulates the expression of the CCNF gene.

Conclusion

CCNF is overexpressed across cancers and is an adverse prognostic factor in terms of OS and RFS in many cancers; this phenomenon may be related to hypomethylation of the CCNF gene, which could lead to cancer progression and worsen prognosis. In addition, CCNF expression patterns were significantly different among patients grouped by sex and race. Its overexpression reduces immune and stromal cell infiltration. miR-98-5p negatively regulates CCNF gene expression. Hence, CCNF is a potential pancancer biomarker and immunotherapy target.

Identification and validation of methylated PENK gene for early detection of bladder cancer using urine DNA

Background

Early detection of bladder cancer (BCa) offers patients a favorable outcome and avoids the need for cystectomy. Development of an accurate and sensitive noninvasive BCa diagnostic test is imperative. DNA methylation is an early epigenetic event in the development of BCa. Certain specific aberrant methylations could serve as useful biomarkers. The aim of this study was to identify methylation biomarkers for early detection of BCa.

Methods

CpG methylation microarray analysis was conducted on primary tumors with varying stages (T1—T4) and paired nontumor tissues from nine BCa patients. Bisulfite-pyrosequencing was performed to confirm the methylation status of candidate genes in tissues and urine sediments (n = 51). Among them, PENK was selected as a potential candidate and validated using an independent set of 169 urine sediments (55 BCa, 25 benign urologic diseases, 8 other urologic cancers, and 81 healthy controls) with a quantitative methylation-specific real time PCR (mePENK-qMSP). All statistical analyses were performed using MedCalc software version 9.3.2.0.

Results

CpG methylation microarray analysis and stepwise validation by bisulfite-pyrosequencing for tissues and urine sediments supported aberrant methylation sites of the PENK gene as potential biomarkers for early detection of BCa. Clinical validation of the mePENK-qMSP test using urine sediment-DNA showed a sensitivity of 86.5% (95% CI: 71.2 – 95.5%), a specificity of 92.5% (95% CI: 85.7 – 96.7%), and an area under ROC of 0.920 (95% CI: 0.863 – 0.959) in detecting Ta high-grade and advanced tumor stages (T1-T4) of BCa patients. Sensitivities for Ta low-grade, Ta high-grade, T1 and T2-T4 were 55.6, 83.3, 88.5, and 100%, respectively. Methylation status of PENK was not correlated with sex, age or stage, while it was associated with the tumor grade of BCa.

Conclusions

In this study, we analyzed the comprehensive patterns of DNA methylation identified that PENK methylation possesses a high potential as a biomarker for urine-based early detection of BCa. Validation of PENK methylation confirms that it could significantly improve the noninvasive detection of BCa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10275-2.

An Overview of DNA Methylation Indicators for the Course of Oral Precancer

DNA methylation is a physiologically epigenetic alteration that happens when a methyl group is introduced to a CpG dinucleotide in the gene-regulating sequence of DNA. However, the majority of oral cancers have a well-defined precancerous stage; there are few clinical and morphological parameters for detecting and signalling the progression of precancerous to malignant tumours. DNA methylation forms are dynamic and reversible, allowing them to adjust to environmental or therapeutic changes. We did an extensive investigation to compile the data supporting aberrant DNA methylation forms as a possible biomarker for prediction. According to two longitudinal studies, p16 hypermethylation was considerably higher in precancerous lesions that progressed to cancer than in lesions that shrank. Most of the studies examined for this study were tiny cross-sectional research with scant validation and inadequately specified control groups. Existing evidence suggests that DNA methylation sequences can be relevant as a diagnostic biomarker for OPS development; however, sample size and research design restrictions make it difficult to draw definitive conclusions. Strong studies, including extensive epigenome-wide methylation scans of OPS with longitudinal monitoring, are necessary in this study in order to corroborate the recently discovered signals and discover new risk loci and disease progression molecular pathways.

Detecting Early-Stage Oral Cancer from Clinically Diagnosed Oral Potentially Malignant Disorders by DNA Methylation Profile

Simple Summary

Clinically, early-stage oral cancers are difficult to distinguish from oral potentially malignant disorders (OPMDs) because they show a variety of mucosal pathologies. Therefore, invasive tissue biopsies should be performed to determine the treatment strategy. Previously, we focused on gargle fluid as a noninvasive testing method and reported aberrant methylation in gargle fluid in patients with oral cancer. In this study, we successfully identified aberrantly methylated genes in early-stage oral cancer and reported that a combination of methylation of six genes could distinguish early-stage oral cancer from OPMDs, with high diagnostic performance. In addition, the methylation panel more accurately reflected the presence of early-stage oral cancer than cytology testing. Our results suggest that the methylation panel using gargle fluid has the potential to be used as a noninvasive screening tool to diagnose early-stage cancer.

Abstract

Clinically, early-stage oral cancers are difficult to distinguish from oral potentially malignant disorders (OPMDs), and invasive tissue biopsy should be performed to determine a treatment strategy. Previously, we focused on gargle fluid as a noninvasive testing method and reported aberrant methylation in gargle fluid in patients with oral cancer. This study aimed to distinguish early-stage oral cancer from clinically diagnosed OPMDs using gargle fluid samples. We collected gargle fluid samples from 40 patients who were clinically diagnosed with OPMDs in the training set; among them, 9 patients were pathologically diagnosed with oral cancer. Methylation levels of 25 tumor suppressor genes were analyzed using the methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) method. We found that a combination of six genes (TP73, CASP8, RARB, KLLN, GSTP1, and CHFR) could distinguish oral cancer from clinically diagnosed OPMDs with high diagnostic performance (area under the curve [AUC], 0.885; sensitivity, 77.8%; and specificity, 87.1%). Additionally, the panel comprised of the six methylated genes was validated in the test set. Furthermore, when compared with cytology testing, the panel could accurately detect oral cancer. The present methylated gene panel may serve as a novel biomarker for oral cancer.

Effect of aberrant DNA methylation on cancer stem cell properties

DNA methylation, as an epigenetic mechanism, occurs by adding a methyl group of cytosines in position 5 by DNA methyltransferases and has essential roles in cellular function, especially in the transcriptional regulation of embryonic and adult stem cells. Hypomethylation and hypermethylation cause either the expression or inhibition of genes, and there is a tight balance between regulating the activation or repression of genes in normal cellular activity. Abnormal methylation is well-known hallmark of cancer development and progression and can switch normal stem cells into cancer stem cells. Cancer Stem Cells (CSCs) are minor populations of tumor cells that exhibit unique properties such as self-regeneration, resistance to chemotherapy, and high ability of metastasis. The purpose of this paper is to show how aberrant DNA methylation accumulation affects self-renewal, differentiation, multidrug-resistant, and metastasis processes in cancer stem cells.

Neurofibromin and suppression of tumorigenesis: beyond the GAP

Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic disease and one of the most common inherited tumor predisposition syndromes, affecting 1 in 3000 individuals worldwide. The NF1 gene encodes neurofibromin, a large protein with RAS GTP-ase activating (RAS-GAP) activity, and loss of NF1 results in increased RAS signaling. Neurofibromin contains many other domains, and there is considerable evidence that these domains play a role in some manifestations of NF1. Investigating the role of these domains as well as the various signaling pathways that neurofibromin regulates and interacts with will provide a better understanding of how neurofibromin acts to suppress tumor development and potentially open new therapeutic avenues. In this review, we discuss what is known about the structure of neurofibromin, its interactions with other proteins and signaling pathways, its role in development and differentiation, and its function as a tumor suppressor. Finally, we discuss the latest research on potential therapeutics for neurofibromin-deficient neoplasms.

A five-gene methylation signature predicts overall survival of patients with clear cell renal cell carcinoma

BACKGROUND

In this study, we aimed to screen methylation signatures associated with the prognosis of patients with clear cell renal cell carcinoma (ccRCC).

METHODS

Gene expression and methylation profiles of ccRCC patients were downloaded from publicly available databases, and differentially expressed genes (DEGs)-differentially methylated genes (DMGs) were obtained. Subsequently, gene set enrichment and transcription factor (TF) regulatory network analyses were performed. In addition, a prognostic model was constructed and the relationship between disease progression and immunity was analyzed.

RESULTS

A total of 23 common DEGs-DMGs were analyzed, among which 14 DEGs-DMGs were obtained with a cutoff value of PCC < 0 and p < 0.05. The enrichment analysis showed that the 14 DEGs-DMGs were enriched in three GO terms and three KEGG pathways. In addition, a total of six TFs were shown to be associated with the 14 DEGs-DMGs, including RP58, SOX9, NF-κB65, ATF6, OCT, and IK2. A prognostic model using five optimized DEGs-DMGs which efficiently predicted survival was constructed and validated using the GSE105288 dataset. Additionally, four types of immune cells (NK cells, macrophages, neutrophils, and cancer-associated fibroblasts), as well as ESTIMATE, immune, and stromal scores were found to be significantly correlated with ccRCC progression (normal, primary, and metastasis) in addition to the five optimized DEGs-DMGs.

CONCLUSION

A five-gene methylation signature with the predictive ability for ccRCC prognosis was investigated in this study, consisting of CCNB2, CDKN1C, CTSH, E2F2, and ERMP1. In addition, potential targets for methylation-mediated immunotherapy were highlighted.

Sesamol Epigenetically Induces Estrogen Receptor α Re-expression by Upregulating miR-370-3p in Estrogen Receptor α-Negative Breast Cancer

Due to lack of estrogen receptor α (ERα, gene name: ESR1), ERα-negative breast carcinoma is insensitive to endocrine therapy, and restoration of ERα has become a promising strategy for ERα-negative breast cancer treatment. Sesamol, a naturally occurring phenolic compound, is usually extracted from sesame seeds. Previous investigations have unmasked its anti-oxidant and anti-inflammation properties. In this study, sesamol induced ERα functional re-expression followed by upregulation of its downstream pS2 and GREB1 genes in ERα-negative breast carcinoma. Moreover, it endowed responsiveness of ERα-negative breast carcinoma to the endocrine treatment drug 4-hydroxytamoxifen without influencing the viability of normal human umbilical vein endothelial cells. Mechanistically, sesamol induced ESR1 gene promoter demethylation by downregulating the expression of the DNA methyltransferases DNMT3A and DNMT3B, without affecting DNMT1. Moreover, the non-coding RNA miR-370-3p directly targeted DNMT3A and DNMT3B mRNA, and its expression increased upon treatment with sesamol. Artificial abrogation of miR-370-3p expression with an antagomir abolished the inhibition of DNMT3A and DNMT3B expression by sesamol, resulting in a fallback in ERα reactivation. In mice, sesamol significantly induced ERα re-expression via miR-370-3p-mediated downregulation of DNMT3A and DNMT3B. Sesamol may be a safe and effective option for clinical adjuvant therapy in patients with ERα-negative breast cancer.

Assessment of Circulating Nucleic Acids in Cancer: From Current Status to Future Perspectives and Potential Clinical Applications

Current approaches for cancer detection and characterization are based on radiological procedures coupled with tissue biopsies, despite relevant limitations in terms of overall accuracy and feasibility, including relevant patients' discomfort. Liquid biopsies enable the minimally invasive collection and analysis of circulating biomarkers released from cancer cells and stroma, representing therefore a promising candidate for the substitution or integration in the current standard of care. Despite the potential, the current clinical applications of liquid biopsies are limited to a few specific purposes. The lack of standardized procedures for the pre-analytical management of body fluids samples and the detection of circulating biomarkers is one of the main factors impacting the effective advancement in the applicability of liquid biopsies to clinical practice. The aim of this work, besides depicting current methods for samples collection, storage, quality check and biomarker extraction, is to review the current techniques aimed at analyzing one of the main circulating biomarkers assessed through liquid biopsy, namely cell-free nucleic acids, with particular regard to circulating tumor DNA (ctDNA). ctDNA current and potential applications are reviewed as well.

The Effects of 5-Aza-2'-Deoxycytidine and Valproic Acid on Apoptosis Induction and Cell Growth Inhibition in Colon Cancer HT 29 Cell Line

Background:

Epigenetic changes, including DNA methylation and histone modification, alter gene expression without the nucleotide template alterations and are associated with all stages of tumor formation and progression. Previously, we investigated the effects of DNA demethylating agents and histone deacetylase inhibitors on hepatocellular carcinoma and colon cancers. The current study aimed to investigate the effects of 5-aza-2'-deoxycytidine (5-AZA-CdR, decitabine) and valproic acid (VPA), individually as well as combined on apoptosis induction and cell growth inhibition in colon cancer HT 29 cell line.

Methods:

The effect of the compounds on the cell viability was measured by MTT assay. To determine cell apoptosis, the cells were treated with 5-aza-CdR and VPA. Propidium iodide was used for staining and the cells were analyzed using flow cytometry.

Results:

Both agents decreased cell viability in a time and dose-dependent manner significantly (P < 0.002). The results of flow cytometry demonstrated that 5-aza-CdR and VPA induced apoptosis significantly as opposed to control groups. Maximal percentage of apoptotic cells was obtained after 48 h with combined treatment.

Conclusions:

Our findings suggest that 5-aza-CdR and VPA can significantly inhibit cell growth and induce apoptosis in colon cancer HT 29 cell line.

Transcriptional E2F1/2/3/6 as potential prognostic biomarkers in cutaneous melanoma

Although the abnormal expression of members of the E2F family has been reported to participate in carcinogenesis in many human types of cancer, the bioinformatics role of the E2F family in melanoma is unknown. This research was designed to detect the expression, methylation, prognostic value and potential effects of the E2F family in melanoma. We investigated E2F family mRNA expression from the Oncomine and GEPIA databases and their methylation status in the MethHC database. Meanwhile, we detected the relative E2F family expression levels by qPCR and immunohistochemistry. Kaplan-Meier Plotter was used to draw survival analysis charts, and gene functional enrichment analyses were applied through cBioPortal database analysis. E2F1/2/3/4/5/6 mRNA and proteins were clearly upregulated in cutaneous melanoma patients, and high expression levels of E2F1/2/3/6 were statistically related to high methylation levels. Increased mRNA expression of E2F1/2/3/6 was related to lower overall survival rates (OS) and disease-free survival (DFS) in cutaneous melanoma cases. Meanwhile, E2F1/2/3/6 carried out these effects through regulating multiple signaling pathways, including the MAPK, PI3K-Akt and p53 signaling pathways. Taking together, our findings suggest that E2F1/2/3/6 could act as potential targets for precision therapy in cutaneous melanoma patients.

Hypomethylation of PlncRNA-1 promoter enhances bladder cancer progression through the miR-136-5p/Smad3 axis

Apart from being potential prognostic biomarkers and therapeutic targets, long non-coding RNAs (lncRNAs) modulate the development and progression of multiple cancers. PlncRNA-1 is a newly discovered lncRNA that exhibits the above properties through multiple regulatory pathways. However, the clinical significance and molecular mechanisms of PlncRNA-1 in bladder cancer have not been established. PlncRNA-1 was found to be overexpressed in 71.43% of bladder cancer tissues. Moreover, the expression level correlated with tumor invasion, T stage, age, and number of tumors, but not with gender, recurrent status, preoperative treatment, pathological grade, and tumor size. The expression level of PlncRNA-1 can, to a certain extent, be used as a predictor of the degree of tumor invasion and T stage among BC patients. Inhibiting PlncRNA-1 expression impaired the proliferation, migration, and invasion of T24 and 5637 bladder cancer cells in vitro and in vivo. Specifically, PlncRNA-1 promoter in BC tissues was found to be hypomethylated at position 131 (36157603 on chromosome 21). PlncRNA-1 promoter hypomethylation induces the overexpression of PlncRNA-1. In addition, PlncRNA-1 modulated the expression of smad3 and has-miR-136-5p (miR-136). Conversely, miR-136 regulated the expression of PlncRNA-1 and smad3. PlncRNA-1 mimics competitive endogenous RNA (ceRNA) in its regulation of smad3 expression by binding miR-136. Rescue analysis further revealed that modulation of miR-136 could reverse the expression of smad3 and epithelial–mesenchymal transition (EMT) marker proteins impaired by PlncRNA-1. In summary, PlncRNA-1 has important clinical predictive values and is involved in the post-transcriptional regulation of smad3. The PlncRNA-1/miR-136/smad3 axis provides insights into the regulatory mechanism of BC, thus may serve as a potential therapeutic target and prognostic biomarker for cancer.

Comparison of methylation capture sequencing and Infinium MethylationEPIC array in peripheral blood mononuclear cells

Background

Epigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium MethylationEPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price.

Methods

Epigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000 ng), medium (300–1000 ng), and low (150 ng–300 ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array.

Results

After quality control, an average of 3,708,550 CpG sites per sample were detected by MC-seq with DNA quantity > 1000 ng. Reproducibility of DNA methylation in MC-seq-detected CpG sites was high among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98–0.99). However, methylation for a small proportion of CpGs (N = 235) differed significantly between the two platforms, with differences in beta values of greater than 0.5.

Conclusions

Our results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.

DNA methylation biomarker selected by an ensemble machine learning approach predicts mortality risk in an HIV-positive veteran population

Background: With the improved life expectancy of people living with HIV (PLWH), identifying vulnerable subpopulations at high mortality risk is important. Evidences showed that DNA methylation (DNAm) is associated with mortality in non-HIV populations. Here, we established a panel of DNAm biomarkers that can predict mortality risk among PLWH.

Methods: 1,081 HIV-positive participants from the Veterans Ageing Cohort Study (VACS) were divided into training (N = 460), validation (N = 114), and testing (N = 507) sets. VACS index was used as a measure of mortality risk among PLWH. Model training and fine-tuning were conducted using the ensemble method in the training and validation sets and prediction performance was assessed in the testing set. The survival analysis comparing the predicted high and low mortality risk groups and the Gene Ontology enrichment analysis of the predictive CpG sites were performed.

Results: We selected a panel of 393 CpGs for the ensemble prediction model that showed excellent performance in predicting high mortality risk with an auROC of 0.809 (95%CI: 0.767,0.851) and a balanced accuracy of 0.653 (95%CI: 0.611, 0.693) in the testing set. The high mortality risk group was significantly associated with 10-year mortality (hazard ratio = 1.79, p = 4E-05) compared with low risk group. These 393 CpGs were located in 280 genes enriched in immune and inflammation response pathways.

Conclusions: We identified a panel of DNAm features associated with mortality risk in PLWH. These DNAm features may serve as predictive biomarkers for mortality risk among PLWH.

Abbreviations: AUC: Area Under Curve; CI: Confidence interval; DMR: differentially methylated region; DNA: Deoxyribonucleic acid; DNAm: DNA methylation; DAVID: Database for Annotation, Visualization, and Integrated Discovery; EWA: epigenome-wide association; FDR: False discovery rate; FWER: Family-wise error rate; GLMNET: elastic-net-regularized generalized linear models; GO: Gene ontology; HIV: Human immunodeficiency virus; HM450K: Human Methylation 450 K BeadChip; k-NN: k-nearest neighbours; NK: Natural killer; PC: Principal component; PLWH: people living with HIV; QC: Quality control; SVM: Support Vector Machines; VACS: Veterans Ageing Cohort Study; XGBoost: Extreme Gradient Boosting Tree

Aberrantly Methylated and Expressed Genes as Prognostic Epigenetic Biomarkers for Colon Cancer

This study aimed to identify prognostic epigenetic biomarkers for colon cancer (CC). Methylation and mRNA expression in CC samples with clinical characteristics that corresponded to those in The Cancer Genome Atlas were analyzed. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were screened between matched tumor and nontumor tissues. Among the 415 DEGs and DMGs that significantly correlated between cytosine-phosphate-guanine (CpG) methylation and gene expression, unc-5 netrin receptor C (UNC5C), solute carrier family 35 member F (SLC35F)1, Ly6/Neurotoxin (LYNX)1, stathmin (STMN)2, slit guidance ligand (SLIT)3, cell adhesion molecule L1 like (CHL1), CAP-Gly domain containing linker protein family member 4 (CLIP4), transmembrane protein (TMEM) 255A, granzyme B (GZMB), and brain expressed X-Linked (BEX)1 were promising epigenetic biomarkers. Prediction was more accurate when models were based on the expression and/or methylation of GZMB rather than clinical stage. Comparisons of tissues with high or low GZMB expression significantly associated the DEGs with natural killer-mediated cytotoxicity, cytokine-cytokine receptor interactions, and chemokine signaling pathways. From among the 10 epigenetic biomarkers, GZMB might serve as a tumor suppressor and function in several immune-related pathways in CC. Prognostic models based on GZMB expression and/or methylation would be significant for patients with CC.

DNA methylation and gene expression of sFRP2, sFRP4, Dkk 1, and Wif1 during osteoblastic differentiation of bone marrow derived mesenchymal stem cells

OBJECTIVES

Bone marrow derived mesenchymal stem cells (BMSCs) are an irresistible choice for use in stem cell therapy and regenerative medicine. BMSCs osteoblastic differentiation is also important in bone development, diseases, malignancies, and cancers studies. Wnt signaling pathway antagonists, Dickkopf-1 (Dkk 1), Secreted Frizzled-Related Proteins (sFRPs), and Wnt Inhibitory Factor 1 (Wif1) play important roles in inducing osteoblastic differentiation. This study is the first to investigate the association between DNA methylation and gene expression of Dkk1, sFRP2, sFRP4, and Wif1 during BMSCs osteoblastic differentiation.

METHODS

Human BMSCs were isolated and characterized using flow cytometry. Then, cells were treated with osteo-differentiation medium for three weeks. Alizarin red S staining and polymerase chain reaction (PCR) (alkaline phosphatase/osteocalcin) were performed for confirmation. The expression of Dkk 1, sFRP2, sFRP4, and Wif1 genes was evaluated at days 7, 14, and 21 using real-time PCR. Methylation-specific PCR (MSP) was performed to detect the methylation status of the promoters of the genes.

RESULTS

Data showed significant decreases (P < 0.05) during various days of BMSCs differentiation, while the promoters of the genes remained mostly un-methylated.

CONCLUSIONS

The down-regulation of Dkk 1, sFRP2, sFRP4, and Wif1 regulates various stages of human BMSCs during osteoblastic differentiation. DNA methylation does not interfere in the down-regulation of these genes, except for Wif1. We propose that the Wnt antagonist gene promoters should remain un-methylated during osteoblastic differentiation of BMSCs and that the down-regulation of these genes may contribute to other epigenetic mechanisms, other than DNA methylation, which implicitly indicates the role of DNA methylation in osteogenic cancers.

Genome-wide methylation patterns predict clinical benefit of immunotherapy in lung cancer

Background

It is crucial to unravel molecular determinants of responses to immune checkpoint blockade (ICB) therapy because only a small subset of advanced non-small cell lung cancer (NSCLC) patients responds to ICB therapy. Previous studies were concentrated on genomic and transcriptomic markers (e.g., mutation burden and immune gene expression). However, these markers are not sufficient to accurately predict a response to ICB therapy.

Results

Here, we analyzed DNA methylomes of 141 advanced NSCLC samples subjected to ICB therapy (i.e., anti-programmed death-1) from two independent cohorts (60 and 81 patients from our and IDIBELL cohorts). Integrative analysis of patients with matched transcriptome data in our cohort (n = 28) at pathway level revealed significant overlaps between promoter hypermethylation and transcriptional repression in nonresponders relative to responders. Fifteen immune-related pathways, including interferon signaling, were identified to be enriched for both hypermethylation and repression. We built a reliable prognostic risk model based on eight genes using LASSO model and successfully validated the model in independent cohorts. Furthermore, we found 30 survival-associated molecular interaction networks, in which two or three hypermethylated genes showed significant mutual exclusion across nonresponders.

Conclusions

Our study demonstrates that methylation patterns can provide insight into molecular determinants underlying the clinical benefit of ICB therapy.

Significant decrease of a master regulator of genes (REST/NRSF) in high-grade squamous intraepithelial lesion and cervical cancer

Background

Methods

Results

Conclusion

Cold-hearted: A case for cold stress in cancer risk

A negative correlation exists between environmental temperature and cancer risk based on both epidemiological and statistical analyses. Previously, cold stress was reported to be an effective cause of tumorigenesis. Several studies have demonstrated that cold temperature serves as a potential risk factor in cancer development. Most recently, a link was demonstrated between the effects of extreme cold climate on cancer incidence, pinpointing its impact on tumour suppressor genes by causing mutation. The underlying mechanism behind cold stress and its association with tumorigenesis is not well understood. Hence, this review intends to shed light on the role of associated factors, genetic and/or non-genetic, which are modulated by cold temperature, and eventually influence tumorigenic potential. While scrutinizing the effect of cold exposure on the body, the expression of certain genes, e.g. uncoupled proteins and heat-shock proteins, were elevated. Biological chemicals such as norepinephrine, thyroxine, and cholesterol were also elevated. Brown adipose tissue, which plays an essential role in thermogenesis, displayed enhanced activity upon cold exposure. Adaptive measures are utilized by the body to tolerate the cold, and in doing so, invites both epigenetic and genetic changes. Unknowingly, these adaptive strategies give rise to a lethal outcome i.e., genesis of cancer. Concisely, this review attempts to draw a link between cold stress, genetic and epigenetic changes, and tumorigenesis and aspires to ascertain the mechanism behind cold temperature-mediated cancer risk.

Septin 9 Methylation in Nasopharyngeal Swabs: A Potential Minimally Invasive Biomarker for the Early Detection of Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is highly prevalent in Southeast Asia, and an unfavorable outcome is usually attributed to advanced stage NPC. Current methods for the early diagnosis of NPC have limitations in clinical practice. The aim of this study was to investigate the diagnostic ability of Septin 9 methylation for NPC. A quantitative methylation-sensitive PCR (qMS-PCR) assay was developed to measure the methylation status and levels of Septin 9 in nasopharyngeal tissues and paired swabs from patients with NPC, chronic nasopharyngitis, and healthy donors. Methylated Septin 9 was detected in 92% (23/25) of NPC tissues and 25% (4/16) of nasopharyngitis controls (p < 0.05). High-frequency hypermethylation with decreased mRNA expression of Septin 9 in NPC was also identified. Further, Septin 9 methylation was identified in 90.5% (19/21) of NPC biopsies and 71.4% (15/21) of paired swabs, indicating a good concordance between the two sample types. In addition, methylated Septin 9 was found in 16 (72.7%) nasal swabs from 22 NPC patients, 2 of 19 (10.5%) nasopharyngitis, but not in any of the healthy controls (p < 0.01). The methylation score in nasal swabs of the NPC group was also significantly higher than that of non-NPC controls (p < 0.001). Moreover, receiver operating characteristic (ROC) curve analysis showed an area under the curve (AUC) of 0.882 of Septin 9 methylation tests to discriminate NPC from non-NPC subjects. Our study demonstrated that frequent methylation of Septin 9 was present in NPC. Its detection in nasopharyngeal swabs may provide a minimally invasive and informative method for identifying early NPC cases.

The Emerging Roles of RNA Modifications in Glioblastoma

Glioblastoma (GBM) is a grade IV glioma that is the most malignant brain tumor type. Currently, there are no effective and sufficient therapeutic strategies for its treatment because its pathological mechanism is not fully characterized. With the fast development of the Next Generation Sequencing (NGS) technology, more than 170 kinds of covalent ribonucleic acid (RNA) modifications are found to be extensively present in almost all living organisms and all kinds of RNAs, including ribosomal RNAs (rRNAs), transfer RNAs (tRNAs) and messenger RNAs (mRNAs). RNA modifications are also emerging as important modulators in the regulation of biological processes and pathological progression, and study of the epi-transcriptome has been a new area for researchers to explore their connections with the initiation and progression of cancers. Recently, RNA modifications, especially m6A, and their RNA-modifying proteins (RMPs) such as methyltransferase like 3 (METTL3) and α-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5), have also emerged as important epigenetic mechanisms for the aggressiveness and malignancy of GBM, especially the pluripotency of glioma stem-like cells (GSCs). Although the current study is just the tip of an iceberg, these new evidences will provide new insights for possible GBM treatments. In this review, we summarize the recent studies about RNA modifications, such as N6-methyladenosine (m6A), N6,2'O-dimethyladenosine (m6Am), 5-methylcytosine (m5C), N1-methyladenosine (m1A), inosine (I) and pseudouridine (ψ) as well as the corresponding RMPs including the writers, erasers and readers that participate in the tumorigenesis and development of GBM, so as to provide some clues for GBM treatment.

Feasibility of endometrial sampling by vaginal tampons in women with Lynch syndrome

Background

Endometrial sampling for the surveillance of women with Lynch syndrome is an invasive and painful procedure. The aim of this study was to evaluate the feasibility of a less invasive procedure of collecting vital cells by vaginal tampons.

Methods

This was a prospective feasibility study of women scheduled to undergo annual gynecological surveillance, including endometrial sampling. We included consecutive asymptomatic women with Lynch syndrome or first-degree relatives and asked them to insert a vaginal tampon 2–4 h before attending their outpatient appointment. Feasibility was evaluated by the following metrics: patient acceptance, pain intensity of each procedure (assessed by visual analog scale; range 0–10), and the presence of vital cells obtained by tampon-based or endometrial sampling methods. Two pathologists independently evaluated all samples.

Results

In total, 25 of 32 approached women completed the tampon-based procedure, with 23 of these subsequently undergoing invasive endometrial sampling. The median visual analog scale scores for tampon use and invasive endometrial sampling were 0 (range, 0–10) and 5.5 (range, 1–10) (p < 0.001). None of the tampon samples analyzed by cytology showed endometrial cells, but they did contain vital squamous cells and granulocytes. By contrast, 18 (78%) of the invasive endometrial samples contained enough endometrial tissue for analysis. No endometrial abnormalities were found by endometrial sampling.

Conclusions

Tampon-based endometrial surveillance was a well-accepted and non-painful procedure, and although tampons contained vital cells, they did not provide endometrial cells. However, this study was limited to asymptomatic women with Lynch syndrome (no endometrial pathology), indicating that research is needed to evaluate whether the tampon method has any utility for endometrial surveillance in women with Lynch syndrome.

Host proteome linked to HPV E7-mediated specific gene hypermethylation in cancer pathways

Background

Human papillomavirus (HPV) infection causes around 90% of cervical cancer cases, and cervical cancer is a leading cause of female mortality worldwide. HPV-derived oncoprotein E7 participates in cervical carcinogenesis by inducing aberrant host DNA methylation. However, the targeting specificity of E7 methylation of host genes is not fully understood but is important in the down-regulation of crucial proteins of the hallmark cancer pathways. In this study, we aim to link E7-driven aberrations in the host proteome to corresponding gene promoter hypermethylation events in the hope of providing novel therapeutic targets and biomarkers to indicate the progression of cervical cancer.

Methods

HEK293 cells were transfected with pcDNA3.1-E7 plasmid and empty vector and subjected to mass spectrometry-based proteomic analysis. Down-regulated proteins (where relative abundance was determined significant by paired T-test) relevant to cancer pathways were selected as gene candidates for mRNA transcript abundance measurement by qPCR and expression compared with that in SiHa cells (HPV type 16 positive). Methylation Specific PCR was used to determine promoter hypermethylation in genes downregulated in both SiHa and transfected HEK293 cell lines. The FunRich and STRING databases were used for identification of potential regulatory transcription factors and the proteins interacting with transcription factor gene candidates, respectively.

Results

Approximately 400 proteins totally were identified in proteomics analysis. The transcripts of six genes involved in the host immune response and cell proliferation (PTMS, C1QBP, BCAP31, CDKN2A, ZMYM6 and HIST1H1D) were down-regulated, corresponding to proteomic results. Methylation assays showed four gene promoters (PTMS, C1QBP, BCAP31 and CDKN2A) were hypermethylated with 61, 55.5, 70 and 78% increased methylation, respectively. Those four genes can be regulated by the GA-binding protein alpha chain, specificity protein 1 and ETS-like protein-1 transcription factors, as identified from FunRich database predictions.

Conclusions

HPV E7 altered the HEK293 proteome, particularly with respect to proteins involved in cell proliferation and host immunity. Down-regulation of these proteins appears to be partly mediated via host DNA methylation. E7 possibly complexes with the transcription factors of its targeting genes and DNMT1, allowing methylation of specific target gene promoters.

Co-occurrence and Mutual Exclusivity Analysis of DNA Methylation Reveals Distinct Subtypes in Multiple Cancers

Co-occurrence and mutual exclusivity (COME) of DNA methylation refer to two or more genes that tend to be positively or negatively correlated in DNA methylation among different samples. Although COME of gene mutations in pan-cancer have been well explored, little is known about the COME of DNA methylation in pan-cancer. Here, we systematically explored the COME of DNA methylation profile in diverse human cancer. A total of 5,128,332 COME events were identified in 14 main cancers types in The Cancer Genome Atlas (TCGA). We also identified functional epigenetic modules of the zinc finger gene family in six cancer types by integrating the gene expression and DNA methylation data and the frequently occurred COME network. Interestingly, most of the genes in those functional epigenetic modules are epigenetically repressed. Strikingly, those frequently occurred COME events could be used to classify the patients into several subtypes with significant different clinical outcomes in six cancers as well as pan-cancer (p-value ≤ = 0.05). Moreover, we observed significant associations between different COME subtypes and clinical features (e.g., age, gender, histological type, neoplasm histologic grade, and pathologic stage) in distinct cancers. Taken together, we identified millions of COME events of DNA methylation in pan-cancer and detected functional epigenetic COME events that could separate tumor patients into different subtypes, which may benefit the diagnosis and prognosis of pan-cancer.

Dissecting Molecular Features of Gliomas: Genetic Loci and Validated Biomarkers

Recently, several studies focused on the genetics of gliomas. This allowed identifying several germline loci that contribute to individual risk for tumor development, as well as various somatic mutations that are key for disease classification. Unfortunately, none of the germline loci clearly confers increased risk per se. Contrariwise, somatic mutations identified within the glioma tissue define tumor genotype, thus representing valid diagnostic and prognostic markers. Thus, genetic features can be used in glioma classification and guided therapy. Such copious genomic variabilities are screened routinely in glioma diagnosis. In detail, Sanger sequencing or pyrosequencing, fluorescence in-situ hybridization, and microsatellite analyses were added to immunohistochemistry as diagnostic markers. Recently, Next Generation Sequencing was set-up as an all-in-one diagnostic tool aimed at detecting both DNA copy number variations and mutations in gliomas. This approach is widely used also to detect circulating tumor DNA within cerebrospinal fluid from patients affected by primary brain tumors. Such an approach is providing an alternative cost-effective strategy to genotype all gliomas, which allows avoiding surgical tissue collection and repeated tumor biopsies. This review summarizes available molecular features that represent solid tools for the genetic diagnosis of gliomas at present or in the next future.

A 13-gene risk score system and a nomogram survival model for predicting the prognosis of clear cell renal cell carcinoma

BACKGROUND

Renal cell carcinoma (RCC) is the second common malignant tumor in the urinary system, and 85% of RCC cases are clear cell RCC (ccRCC). This study is designed to build a risk score system for ccRCC.

METHODS

The gene methylation and expression data of ccRCC samples were downloaded from The Cancer Genome Atlas database (training set) and ArrayExpress database (validation set). The differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified by limma package, and their intersecting genes with negative Pearson correlation coefficients were remained using cor.test function. Prognosis-associated genes were identified by survival package, and the optimal DMGs were obtained using penalized package. After risk score system was built, nomogram survival model was constructed using rms package. Additionally, pathways were enriched for the DEGs between high- and low-risk groups using Gene Set Enrichment Analysis.

RESULTS

There were 3,638 DMGs and 2,702 DEGs between tumor and normal samples. Among the 312 intersecting genes, 43 prognosis-associated genes were identified. A total of 13 optimal DMGs (BTBD19, ADAM8, BGLAP, TNFRSF13C, JPH4, BEST1, GNRH2, UBE2QL1, CHODL, GDF9, UPB1, KCNH3; and ADAMTSL4) were obtained for building the risk score system. After pathological M, pathological T, platelet qualitative, and RS status were revealed to be independent prognostic factors, a nomogram survival model was constructed. For the 920 DEGs between the high- and low-risk samples, 6 significant pathways were enriched.

CONCLUSION

The 13-gene risk score system and the nomogram survival model might be used for prognostic prediction of ccRCC patients.

Ultra-low level detection of hepatocellular carcinoma global methylation using a AuNP modified carbon fiber microelectrode

Hepatocellular carcinoma (HCC) is one of the most common cancerous diseases, with a low 5 year survival rate. Global hypomethylation drives genomic instability, which is regarded as one biomarker for early diagnosis. Long interspersed nucleotide element-1 (LINE-1) makes up around 17% of the genome, and could be regarded as a surrogate marker for global DNA methylation. In this work, a gold nanoparticle (AuNP) modified carbon fiber microelectrode (CFME) with a diameter of 7 μm was applied for the first time to detect the methylation level of LINE-1, by distinguishing adsorption affinities between different DNA bases and AuNPs. Several parameters, including AuNP electrodeposition time, sample adsorption time, and DNA concentration have been analyzed and optimized. The detection limit of our assay was 0.1 nM with only 2 μL sample solution. And the CFME had an excellent sensitivity of 10% methylation change and had the capacity to distinguish only one methylated CpG site. The global DNA methylation level of real samples including cell lines and clinical tissues was tested. Higher signals of HCC cell lines and cancer tissues were observed respectively, compared with normal hepatic cell lines and normal tissues. This work provides a promising approach for HCC early diagnosis and prognosis.

Using a AuNP modified carbon fiber microelectrode to detect hepatocellular carcinoma global methylation with an ultra-low concentration of DNA samples.

The Gasdermin E Gene Has Potential as a Pan-Cancer Biomarker, While Discriminating between Different Tumor Types

Due to the elevated rates of incidence and mortality of cancer, early and accurate detection is crucial for achieving optimal treatment. Molecular biomarkers remain important screening and detection tools, especially in light of novel blood-based assays. DNA methylation in cancer has been linked to tumorigenesis, but its value as a biomarker has not been fully explored. In this study, we have investigated the methylation patterns of the Gasdermin E gene across 14 different tumor types using The Cancer Genome Atlas (TCGA) methylation data (N = 6502). We were able to identify six CpG sites that could effectively distinguish tumors from normal samples in a pan-cancer setting (AUC = 0.86). This combination of pan-cancer biomarkers was validated in six independent datasets (AUC = 0.84–0.97). Moreover, we tested 74,613 different combinations of six CpG probes, where we identified tumor-specific signatures that could differentiate one tumor type versus all the others (AUC = 0.79–0.98). In all, methylation patterns exhibited great variation between cancer and normal tissues, but were also tumor specific. Our analyses highlight that a Gasdermin E methylation biomarker assay, not only has the potential for being a methylation-specific pan-cancer detection marker, but it also possesses the capacity to discriminate between different types of tumors.

Screening of Methylation Signature and Gene Functions Associated With the Subtypes of Isocitrate Dehydrogenase-Mutation Gliomas

Isocitrate dehydrogenase (IDH) is an oncogene, and the expression of a mutated IDH promotes cell proliferation and inhibits cell differentiation. IDH exists in three different isoforms, whose mutation can cause many solid tumors, especially gliomas in adults. No effective method for classifying gliomas on genetic signatures is currently available. DNA methylation may be applied to distinguish cancer cells from normal tissues. In this study, we focused on three subtypes of IDH-mutation gliomas by examining methylation data. Several advanced computational methods were used, such as Monte Carlo feature selection (MCFS), incremental feature selection (IFS), support machine vector (SVM), etc. The MCFS method was adopted to analyze methylation features, resulting in a feature list. Then, the IFS method incorporating SVM was applied to the list to extract important methylation features and construct an optimal SVM classifier. As a result, several methylation features (sites) were found to relate to glioma subclasses, which are annotated onto multiple genes, such as FLJ37543, LCE3D, FAM89A, ADCY5, ESR1, C2orf67, REST, EPHA7, etc. These genes are enriched in biological functions, including cellular developmental process, neuron differentiation, cellular component morphogenesis, and G-protein-coupled receptor signaling pathway. Our results, which are supported by literature reports and independent dataset validation, showed that our identified genes and functions contributed to the detailed glioma subtypes. This study provided a basic research on IDH-mutation gliomas.

Circulating methylated RUNX3 and SFRP1 genes as a noninvasive panel for early detection of colorectal cancer

OBJECTIVE

This study was conducted to assess the methylation status of runt-related transcription factor 3 (RUNX3) and secreted frizzled-related protein 1 (SFRP1) genes in paired tissue and serum samples of colorectal cancer (CRC), adenomatous, and control subjects and elucidate the association between methylation status on RUNX3 and SFRP1 mRNA expression.

METHODS

Methylation status of RUNX3 and SFRP1 in paired tissue and serum samples and RUNX3 and SFRP1 mRNA expression in tissue from 85 patients with CRC, 40 with adenoma, and 40 healthy controls were determined using methylation-specific PCR and reverse transcription PCR.

RESULTS

The frequency RUNX3 and SFRP1 genes methylation was significantly higher in both tissues and serum of CRC patients and was significantly associated with absence of its corresponding mRNA expression. The concordance between tissue and serum methylation status was 94.4% for RUNX3 and 94.3% for SFRP1. Tissue RUNX3 methylation status detected CRC with 63.53% sensitivity and 80.00% specificity, while serum RUNX3 methylation status detected CRC with 60.00% sensitivity and 82.50% specificity. Tissue SFRP1 methylation status showed a sensitivity of 82.35% and specificity of 65.00%, while serum SFRP1 methylation status showed a sensitivity of 77.65% and specificity of 70.00% in detection of CRC. RUNX3/SFRP1/carcinoembryonic antigen (CEA) panel identified CRC with sensitivity of 89.41% in tissue and 84.71% in serum.

CONCLUSION

Our results verified the reliability of using serum RUNX3 and SFRP1 methylation status as a noninvasive biomarker for diagnosis of CRC and that combined detection of RUNX3/SFRP1/CEA panel might be a promising strategy for early detection of CRC.

Epigenetic signatures in overgrowth syndromes: Translational opportunities

In recent years, numerous overgrowth syndromes have been found to be caused by pathogenic DNA sequence variants in "epigenes," genes that encode proteins that function in epigenetic regulation. Epigenetic marks, including DNA methylation (DNAm), histone modifications and chromatin conformation, have emerged as a vital genome-wide regulatory mechanism that modulate the transcriptome temporally and spatially to drive normal developmental and cellular processes. Evidence suggests that epigenetic marks are layered and engage in crosstalk, in that disruptions of any one component of the epigenetic machinery impact the others. This interdependence of epigenetic marks underpins the recent identification of gene-specific DNAm signatures for a variety of disorders caused by pathogenic variants in epigenes. Here, we discuss the power of DNAm signatures with respect to furthering our understanding of disease pathophysiology, enhancing the efficacy of molecular diagnostics and identifying new targets for therapeutics of overgrowth syndromes. These findings highlight the promise of the field of epigenomics to provide unprecedented insights into disease mechanisms generating a host of opportunities to advance precision medicine.

Long non-coding RNA AK001058 regulates tumor growth and angiogenesis in colorectal cancer via methylation of ADAMTS12

Colorectal cancer, a common gastrointestinal malignant tumor, has been a leading cause of cancer related deaths. Long non-coding RNAs (lncRNAs) play an important role in regulating cancer development. The aim of this study was to investigate the role and potential mechanism of lncRNA AK001058 in colorectal cancer. To establish tumor xenografts, BALB/c nude mice received subcutaneously injection of SW480 cells with transfection targeting AK001058 (overexpression or knockdown). Tumor growth was observed and recorded. The relative gene expression levels were determined by quantitative real-time PCR or western blot. Cell apoptosis was determined by tunnel analysis. Microvessel morphology changes were detected by H&E staining. Methylation level of CpG island was analyzed using methylation specific PCR. The results showed that AK001058 overexpression notably accelerated tumor growth. AK001058 overexpression also decreased cell apoptosis, worsened microvessel morphology and increased the expression of VEGFA and angiopoietin II. Moreover, AK001058 decreased the expression of ADAMTS12 by increasing its methylation level. Nevertheless, AK001058 knockdown exerted the opposite function. Therefore, AK001058 knockdown could effectively inhibit tumor growth mostly accounting for decreased cell apoptosis and tumor angiogenesis, which was partly dependent on the high methylation level of ADATS12. These data provided a novel therapeutic strategy of colorectal cancer.

Construction of Novel DNA Methylation-Based Prognostic Model to Predict Survival in Glioblastoma

Glioblastoma (GBM) is a most aggressive primary cancer in brain with poor prognosis. This study aimed to identify novel tumor biomarkers with independent prognostic values in GBMs. The DNA methylation profiles were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database. Differential methylated genes (DMGs) were screened from recurrent GBM samples using limma package in R software. Functional enrichment analysis was performed to identify major biological processes and signaling pathways. Furthermore, critical DMGs associated with the prognosis of GBM were screened according to univariate and multivariate cox regression analysis. A risk score-based prognostic model was constructed for these DMGs and prediction ability of this model was validated in training and validation data set. In total, 495 DMGs were identified between recurrent samples and disease-free samples, including 356 significantly hypermethylated and 139 hypomethylated genes. Functional and pathway items for these DMGs were mainly related to sensory organ development, neuroactive ligand-receptor interaction, pathways in cancer, etc. Five genes with abnormal methylation level were significantly correlated with prognosis according to survival analysis, such as ALX1, KANK1, NUDT12, SNED1, and SVOP. Finally, the risk model provided an effective ability for prognosis prediction both in training and validation data set. We constructed a novel prognostic model for survival prediction of GBMs. In addition, we identified five DMGs as critical prognostic biomarkers in GBM progression.

A simple and low-cost screen printed electrode for hepatocellular carcinoma methylation detection

There is a great demand for robust diagnostic and prognostic approaches for Hepatocellular Carcinoma (HCC). DNA methylation, a common epigenetic modification, has been found in many promoter regions of tumor suppressor genes. Hypermethylation of these gene promoters will repress the gene transcription and lead to the occurrence of cancers. The abnormal methyation level of the p16 gene promoter could be a promising marker for the detection of HCC. The adsorption affinities between different DNA bases and AuNPs are not the same. After bisulfite treatment and asymmetric PCR, methylation and unmethylation sequences can be changed into guanine-enriched and adenine-enriched sequences, respectively. A home-made gold nanoparticle modified screen printed carbon electrode (AuNP-SPCE) was employed to distinguish the adsorption affinities between guanine-enriched and adenine-enriched sequences, which could be used to analyze the level of DNA methylation. Several key experimental factors were investigated and optimized. The results had shown that the optimal AuNP electrodeposition time was 100 s and 15 min of adsorption could distinguish guanine-enriched and adenine-enriched sequences with a concentration of 100 nM at 25 °C. The detection limit of our AuNP-SPCE was 1.1 ng, and the assay had a good sensitivity of 10% methylation change and was able to distinguish only one methylated CpG site. What's more, the RSD over three assays with a disposable AuNP-SPCE was ≤7.2%. The assay was applied to real samples including cell lines and clinical tissues. Compared with normal hepatic cell lines and normal tissues, lower signals of HCC cell lines and cancer tissues were observed, respectively. It had shown a good discrimination of the abnormal methylation level of the p16 gene promoter.

DNA methylation-regulated QPCT promotes sunitinib resistance by increasing HRAS stability in renal cell carcinoma

Rationale: Although sunitinib has been shown to improve the survival rate of advanced renal cell carcinoma (RCC) patients, poor drug response is a major challenge that reduces patient benefit. It is important to elucidate the underlying mechanism so that the therapeutic response to sunitinib can be restored. Methods: We used an Illumina HumanMethylation 850K microarray to find methylation-differentiated CpG sites between sunitinib-nonresponsive and -responsive RCC tissues and Sequenom MassARRAY methylation analysis to verify the methylation chip results. We verified glutaminyl peptide cyclotransferase (QPCT) expression in sunitinib-nonresponsive and -responsive RCC tissues via qRT-PCR, western blot and immunohistochemical assays. Then, cell counting kit 8 (CCK-8), plate colony formation and flow cytometric assays were used to verify the function of QPCT in RCC sunitinib resistance after QPCT intervention or overexpression. Chromatin immunoprecipitation (ChIP) was performed to clarify the upstream regulatory mechanism of QPCT. A human proteome microarray assay was used to identify downstream proteins that interact with QPCT, and co-immunoprecipitation (co-IP) and confocal laser microscopy were used to verify the protein chip results. Results: We found that the degree of methylation in the QPCT promoter region was significantly different between sunitinib-nonresponsive and -responsive RCC tissues. In the sunitinib-nonresponsive tissues, the degree of methylation in the QPCT promoter region was significantly reduced, and the expression of QPCT was upregulated, which correlated with a clinically poor response to sunitinib. A knockdown of QPCT conferred sunitinib sensitivity traits to RCC cells, whereas an overexpression of QPCT restored sunitinib resistance in RCC cells. Mechanistically, reducing the methylation degree of the QPCT promoter region by 5-aza-2'-deoxycytidine (decitabine) in RCC cells could increase the expression of QPCT and NF-κB (p65) bound to the QPCT promoter region, positively regulating its expression, while the hypermethylation in the QPCT promoter region could inhibit the binding of NF-κB (p65). QPCT could bind to HRAS and attenuate the ubiquitination of HRAS, thus increasing its stability and leading to the activation of the ERK pathway in RCC cells. Conclusion: QPCT may be a novel predictor of the response to sunitinib therapy in RCC patients and a potential therapeutic target.

Integrative analysis of DNA methylation and gene expression to identify key epigenetic genes in glioblastoma

Glioblastoma (GBM) ranks the most common and aggressive primary brain malignant tumor worldwide. However, the survival rates of patients remain very poor. Therefore, molecular oncology of GBM are urgently needed. In this study, we performed an integrative analysis of DNA methylation and gene expression to identify key epigenetic genes in GBM. The methylation and gene expression of GBM patients in The Cancer Genome Atlas (TCGA) database were downloaded. After data preprocessing, we identified 4,881 differentially expressed genes (DEGs) between tumor and normal samples, including 1,111 upregulated and 3,770 downregulated genes. Then, we randomly separated all samples into training set (n = 69) and testing set (n = 69). We next obtained 11,269 survival-methylation sites by univariate and multivariate Cox regression analyses. In the correlation analysis, we defined 198 low promoter methylation with high gene expression as epigenetically induced (EI) genes and 111 high promoter methylation with low gene expression as epigenetically suppressed (ES) genes. Key markers including C1orf61 and FAM50B were selected with a Pearson correlation coefficient greater than 0.75. Further, we chose the 20 CpG methylation sites of above two genes in unsupervised clustering analysis using the Euclidean distance. We found that the prognosis of the hypomethylated group was significantly better than that in the hypermethylated group (log-rank test p-value = 0.011). Based on the validation in the TCGA testing set and GEO dataset, we validated the prognostic value of our signature (p-value = 0.02 in TCGA and 0.012 in GEO). In conclusion, our findings provided predictive and prognostic value as methylation-based biomarkers for the diagnosis and treatment of GBM.