DNA Methylation-Based Point-of-Care Cancer Detection: Challenges and Possibilities

Understanding the role of DNA methylation in colorectal cancer: Mechanisms, detection, and clinical significance

Colorectal cancer (CRC) is one of the deadliest malignancies worldwide, ranking third in incidence and second in mortality. Remarkably, early stage localized CRC has a 5-year survival rate of over 90%; in stark contrast, the corresponding 5-year survival rate for metastatic CRC (mCRC) is only 14%. Compounding this problem is the staggering lack of effective therapeutic strategies. Beyond genetic mutations, which have been identified as critical instigators of CRC initiation and progression, the importance of epigenetic modifications, particularly DNA methylation (DNAm), cannot be underestimated, given that DNAm can be used for diagnosis, treatment monitoring and prognostic evaluation. This review addresses the intricate mechanisms governing aberrant DNAm in CRC and its profound impact on critical oncogenic pathways. In addition, a comprehensive review of the various techniques used to detect DNAm alterations in CRC is provided, along with an exploration of the clinical utility of cancer-specific DNAm alterations.

Transfer of blocker-based qPCR reactions for DNA methylation analysis into a microfluidic LoC system using thermal modeling

Changes in the DNA methylation landscape are associated with many diseases like cancer. Therefore, DNA methylation analysis is of great interest for molecular diagnostics and can be applied, e.g., for minimally invasive diagnostics in liquid biopsy samples like blood plasma. Sensitive detection of local de novo methylation, which occurs in various cancer types, can be achieved with quantitative HeavyMethyl-PCR using oligonucleotides that block the amplification of unmethylated DNA. A transfer of these quantitative PCRs (qPCRs) into point-of-care (PoC) devices like microfluidic Lab-on-Chip (LoC) cartridges can be challenging as LoC systems show significantly different thermal properties than qPCR cyclers. We demonstrate how an adequate thermal model of the specific LoC system can help us to identify a suitable thermal profile, even for complex HeavyMethyl qPCRs, with reduced experimental effort. Using a simulation-based approach, we demonstrate a proof-of-principle for the successful LoC transfer of colorectal SEPT9/ACTB-qPCR from Epi Procolon® colorectal carcinoma test, by avoidance of oligonucleotide interactions.

Effect of Alcohol Intake on Inflammatory Status and Prognosis in Cancer Patients

Purpose

To explore the effect of alcohol on the inflammatory status and prognosis of patients with malignancy.

Patients and Methods

The clinical data of patients with malignant tumor who were admitted to the First Hospital of Jilin University from November 2011 to December 2018 were collected including basic clinical information, anthropometric indicators, body composition analysis, and serological indicators. Univariate and multivariate Cox proportional hazards models were performed to find predictors of survival. A nomogram was generated to indicate the interrelationships between the variables in the prediction model and the extent to which alcohol consumption affects prognosis. The C-index and calibration curves were used to verify the predictive accuracy of the scoring system.

Results

A total of 2929 cancer patients were included in this study, of which 552 (18.8%) patients had alcohol consumption habits and 2377 (81.2%) patients had no alcohol history. Patients in the Alcohol group had significantly shorter overall survival (OS) than the Non-Alcohol group, and further sub-analysis indicated alcohol consumption was significantly associated with prognosis of advanced breast cancer (HR = 4.617, 95% CI 1.361–15.664, p=0.014), and early stage hepatocellular carcinoma (HCC) without viral hepatitis (HR = 8.933, 95% CI 1.444–55.275, p = 0.019). Multivariate Cox regression models also demonstrated that daily alcohol intake was a risk factor of survival benefits (HR = 1.256, 95% CI 1.016–1.554, p = 0.036). Finally, a nomogram was constructed and the c-index of this scoring system is 0.751. The 3- and 5-year calibration curves of the model show a high agreement between the predicted probability and the actual observed survival rate.

Conclusion

Alcohol intake was demonstrated associates with patient outcomes. A human component-prognosis scoring system was established to predict the survival benefits of cancer patients.

Non-invasive diagnosis and surveillance of bladder cancer with driver and passenger DNA methylation in a prospective cohort study

BACKGROUND

State-of-art non-invasive diagnosis processes for bladder cancer (BLCA) harbour shortcomings such as low sensitivity and specificity, unable to distinguish between high- (HG) and low-grade (LG) tumours, as well as inability to differentiate muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). This study investigates a comprehensive characterization of the entire DNA methylation (DNAm) landscape of BLCA to determine the relevant biomarkers for the non-invasive diagnosis of BLCA.

METHODS

A total of 304 samples from 224 donors were enrolled in this multi-centre, prospective cohort study. BLCA-specific DNAm signature discovery was carried out with genome-wide bisulfite sequencing in 32 tumour tissues and 12 normal urine samples. A targeted sequencing assay for BLCA-specific DNAm signatures was developed to categorize tumour tissue against normal urine, or MIBC against NMIBC. Independent validation was performed with targeted sequencing of 259 urine samples in a double-blinded manner to determine the clinical diagnosis and prognosis value of DNAm-based classification models. Functions of genomic region harbouring BLCA-specific DNAm signature were validated with biological assays. Concordances of pathology to urine tumour DNA (circulating tumour DNA [ctDNA]) methylation, genomic mutations or other state-of-the-art diagnosis methods were measured.

RESULTS

Genome-wide DNAm profile could accurately classify LG tumour from HG tumour (LG NMIBC vs. HG NMIBC: p = .038; LG NMIBC vs. HG MIBC, p = .00032; HG NMIBC vs. HG MIBC: p = .82; Student's t-test). Overall, the DNAm profile distinguishes MIBC from NMIBC and normal urine. Targeted-sequencing-based DNAm signature classifiers accurately classify LG NMIBC tissues from HG MIBC and could detect tumours in urine at a limit of detection of less than .5%. In tumour tissues, DNAm accurately classifies pathology, thus outperforming genomic mutation or RNA expression profiles. In the independent validation cohort, pre-surgery urine ctDNA methylation outperforms fluorescence in situ hybridization (FISH) assay to detect HG BLCA (n = 54) with 100% sensitivity (95% CI: 82.5%-100%) and LG BLCA (n = 26) with 62% sensitivity (95% CI: 51.3%-72.7%), both at 100% specificity (non-BLCA: n = 72; 95% CI: 84.1%-100%). Pre-surgery urine ctDNA methylation signature correlates with pathology and predicts recurrence and metastasis. Post-surgery urine ctDNA methylation (n = 61) accurately predicts recurrence-free survival within 180 days, with 100% accuracy.

CONCLUSION

With the discovery of BLCA-specific DNAm signatures, targeted sequencing of ctDNA methylation outperforms FISH and DNA mutation to detect tumours, predict recurrence and make prognoses.

Rapid and ultrasensitive electrochemical detection of DNA methylation for ovarian cancer diagnosis

Alterations in DNA methylation, a stable epigenetic marker, are important components in the development of cancer. It is vital to develop diagnostic systems with the ability to rapidly quantify DNA methylation with high sensitivity and selectivity. However, the analysis of DNA methylation must address two main challenges: (i) ultralow abundance and (ii) differentiating methylated cytosine from normal cytosine on target DNA sequence in the presence of an overwhelming background of circulating cell-free DNA. Here we report the development of an ultrasensitive and highly-selective electrochemical biosensor for the rapid detection of DNA methylation in blood. The sensing of DNA methylation involves the hybridization on a network of probe DNA modified gold-coated magnetic nanoparticles (DNA-Au@MNPs) complementary to target DNA, and subsequently enzymatic cleavage to differentiate methylated DNA strands from corresponding unmethylated DNA strands. The biosensor presents a dynamic range from 2 aM to 20 nM for 110 nucleotide DNA sequences containing a single-site methylation with the lowest detected concentration of 2 aM. This DNA-Au@MNPs based sensor provides a promising method to achieve 35 min response time and minimally invasive diagnosis of ovarian cancer.

Comprehensive Analysis of the Immune Cell Infiltration Landscape and Immune-Related Methylation in Retinoblastoma

Retinoblastoma is a common pediatric intraocular cancer, originating from cone precursors. The development of immunotherapies can help eradicate the tumor without vision loss, which would largely improve the quality of life of patients with retinoblastoma. Investigation of the tumor immune microenvironment provides knowledge for developing novel immunotherapies in cancer. However, the immune cell infiltrative landscape of retinoblastoma is unknown. Here, we compared the relative expression of immune gene signatures among 59 patients with retinoblastoma. The patients were divided into two subgroups according to the 28 types of immune cell infiltration (ICI) scores. We found that a subgroup with high ICI scores had increased expression levels of late cone markers, while the other subgroup exhibited larger tumor size and metastasis propensity. Furthermore, hypermethylated genes in the high-ICI subgroup were associated with immune regulation in the tumor microenvironment, suggesting that DNA methylation may play a vital regulatory role in retinoblastoma immunity. Our study provides a comprehensive framework for the systemic analysis of the influences of epigenetic events on the tumor immune microenvironment. We anticipate that our assay can not only provide insights into tumor immune regulation but also open up the perspectives for the identification of novel immunotherapy targets for retinoblastoma.

Magnetic Immunosensor Coupled to Enzymatic Signal for Determination of Genomic DNA Methylation

Aberrations of genomic DNA methylation have been confirmed to be involved in the evolution of human cancer and have thus gained the potential to be depicted as biomarkers for cancer diagnostics and prognostic predictions, which implicates an urgent need for detection of total genomic DNA methylation. In this work, we suggested an assay for the quantification of global DNA methylation, utilizing methylation specific antibody (5mC) modified magnetic beads (MBs) for immunorecognition and affinity enrichment. Subsequently, the captured DNA on the surface of MBs interacted with the glucose oxidase-conjugated DNA antibody whose catalytic reaction product was engaged in electrochemical detection of the overall level of DNA methylation on a PB-doped screen-printed electrode. With 15 pg of input DNA, which, to our best knowledge, is the lowest required amount of DNA without sodium bisulfite treatment or amplification, this test strategy was able to perceive as low as 5% methylation level within 70 min including the preparation of anti-5mC-MBs. We believe this detection technique offers a promising option to detect global DNA methylation in both academic and clinical scenarios.

Opportunities for Early Cancer Detection: The Rise of ctDNA Methylation-Based Pan-Cancer Screening Technologies

The efficiency of conventional screening programs to identify early-stage malignancies can be limited by the low number of cancers recommended for screening as well as the high cumulative false-positive rate, and associated iatrogenic burden, resulting from repeated multimodal testing. The opportunity to use minimally invasive liquid biopsy testing to screen asymptomatic individuals at-risk for multiple cancers simultaneously could benefit from the aggregated diseases prevalence and a fixed specificity. Increasing both latter parameters is paramount to mediate high positive predictive value—a useful metric to evaluate a screening test accuracy and its potential harm-benefit. Thus, the use of a single test for multi-cancer early detection (stMCED) has emerged as an appealing strategy for increasing early cancer detection rate efficiency and benefit population health. A recent flurry of these stMCED technologies have been reported for clinical potential; however, their development is facing unique challenges to effectively improve clinical cost–benefit. One promising avenue is the analysis of circulating tumour DNA (ctDNA) for detecting DNA methylation biomarker fingerprints of malignancies—a hallmark of disease aetiology and progression holding the potential to be tissue- and cancer-type specific. Utilizing panels of epigenetic biomarkers could potentially help to detect earlier stages of malignancies as well as identify a tumour of origin from blood testing, useful information for follow-up clinical decision making and subsequent patient care improvement. Overall, this review collates the latest and most promising stMCED methodologies, summarizes their clinical performances, and discusses the specific requirements multi-cancer tests should meet to be successfully implemented into screening guidelines.

Epigenetic Mechanisms as Emerging Therapeutic Targets and Microfluidic Chips Application in Pulmonary Arterial Hypertension

Pulmonary arterial hypertension (PAH) is a disease that progress over time and is defined as an increase in pulmonary arterial pressure and pulmonary vascular resistance that frequently leads to right-ventricular (RV) failure and death. Epigenetic modifications comprising DNA methylation, histone remodeling, and noncoding RNAs (ncRNAs) have been established to govern chromatin structure and transcriptional responses in various cell types during disease development. However, dysregulation of these epigenetic mechanisms has not yet been explored in detail in the pathology of pulmonary arterial hypertension and its progression with vascular remodeling and right-heart failure (RHF). Targeting epigenetic regulators including histone methylation, acetylation, or miRNAs offers many possible candidates for drug discovery and will no doubt be a tempting area to explore for PAH therapies. This review focuses on studies in epigenetic mechanisms including the writers, the readers, and the erasers of epigenetic marks and targeting epigenetic regulators or modifiers for treatment of PAH and its complications described as RHF. Data analyses from experimental cell models and animal induced PAH models have demonstrated that significant changes in the expression levels of multiple epigenetics modifiers such as HDMs, HDACs, sirtuins (Sirt1 and Sirt3), and BRD4 correlate strongly with proliferation, apoptosis, inflammation, and fibrosis linked to the pathological vascular remodeling during PAH development. The reversible characteristics of protein methylation and acetylation can be applied for exploring small-molecule modulators such as valproic acid (HDAC inhibitor) or resveratrol (Sirt1 activator) in different preclinical models for treatment of diseases including PAH and RHF. This review also presents to the readers the application of microfluidic devices to study sex differences in PAH pathophysiology, as well as for epigenetic analysis.

Dual-modality loop-mediated isothermal amplification for pretreatment-free detection of Septin9 methylated DNA in colorectal cancer

Currently, the determination of DNA methylation is still a challenge due to the limited efficiency of enrichment, bisulfite modification, and detection. In this study, a dual-modality loop-mediated isothermal amplification integrated with magnetic bead isolation is  proposed for the determination of methylated Septin9 gene in colorectal cancer. Magnetic beads modified with anti-methyl cytosine antibody were prepared for fast enrichment of methylated DNA through specific immunoaffinity (30 min). One-pot real-time fluorescence and colorimetric loop-mediated isothermal amplification were simultaneously developed for detecting methylated Septin9 gene (60 min). The real-time fluorescence generating by SYTO-9 dye (excitation: 470 nm and emission: 525 nm) and pH indicator (neutral red) was used for quantitative and visualized detection of methylated DNA. This method was demonstrated to detect methylated DNA from HCT 116 cells ranging from 2 to 0.02 ng/μL with a limit of detection of 0.02 ± 0.002 ng/μL (RSD: 9.75%). This method also could discriminate methylated Septin9 in 0.1% HCT 116 cells (RSD: 6.60%), suggesting its high specificity and sensitivity. The feasibility of this assay was further evaluated by clinical plasma samples from 20 colorectal cancer patients and 20 healthy controls, which shows the potential application in simple, low cost, quantitative, and visualized detection of methylated nucleic acids.

Detection of Cell Types Contributing to Cancer From Circulating, Cell-Free Methylated DNA

Detection of cellular changes in tissue biopsies has been the basis for cancer diagnostics. However, tissue biopsies are invasive and limited by inaccuracies due to sampling locations, restricted sampling frequency, and poor representation of tissue heterogeneity. Liquid biopsies are emerging as a complementary approach to traditional tissue biopsies to detect dynamic changes in specific cell populations. Cell-free DNA (cfDNA) fragments released into the circulation from dying cells can be traced back to the tissues and cell types they originated from using DNA methylation, an epigenetic regulatory mechanism that is highly cell-type specific. Decoding changes in the cellular origins of cfDNA over time can reveal altered host tissue homeostasis due to local cancer invasion and metastatic spread to distant organs as well as treatment responses. In addition to host-derived cfDNA, changes in cancer cells can be detected from cell-free, circulating tumor DNA (ctDNA) by monitoring DNA mutations carried by cancer cells. Here, we will discuss computational approaches to identify and validate robust biomarkers of changed tissue homeostasis using cell-free, methylated DNA in the circulation. We highlight studies performing genome-wide profiling of cfDNA methylation and those that combine genetic and epigenetic markers to further identify cell-type specific signatures. Finally, we discuss opportunities and current limitations of these approaches for implementation in clinical oncology.

Identification and Validation of Immune-Related Methylation Clusters for Predicting Immune Activity and Prognosis in Breast Cancer

The role of DNA methylation of breast cancer-infiltrating immune cells has not been fully explored. We conducted a cohort-based retrospective study analyzing the genome-wide immune-related DNA methylation of 1057 breast cancer patients from the TCGA cohort and GSE72308 cohort. Based on patients' overall survival (OS), a prognostic risk score system using 18 immune-related methylation genes (IRMGs) was established and further validated in an independent cohort. Kaplan-Meier analysis showed a clear separation of OS between the low- and high-risk groups. Patients in the low-risk group had a higher immune score and stromal score compared with the high-risk group. Moreover, the characteristics based on 18-IRMGs signature were related to the tumor immune microenvironment and affected the abundance of tumor-infiltrating immune cells. Consistently, the 18-IRMGs signatures showed similar influences on immune modulation and survival in another external validation cohort (GSE72308). In conclusion, the proposed 18-IRMGs signature could be a potential marker for breast cancer prognostication.

Prognostic biomarker identification and tumor classification in breast cancer patients by methylation and transcriptome analysis

Breast cancer is one of the most common and heterogeneous malignancies. Although the prognosis of breast cancer has improved with the development of early screening, the mechanisms underlying tumorigenesis and progression remain incompletely understood. DNA methylation has been implicated in tumorigenesis and tumor development and, in the present study. we screened methylation-driven genes and explored their prognostic values in breast cancer. RNA-sequencing (RNA-Seq) transcriptome data and DNA methylation data of the TCGA-BRCA dataset were obtained from The Cancer Genome Atlas. Differentially expressed genes and differentially methylated genes were identified separately. The intersected 783 samples with both RNA-Seq data and DNA methylation data were selected for further analysis. Fifty-six methylation-driven genes were identified using the MethylMix r package and 10 prognosis methylation-driven genes (CDO1, CELF2, ITPAIPL1, KCNH8, PTK6, RAB25, RIC3, USP44, ZSCAN1 and ZSCAN23) were further screened by combined methylation and gene expression analysis. Based on the methylation data of the screened 10 methylation-driven genes, six subgroups were identified with the ConsensusClusterPlus r package. The protein levels of the 10 prognostic methylation-driven genes were detected by immunohistochemical experiments. Moreover, based on the RNA-Seq data, a signature calculating the risk score of each patient was developed with stepwise regression. The risk score and other clinical features (age and stage) were confirmed to be independent prognostic factors by univariate and multivariate Cox regression analyses. Finally, a prognostic nomogram incorporating all the significant factors was integrated to predict the 3-, 5- and 7-year overall survival. Taken together, the methylation-driven genes identified here may be potential biomarkers of breast cancer.

Hypomethylation of GDNF family receptor alpha 1 promotes epithelial-mesenchymal transition and predicts metastasis of colorectal cancer

Tumor metastasis is the major cause of poor prognosis and mortality in colorectal cancer (CRC). However, early diagnosis of highly metastatic CRC is currently difficult. In the present study, we screened for a novel biomarker, GDNF family receptor alpha 1 (GFRA1) based on the expression and methylation data in CRC patients from The Cancer Genome Altlas (TCGA), followed by further analysis of the correlation between the GFRA1 expression, methylation, and prognosis of patients. Our results show DNA hypomethylation-mediated upregulation of GFRA1 in invasive CRC, and it was found to be correlated with poor prognosis of CRC patients. Furthermore, GFRA1 methylation-modified sequences were found to have potential as methylation diagnostic markers of highly metastatic CRC. The targeted demethylation of GFRA1 by dCas9-TET1CD and gRNA promoted CRC metastasis in vivo and in vitro. Mechanistically, demethylation of GFRA1 induces epithelial-mesenchymal transition (EMT) by promoting AKT phosphorylation and increasing c-Jun expression in CRC cells. Collectively, our findings indicate that GFRA1 hypomethylation can promote CRC invasion via inducing EMT, and thus, GFRA1 methylation can be used as a biomarker for the early diagnosis of highly metastasis CRC.

Abnormal DNA methylation, one of important characteristics in tumor cells, is exploited as biomarkers for cancer diagnosis and prognosis prediction. Early diagnosis of highly metastatic CRC will be helpful for the clinical management, thus prolongs patient survival. However, it is currently difficult to make early diagnosis of highly metastatic CRC in clinical practice. Currently, we screened a novel biomarker gene, GFRA1, which associated with the invasion and poor prognosis of CRC. The targeted demethylation of GFRA1 exerted a significant promoting effect on CRC metastasis, and GFRA1 methylation-modified sequences are valuable diagnostic biomarker for CRC metastasis risk assessment. Mechanically, demethylation of GFRA1 induced epithelial-mesenchymal transition (EMT) by upregulating AKT phosphorylation and c-Jun expression in CRC cells. Our results demonstrate the promoting effect of GFRA1 demethylation on CRC invasion and GFRA1 methylation may be a potential prognostic marker for predicting metastasis of CRC.

MBD2 Correlates with a Poor Prognosis and Tumor Progression in Renal Cell Carcinoma

Purpose

DNA methylation plays an important role in regulating gene expression. Methyl-CpG-binding domain (MBD) proteins recognize and bind to methylated DNA, which mediate gene silencing by the interaction with deacetylases and histone methyltransferases. MBD2 has been reported in various human cancers; however, its clinical implication and potential regulatory role in renal cell carcinoma (RCC) have not been elaborated.

Materials and Methods

In the study, we estimated the expression and prognostic value of MBD2 in RCC cell lines and tissues by Western blotting and immunohistochemistry. The associations of MBD2 expression and pathological characters and survival in RCC patients were performed using χ2 and Kaplan-Meier survival analysis, respectively. Univariate and multivariable Cox regression analyses suggested the independent predictors in RCC prognosis. The functional role of MBD2 in RCC progression was assessed by in vitro cell experiments. In addition, we identified the MBD2-mediated alterations of protein-related proliferation and EMT markers in RCC cells after MBD2 overexpression and knockdown.

Results

We found that the protein levels of MBD2 were upregulated in RCC cells and tissues. High MBD2 expression was related to TNM stage and predicted poorer survival in RCC. Enforced expression of MBD2 significantly promoted the proliferation, cycle progress, invasion and migration of RCC cells in vitro. However, downregulating MBD2 remarkably weakened the above cell functions. Mechanistically, the promotive effect of MBD2 overexpression may be regulated by its effects onp21, p53 and Cyclin D1 expression and EMT process.

Conclusion

These results indicated that MBD2confers an oncogenic function in the malignant progression of RCC. MBD2 could be served as a meaningful prognostic biomarker and a latent therapeutic target in RCC patients.

Circulating tumor cells as Trojan Horse for understanding, preventing, and treating cancer: a critical appraisal

Circulating tumor cells (CTCs) are regarded as harbingers of metastases. Their ability to predict response to therapy, relapse, and resistance to treatment has proposed their value as putative diagnostic and prognostic indicators. CTCs represent one of the zeniths of cancer evolution in terms of cell survival; however, the triggers of CTC generation, the identification of potentially metastatic CTCs, and the mechanisms contributing to their heterogeneity and aggressiveness represent issues not yet fully deciphered. Thus, prior to enabling liquid biopsy applications to reach clinical prime time, understanding how the above mechanistic information can be applied to improve treatment decisions is a key challenge. Here, we provide our perspective on how CTCs can provide mechanistic insights into tumor pathogenesis, as well as on CTC clinical value. In doing so, we aim to (a) describe how CTCs disseminate from the primary tumor, and their link to epithelial-mesenchymal transition (EMT); (b) trace the route of CTCs through the circulation, focusing on tumor self-seeding and the possibility of tertiary metastasis; (c) describe possible mechanisms underlying the enhanced metastatic potential of CTCs; (d) discuss how CTC could provide further information on the tissue of origin, especially in cancer of unknown primary origin. We also provide a comprehensive review of meta-analyses assessing the prognostic significance of CTCs, to highlight the emerging role of CTCs in clinical oncology. We also explore how cell-free circulating tumor DNA (ctDNA) analysis, using a combination of genomic and phylogenetic analysis, can offer insights into CTC biology, including our understanding of CTC heterogeneity and tumor evolution. Last, we discuss emerging technologies, such as high-throughput quantitative imaging, radiogenomics, machine learning approaches, and the emerging breath biopsy. These technologies could compliment CTC and ctDNA analyses, and they collectively represent major future steps in cancer detection, monitoring, and management.

SERS-Based Assessment of MRD in Acute Promyelocytic Leukemia?

Acute promyelocytic leukemia (APL) is characterized by a unique chromosome translocation t(15;17)(q24;q21), which leads to the PML/RARA gene fusion formation. However, it is acknowledged that this rearrangement alone is not able to induce the whole leukemic phenotype. In addition, epigenetic processes, such as DNA methylation, may play a crucial role in leukemia pathogenesis. DNA methylation, catalyzed by DNA methyltransferases (DNMTs), involves the covalent transfer of a methyl group (-CH3) to the fifth carbon of the cytosine ring in the CpG dinucleotide and results in the formation of 5-methylcytosine (5-mC). The aberrant gene promoter methylation can be an alternative mechanism of tumor suppressor gene inactivation. Understanding cancer epigenetics and its pivotal role in oncogenesis, can offer us not only attractive targets for epigenetic treatment but can also provide powerful tools in monitoring the disease and estimating the prognosis. Several genes of interest, such as RARA, RARB, p15, p16, have been studied in APL and their methylation status was correlated with potential diagnostic and prognostic significance. In the present manuscript we comprehensively examine the current knowledge regarding DNA methylation in APL pathogenesis. We also discuss the perspectives of using the DNA methylation patterns as reliable biomarkers for measurable residual disease (MRD) monitoring and as a predictor of relapse. This work also highlights the possibility of detecting aberrant methylation profiles of circulating tumor DNA (ctDNA) through liquid biopsies, using the conventional methods, such as methylation-specific polymerase chain reaction (MS-PCR), sequencing methods, but also revolutionary methods, such as surface-enhanced Raman spectroscopy (SERS).

CpG methylation signature defines human temporal lobe epilepsy and predicts drug-resistant

Aims

Temporal lobe epilepsy (TLE) is the most common focal epilepsy syndrome in adults and frequently develops drug resistance. Studies have investigated the value of peripheral DNA methylation signature as molecular biomarker for diagnosis or prognosis. We aimed to explore methylation biomarkers for TLE diagnosis and pharmacoresistance prediction.

Methods

We initially conducted genome‐wide DNA methylation profiling in TLE patients, and then selected candidate CpGs in training cohort and validated in another independent cohort by employing machine learning algorithms. Furthermore, nomogram comprising DNA methylation and clinicopathological data was generated to predict the drug response in the entire patient cohort. Lastly, bioinformatics analysis for CpG‐associated genes was performed using Ingenuity Pathway Analysis.

Results

After screening and validation, eight CpGs were identified for diagnostic biomarker with an area under the curve (AUC) of 0.81 and six CpGs for drug‐resistant prediction biomarker with an AUC of 0.79. The nomogram for drug‐resistant prediction comprised methylation risk score, disease course, seizure frequency, and hippocampal sclerosis, with AUC as high as 0.96. Bioinformatics analysis indicated drug response–related CpGs corresponding genes closely related to DNA methylation.

Conclusions

This study demonstrates the ability to use peripheral DNA methylation signature as molecular biomarker for epilepsy diagnosis and drug‐resistant prediction.

CHG: A Systematically Integrated Database of Cancer Hallmark Genes

Background

The analysis of cancer diversity based on a logical framework of hallmarks has greatly improved our understanding of the occurrence, development and metastasis of various cancers.

Methods

We designed Cancer Hallmark Genes (CHG) database which focuses on integrating hallmark genes in a systematic, standard way and annotates the potential roles of the hallmark genes in cancer processes. Following the conceptual criteria description of hallmark function the keywords for each hallmark were manually selected from the literature. Candidate hallmark genes collected were derived from 301 pathways of KEGG database by Lucene and manually corrected.

Results

Based on the variation data, we finally identified the hallmark genes of various types of cancer and constructed CHG. And we also analyzed the relationships among hallmarks and potential characteristics and relationships of hallmark genes based on the topological structures of their networks. We manually confirm the hallmark gene identified by CHG based on literature and database. We also predicted the prognosis of breast cancer, glioblastoma multiforme and kidney papillary cell carcinoma patients based on CHG data.

Conclusions

In summary, CHG, which was constructed based on a hallmark feature set, provides a new perspective for analyzing the diversity and development of cancers.

Electrochemical biosensing to move forward in cancer epigenetics and metastasis: A review

Early detection and effective treatment are crucial to reduce the physical, emotional, and financial pressure exerted by growing cancer burden on individuals, families, communities, and health systems. Currently, it is clear that the accurate analysis of emerging cancer epigenetic and metastatic-related biomarkers at different molecular levels is envisaged as an exceptional solution for early and reliable diagnosis and the improvement of therapy efficiency through personalized treatments. Within this field, electrochemical biosensing has demonstrated to be competitive over other emerging and currently used methodologies for the determination of these biomarkers accomplishing the premises of user-friendly, multiplexing ability, simplicity, reduced costs and decentralized analysis, demanded by clinical oncology, thus priming electrochemical biosensors to spark a diagnostic revolution for cancer prediction and eradication. This review article critically discusses the main characteristics, opportunities and versatility exhibited by electrochemical biosensing, through highlighting representative examples published during the last two years, for the reliable determination of these emerging biomarkers, with great diagnostic, predictive and prognostic potential. Special attention is paid on electrochemical affinity biosensors developed for the single or multiplexed determination of methylation events, non-coding RNAs, ctDNA features and metastasis-related protein biomarkers both in liquid and solid biopsies of cancer patients. The main challenges to which further work must be addressed and the impact of these advances should have in the clinical acceptance of these emerging biomarkers are also discussed which decisively will contribute to understand the molecular basis involved in the epigenetics and metastasis of cancer and to apply more efficient personalized therapies.