DNA Methylation Biomarkers Research Articles

Candidate Epigenetic Biomarker of Cognitive Trajectory: The Chicken or the Egg?

Brain health throughout the life course depends upon both genetic and epigenetic features. The most widely studied epigenetic mark in the brain has been DNA methylation owing to its stability and convenience to assay from widely available DNA biospecimens. Evidence suggests that distinct DNA methylation patterns serve as a wide-ranging biomarker including but not limited to disease status, disease risk, predictor of life expectancy and mortality, aging, and prior environmental exposures. Emerging research is suggesting the utility of DNA methylation biomarkers in neuroimaging and neurocognition epigenetics.

Integrative Multi-Omics Analysis Reveals Candidate Biomarkers for Oral Squamous Cell Carcinoma.

Oral squamous cell carcinoma (OSCC) is one of the most common types of cancer worldwide. Due to the lack of early detection and treatment, the survival rate of OSCC remains poor and the incidence of OSCC has not decreased during the past decades. To explore potential biomarkers and therapeutic targets for OSCC, we analyzed differentially expressed genes (DEGs) associated with OSCC using RNA sequencing technology. Methylation−regulated and differentially expressed genes (MeDEGs) of OSCC were further identified via an integrative approach by examining publicly available methylomic datasets together with our transcriptomic data. Protein−protein interaction (PPI) networks of MeDEGs were constructed and highly connected hub MeDEGs were identified from these PPI networks. Subsequently, expression and survival analyses of hub genes were performed using The Cancer Genome Atlas (TCGA) database and the Gene Expression Profiling Interactive Analysis (GEPIA) online tool. A total of 56 upregulated MeDEGs and 170 downregulated MeDEGs were identified in OSCC. Eleven hub genes with high degree of connectivity were picked out from the PPI networks constructed by those MeDEGs. Among them, the expression level of four hub genes (CTLA4, CDSN, ACTN2, and MYH11) were found to be significantly changed in the head and neck squamous carcinoma (HNSC) patients. Three hypomethylated hub genes (CTLA4, GPR29, and TNFSF11) and one hypermethylated hub gene (ISL1) were found to be significantly associated with overall survival (OS) of HNSC patients. Therefore, these hub genes may serve as potential DNA methylation biomarkers and therapeutic targets of OSCC.

DunedinPACE, a DNA methylation biomarker of the pace of aging.

Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously, we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al., 2020). Here, we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome). We used data from the Dunedin Study 1972-1973 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets. DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge. DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience. This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.

Prognostic Significance of SLFN11 Methylation in Plasma Cell-Free DNA in Advanced High-Grade Serous Ovarian Cancer.

Simple SummaryIn the present study, we examined the methylation status of six gene promoters (BRCA1, CST6, MGMT, RASSF10, SLFN11 and USP44) in high-grade serous ovarian cancer (HGSOC). We evaluated the prognostic significance of DNA methylation of these six gene promoters in primary tumors (FFPEs) and plasma cfDNA samples from patients with early, advanced and metastatic HGSOC. We report for the first time that the DNA methylation of SLFN11 in plasma cfDNA was significantly correlated with worse PFS (p = 0.045) in advanced stage HGSOC. Our results strongly indicate that SLFN11 epigenetic inactivation could serve as a potential prognostic DNA methylation biomarker and a predictor of resistance to platinum-based chemotherapy in ovarian cancer.Background: Epigenetic alterations in ctDNA are highly promising as a source of novel potential liquid biopsy biomarkers and comprise a very promising liquid biopsy approach in ovarian cancer, for early diagnosis, prognosis and response to treatment. Methods: In the present study, we examined the methylation status of six gene promoters (BRCA1, CST6, MGMT, RASSF10, SLFN11 and USP44) in high-grade serous ovarian cancer (HGSOC). We evaluated the prognostic significance of DNA methylation of these six gene promoters in primary tumors (FFPEs) and plasma cfDNA samples from patients with early, advanced and metastatic HGSOC. Results: We report for the first time that the DNA methylation of SLFN11 in plasma cfDNA was significantly correlated with worse PFS (p = 0.045) in advanced stage HGSOC. Conclusions: Our results strongly indicate that SLFN11 epigenetic inactivation could be a predictor of resistance to platinum drugs in ovarian cancer. Our results should be further validated in studies based on a larger cohort of patients, in order to further explore whether the DNA methylation of SLFN11 promoter could serve as a potential prognostic DNA methylation biomarker and a predictor of resistance to platinum-based chemotherapy in ovarian cancer.

Prenatal lead exposure, telomere length in cord blood, and DNA methylation age in the PROGRESS prenatal cohort

BackgroundLead is a ubiquitous pollutant with deleterious effects on human health and remains a major current public health concern in developing countries. This heavy metal may interfere with nucleic acids via oxidative stress or epigenetic changes that affect biological markers of aging, e.g., telomere length and DNA methylation (DNAm). Telomere shortening associates with biological age in newborns, and DNA methylation at specific CpG sites can be used to calculate “epigenetic clocks". ObjectiveThe aim of this study was to examine the associations of prenatal lead exposures with telomere length and DNA-methylation-based predictors of age in cord blood. DesignThe study included 507 mother–child pairs from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study, a birth cohort in Mexico City. Maternal blood (second trimester, third trimester and at delivery) and bone lead levels (one month postpartum) were measured using inductively coupled plasma-mass spectrometry and X-ray fluorescence, respectively. Cord blood leukocyte telomere length was measured using quantitative PCR and apparent age by DNA methylation biomarkers, i.e., Horvath's DNA methylation age and the Knight's predictor of gestational age. ResultsAverage maternal age was 28.5 ± 5.5 years, and 51.5% reported low socioeconomic status. Children's mean telomere length was 1.2 ± 1.3 relative units, and mean DNA methylation ages using the Horvath's and Knight's clocks were −2.6 ± 0.1 years and 37.9 ± 1.4 weeks (mean ± SD), respectively. No significant associations were found between maternal blood and bone lead concentrations with telomere length and DNAm age in newborns. ConclusionWe found no associations of prenatal lead exposure with telomere length and DNA methylation age biomarkers.

Opting for Local Region in SHOX2 Promoter as a DNA Methylation Biomarker for Lung Cancer Diagnosis

Epigenetic alterations play a main role in the initiation and progression of lung cancer. CpG methylation in the promoter of the Short Stature Homeobox 2 (SHOX2) gene has been evaluated and validated at different stages of this malignant disease. Several approaches for measuring DNA methylation have been established, including quantitative methylation-specific PCR (qMSP). This is a simple, fast, and cost-effective technique that can be easily applied to clinical practice. In this study, formalin-fixed, paraffin-embedded (FFPE) tissue samples were collected from 30 lung cancer patients and 30 patients suffering from non-cancerous pulmonary diseases. The methylation level of SHOX2 was evaluated in two CpG-riched regions by using qMSP and one of them could be conferred as a potential biomarker to lung cancer.

Early and accurate detection of cholangiocarcinoma in patients with primary sclerosing cholangitis by methylation markers in bile.

Background and AimsPrimary sclerosing cholangitis (PSC) is associated with increased risk of cholangiocarcinoma (CCA). Early and accurate CCA detection represents an unmet clinical need as the majority of patients with PSC are diagnosed at an advanced stage of malignancy. In the present study, we aimed at establishing robust DNA methylation biomarkers in bile for early and accurate diagnosis of CCA in PSC.Approach and ResultsDroplet digital PCR (ddPCR) was used to analyze 344 bile samples from 273 patients with sporadic and PSC‐associated CCA, PSC, and other nonmalignant liver diseases for promoter methylation of cysteine dioxygenase type 1, cannabinoid receptor interacting protein 1, septin 9, and vimentin. Receiver operating characteristic (ROC) curve analyses revealed high AUCs for all four markers (0.77–0.87) for CCA detection among patients with PSC. Including only samples from patients with PSC diagnosed with CCA ≤ 12 months following bile collection increased the accuracy for cancer detection, with a combined sensitivity of 100% (28/28) and a specificity of 90% (20/203). The specificity increased to 93% when only including patients with PSC with longtime follow‐up (> 36 months) as controls, and remained high (83%) when only including patients with PSC and dysplasia as controls (n = 23). Importantly, the bile samples from the CCA‐PSC ≤ 12 patients, all positive for the biomarkers, included both early‐stage and late‐stage CCA, different tumor growth patterns, anatomical locations, and carbohydrate antigen 19‐9 levels.ConclusionsUsing highly sensitive ddPCR to analyze robust epigenetic biomarkers, CCA in PSC was accurately detected in bile, irrespective of clinical and molecular features, up to 12 months before CCA diagnosis. The findings suggest a potential for these biomarkers to complement current detection and screening methods for CCA in patients with PSC.

Epigenome-Wide Association Study of Prostate Cancer in African Americans Identifies DNA Methylation Biomarkers for Aggressive Disease.

DNA methylation plays important roles in prostate cancer (PCa) development and progression. African American men have higher incidence and mortality rates of PCa than other racial groups in U.S. The goal of this study was to identify differentially methylated CpG sites and genes between clinically defined aggressive and nonaggressive PCa in African Americans. We performed genome-wide DNA methylation profiling in leukocyte DNA from 280 African American PCa patients using Illumina MethylationEPIC array that contains about 860K CpG sties. There was a slight increase of overall methylation level (mean β value) with the increasing Gleason scores (GS = 6, GS = 7, GS ≥ 8, P for trend = 0.002). There were 78 differentially methylated CpG sites with P < 10−4 and 9 sites with P < 10−5 in the trend test. We also found 77 differentially methylated regions/genes (DMRs), including 10 homeobox genes and six zinc finger protein genes. A gene ontology (GO) molecular pathway enrichment analysis of these 77 DMRs found that the main enriched pathway was DNA-binding transcriptional factor activity. A few representative DMRs include HOXD8, SOX11, ZNF-471, and ZNF-577. Our study suggests that leukocyte DNA methylation may be valuable biomarkers for aggressive PCa and the identified differentially methylated genes provide biological insights into the modulation of immune response by aggressive PCa.

Identification of DNA methylation biomarkers with potential to predict response to neoadjuvant chemotherapy in triple-negative breast cancer

Neoadjuvant chemotherapy (NAC) is used to treat triple-negative breast cancer (TNBC) prior to resection. Biomarkers that accurately predict a patient’s response to NAC are needed to individualise therapy and avoid chemotoxicity from unnecessary chemotherapy. We performed whole-genome DNA methylation profiling on diagnostic TNBC biopsy samples from the Sequential Evaluation of Tumours Undergoing Preoperative (SETUP) NAC study. We found 9 significantly differentially methylated regions (DMRs) at diagnosis which were associated with response to NAC. We show that 4 of these DMRs are associated with TNBC overall survival (P < 0.05). Our results highlight the potential of DNA methylation biomarkers for predicting NAC response in TNBC.

Epigenome association study for DNA methylation biomarkers in buccal and monocyte cells for female rheumatoid arthritis

Genetics (i.e., mutations) has been assumed to be the major factor in rheumatoid arthritis (RA) etiology, but accounts for a minority of the variance in disease risk for RA. In contrast to genetics, the environment can have dramatic impacts on epigenetics that associate with disease etiology. The current study used buccal cells and purified blood monocytes from two different clinical cohorts involving Caucasian or African American female populations with or without arthritis. The differential DNA methylation regions (DMRs) between the control and RA populations were identified with an epigenome-wide association study. The DMRs (i.e., epimutations) identified in the buccal cells and monocytes were found to be distinct. The DMR associated genes were identified and many have previously been shown to be associated with arthritis. Observations demonstrate DNA methylation epimutation RA biomarkers are cell type specific and similar findings were observed with the two racial background populations. Rheumatoid arthritis susceptibility epigenetic diagnosis appears feasible and may improve the clinical management of RA and allowpreventative medicine considerations.

DNA Hypermethylation af a Panel Of Genes as an Urinary Biomarker For Bladder Cancer Diagnosis.

Several studies have shown frequent changes in DNA methylation in bladder cancer (BCa), which vary among different geographical areas. The aim of this study is to examine the diagnostic accuracy of a panel of DNA methylation biomarkers in a Greek clinical setting contributing to the development of a universal panel of urine biomarkers. Individuals with primary BCa and control individuals matching the gender, age and smoking status of the cancer patients were recruited. DNA methylation was assessed for the gene promoters of RASSF1, RARB, DAPK, TERT and APC in urine samples collected by spontaneous urination using quantitative Methylation Specific PCR (qMSP). All genes had been previously separately associated with BCa. Fifty patients and 35 healthy controls were recruited, with average age of 70.26 years and average smoking status of 44.78 pack-years. In the BCa group, DNA methylation was detected in 27 (61.4%) samples. RASSF1 was methylated in 52.2% of samples. Only 3 (13.6%) samples from the control group were methylated, all in the RASSF1 gene promoter. The specificity and sensitivity of this panel of genes to diagnose BCa was 86% and 61% respectively. The RASSF1 gene could diagnose BCa with specificity 86.4% and sensitivity 52.3%. Promoter DNA methylation of this panel of five genes could be further investigated as urine biomarker for the diagnosis of BCa. The RASSF1 could be a single candidate biomarker for predicting BCa patients versus controls. Studies are required in order to develop a geographically adjusted diagnostic biomarker for BCa.

Deciphering a TB-related DNA methylation biomarker and constructing a TB diagnostic classifier

We systemically identified tuberculosis (TB)-related DNA methylation biomarkers and further constructed classifiers for TB diagnosis. TB-related DNA methylation datasets were searched through October 3, 2020. Limma and DMRcate were employed to identify differentially methylated probes (DMPs) and regions (DMRs). Machine learning methods were used to construct classifiers. The performance of the classifiers was evaluated in discovery datasets and a prospective independent cohort. Eighty-nine DMPs and 24 DMRs were identified based on 67 TB patients and 45 healthy controls from 4 datasets. Nine and three DMRs were selected by elastic net regression and logistic regression, respectively. Among the selected DMRs, two regions (chr3: 195635643–195636243 and chr6: 29691631–29692475) were differentially methylated in the independent cohort (p = 4.19 × 10−5 and 0.024, respectively). Among the ten classifiers, the 3-DMR logistic regression classifier exhibited the strongest performance. The sensitivity, specificity, and area under the curve were, respectively, 79.1%, 84.4%, and 0.888 in the discovery datasets and 64.5%, 90.3%, and 0.838 in the independent cohort. The differential diagnostic ability of this classifier was also assessed. Collectively, these data showed that DNA methylation might be a promising TB diagnostic biomarker. The 3-DMR logistic regression classifier is a potential clinical tool for TB diagnosis, and further validation is needed.

DNA Methylation Abnormalities and Altered Whole Transcriptome Profiles after Switching from Combustible Tobacco Smoking to Heated Tobacco Products.

The use of heated tobacco products (HTP) has increased exponentially in Japan since 2016; however, their effects on health remain a major concern. Tsuruoka Metabolome Cohort Study participants (n = 11,002) were grouped on the basis of their smoking habits as never smokers (NS), past smokers (PS), combustible tobacco smokers (CS), and HTP users for <2 years. Peripheral blood mononuclear cells were collected from 52 participants per group matched to HTP users using propensity scores, and DNA and RNA were purified from the samples. DNA methylation (DNAm) analysis of the 17 smoking-associated DNAm biomarker genes (such as AHRR, F2RL3, LRRN3, and GPR15), as well as whole transcriptome analysis, was performed. Ten of the 17 genes were significantly hypomethylated in CS and HTP users compared with NS, among which AHRR, F2RL3, and RARA showed intermediate characteristics between CS and NS; nonetheless, AHRR expression was significantly higher in CS than in the other three groups. Conversely, LRRN3 and GPR15 were more hypomethylated in HTP users than in NS, and GPR15 expression was markedly upregulated in all the groups when compared with that in NS. HTP users (switched from CS <2 years) display abnormal DNAm and transcriptome profiles, albeit to a lesser extent than the CS. However, because the molecular genetic effects of long-term HTP use are still unknown, long-term molecular epidemiologic studies are needed. This study provides new insights into the molecular genetic effects on DNAm and transcriptome profiles in HTP users who switched from CS.

Potential evidence for epigenetic biomarkers of metabolic syndrome in human whole blood in Latinos.

Metabolic syndrome (MetS) is highly prevalent worldwide. In the United States, estimates show that more than 30% of the adult population has MetS. MetS consists of multiple phenotypes, including obesity, dyslipidemia, and impaired glucose tolerance. Therefore, identifying the molecular mechanisms to explain this complex disease is critical for diagnosing and treating MetS. We previously showed 70 increased genes and 20 decreased genes in whole blood in MetS participants. The present study aimed to identify blood-based DNA methylation biomarkers in non-MetS versus MetS participants. The present study analyzed whole blood DNA samples from 184 adult participants of Latino descent from the Arizona Insulin Resistance (AIR) registry. We used the National Cholesterol Education Program Adult Treatment Panel III (NCEP: ATP III) criteria to identify non-MetS (n = 110) and MetS (n = 74) participants. We performed whole blood methylation analysis on select genes: ATP Synthase, H+ Transporting mitochondrial F1 Complex, Epsilon Subunit (ATP5E), Cytochrome C Oxidase Subunit VIc (COX6C), and Ribosomal Protein L9 (RPL9). The pyrosequencing analysis was a targeted approach focusing on the promoter region of each gene that specifically captured CpG methylation sites. In MetS participants, we showed decreased methylation in two CpG sites in COX6C and three CpG sites in RPL9, all p < 0.05 using the Mann-Whitney U test. There were no ATP5E CpG sites differently methylated in the MetS participants. Furthermore, while adjusting for age, gender, and smoking status, logistic regression analysis reaffirmed the associations between MetS and mean methylation within COX6C and RPL9 (both p < 0.05). In addition, Spearman’s correlation revealed a significant inverse relationship between the previously published gene expression data and methylation data for RPL9 (p < 0.05). In summary, these results highlight potential blood DNA methylation biomarkers for the MetS phenotype. However, future validation studies are warranted to strengthen our findings.

Clinical significance of novel DNA methylation biomarkers for renal clear cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor characterized by the highest mortality rate of the genitourinary cancers, and, therefore, new diagnostic and/or prognostic biomarkers are urgently needed. Based on genome-wide DNA methylation profiling in 11 pairs of ccRCC and non-cancerous renal tissues (NRT), the methylation at regulatory regions of ZNF677, FBN2, PCDH8, TFAP2B, TAC1, and FLRT2 was analyzed in 168 renal tissues and 307 urine samples using qualitative and quantitative methylation-specific PCR (MSP). Significantly higher methylation frequencies for all genes were found in ccRCC tissues compared to NRT (33-60% vs. 0-11%). The best diagnostic performance demonstrated a panel of ZNF677, FBN2, PCDH8, TFAP2B & TAC1 with 82% sensitivity and 96% specificity. Hypermethylation of ZNF677 and PCDH8 in the tissue samples was significantly related to numerous adverse clinicopathologic parameters. For the urine-based ccRCC detection, the highest diagnostic power (AUC = 0.78) was observed for a panel of ZNF677 & PCDH8 (with or without FBN2 or FLRT2) with 69-78% sensitivity and 69-80% specificity, albeit with lower values in the validation cohort. Besides, methylation of PCDH8 was significantly related to higher tumor stage and fat invasion in the study and validation cohorts. Moreover, PCDH8 was strongly predictive for OS (HR, 5.7; 95% CI 1.16-28.12), and its prognostic power considerably increased in combination with ZNF677 (HR, 12.5; 95% CI 1.47-105.58). In summary, our study revealed novel, potentially promising DNA methylation biomarkers of ccRCC with the possibility to be applied for non-invasive urine-based ccRCC detection and follow-up.

Identification of prostate cancer specific methylation biomarkers from a multi-cancer analysis

BackgroundDetecting prostate cancer at a non-aggressive stage is the main goal of prostate cancer screening. DNA methylation has been widely used as biomarkers for cancer diagnosis and prognosis, however, with low clinical translation rate. By taking advantage of multi-cancer data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we aimed to identify prostate cancer specific biomarkers which can separate between non-aggressive and aggressive prostate cancer based on DNA methylation patterns.ResultsWe performed a comparison analysis of DNA methylation status between normal prostate tissues and prostate adenocarcinoma (PRAD) samples at different Gleason stages. The candidate biomarkers were selected by excluding the biomarkers existing in multiple cancers (pan-cancer) and requiring significant difference between PRAD and other urinary samples. By least absolute shrinkage and selection operator (LASSO) selection, 8 biomarkers (cg04633600, cg05219445, cg05796128, cg10834205, cg16736826, cg23523811, cg23881697, cg24755931) were identified and in-silico validated by model constructions. First, all 8 biomarkers could separate PRAD at different stages (Gleason 6 vs. Gleason 3 + 4: AUC = 0.63; Gleason 6 vs. Gleason 4 + 3 and 8–10: AUC = 0.87). Second, 5 biomarkers (cg04633600, cg05796128, cg23523811, cg23881697, cg24755931) effectively detected PRAD from normal prostate tissues (AUC ranged from 0.88 to 0.92). Last, 6 biomarkers (cg04633600, cg05219445, cg05796128, cg23523811, cg23881697, cg24755931) completely distinguished PRAD with other urinary samples (AUC = 1).ConclusionsOur study identified and in-silico validated a panel of prostate cancer specific DNA methylation biomarkers with diagnosis value.

Multiplexed DNA Methylation Analysis in Colorectal Cancer Using Liquid Biopsy and Its Diagnostic and Predictive Value.

Early diagnosis of colorectal cancer (CRC) is of high importance as prognosis depends on tumour stage at the time of diagnosis. Detection of tumour-specific DNA methylation marks in cfDNA has several advantages over other approaches and has great potential for solving diagnostic needs. We report here the identification of DNA methylation biomarkers for CRC and give insights in our methylation-sensitive restriction enzyme coupled qPCR (MSRE-qPCR) system. Targeted microarrays were used to investigate the DNA methylation status of 360 cancer-associated genes. Validation was done by qPCR-based approaches. A focus was on investigating marker performance in cfDNA from 88 patients (44 CRC, 44 controls). Finally, the workflow was scaled-up to perform 180plex analysis on 110 cfDNA samples, to identify a DNA methylation signature for advanced colonic adenomas (AA). A DNA methylation signature (n = 44) was deduced from microarray experiments and confirmed by quantitative methylation-specific PCR (qMSP) and by MSRE-qPCR, providing for six genes’ single areas under the curve (AUC) values of >0.85 (WT1, PENK, SPARC, GDNF, TMEFF2, DCC). A subset of the signatures can be used for patient stratification and therapy monitoring for progressed CRC with liver metastasis using cfDNA. Furthermore, we identified a 35-plex classifier for the identification of AAs with an AUC of 0.80.

Promising Epigenetic Biomarkers for the Early Detection of Colorectal Cancer: A Systematic Review.

Simple SummaryHigh-performance, non-invasive screening is a requirement in colorectal cancer (CRC) as early detection is a key in reducing disease-related mortality in CRC patients. However, colonoscopy, the actual gold standard in CRC screening, is invasive and often avoided by patients. Conventional screening methods encounter several limitations; therefore, new testing strategies have been considered. DNA methylation is the most prevalent epigenetic alteration that occurs in all stages of carcinogenesis. Our research focused on identifying potential DNA methylation single biomarkers or panels as promising tools in the early detection of CRC; it evaluated methylated genes currently targeted by already approved diagnostic kits. A panel of five CTCF methylated binding sites holds the promise for early-stage specific detection of CRC. CRC screening compliance and accuracy can be enhanced by employing a stool mt-DNA methylation test.In CRC, screening compliance is decreased due to the experienced discomfort associated with colonoscopy, although this method is the gold standard in terms of sensitivity and specificity. Promoter DNA methylation (hypomethylation or hypermethylation) has been linked to all CRC stages. Study objectives: to systematically review the current knowledge on approved biomarkers, reveal new potential ones, and inspect tactics that can improve performance. This research was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines; the risk of bias was evaluated using the revised Quality Assessment of Diagnostic Accuracy Studies criteria (QUADAS-2). The Web of Science® Core Collection, MEDLINE® and Scopus® databases were searched for original articles published in peer-reviewed journals with the specific keywords “colorectal cancer”, “early detection”, “early-stage colorectal cancer”, “epigenetics”, “biomarkers”, “DNA methylation biomarkers”, “stool or blood or tissue or biopsy”, “NDRG4”, “BMP3”, “SEPT9”, and “SDC2”. Based on eligibility criteria, 74 articles were accepted for analysis. mSDC2 and mSEPT9 were frequently assessed in studies, alone or together as part of the ColoDefense panel test—the latter with the greatest performance. mBMP3 may not be an appropriate marker for detecting CRC. A panel of five methylated binding sites of the CTCF gene holds the promise for early-stage specific detection of CRC. CRC screening compliance and accuracy can be enhanced by employing a stool mt-DNA methylation test.

OA16.04 A Combined Model of Clinical, Imaging and DNA Methylation Biomarkers to Improve the Classification of Pulmonary Nodules

Early detection is the key to reducing lung cancer related deaths. Accurate malignant-benign classification of pulmonary nodules is still a great diagnostic challenge. Our previous studies (DOI: 10.7150/thno.28119; 10.1172/JCI145973) have established a blood-based DNA methylation model (PulmoSeek) to tackle this problem. Here we described a novel combined model of clinical, imaging and blood-based DNA methylation biomarkers, termed “PulmoSeek Plus”, to further improve the classification of pulmonary nodules.

S444 Accurate Detection of Esophageal Squamous Cell Carcinoma (ESCC) Using Machine Learning with Methylated DNA Biomarkers

Introduction: Esophageal squamous cell carcinoma (ESCC) is the most common type of esophageal cancer worldwide. The gold standard for its diagnosis requires esophagogastroduodenoscopy, but this is not feasible as a screening modality due to high cost and risk. Therefore, we sought to develop a diagnostic strategy using ESCC-specific methylated DNA biomarkers on esophageal cells obtained via minimally invasive method. Methods: Using genome-wide methylation data and bioinformatics, we identified candidate ESCC-specific methylated DNA biomarkers, which were initially tested on 48 ESCC-matched normal tissue pairs. These candidate biomarkers were further evaluated in a cross-sectional case-control study of 63 patients from whom esophageal cytology samples were collected using a minimally invasive sponge device. Finally, a multi-biomarker model for ESCC diagnosis was created using a machine learning pipeline with the random subspace method. Results: Five of the 6 biomarkers (cg20655070, SLC35F1, TAC1, ZNF132, and ZNF542) exhibited significantly higher methylation levels in tumor DNA vs matched control tissue DNAs (P < 0.05). When tested on sponge-derived esophageal cytology DNA, these 5 markers were all significantly hypermethylated in ESCC vs non-ESCC control DNAs (P < 0.01), and all 5 distinguished ESCCs from controls with areas under receiver operating characteristics curve (AUCs) > 0.76 (P < 0.01). Finally, a discriminatory 5-marker-plus-age diagnostic panel was then developed, which demonstrated outstanding biomarker performance (sensitivity = 0.91, specificity = 0.96, and AUC = 0.90). Conclusion: This highly discriminatory biomarker panel is a promising strategy for ESCC diagnosis using low-cost, minimally invasive sampling techniques and merits further study in prospective cancer screening trials.