DNA Methylation Markers for Breast Cancer Detection in the Developing World

IL21R hypomethylation as a biomarker for distinguishing benign and malignant breast tumours

Some benign and malignant breast tumours are similar in pathological morphology, which are difficult to be distinguished in clinical diagnosis. In this study, we intended to explore novel biomarkers for differential diagnosis of benign and malignant breast tumours. Methylation EPIC 850K beadchip and RNA-sequencing were used to analyse 29 tissue samples from patients with early-stage breast cancer (BC) and benign breast tumours for differently methylated and expressed genes. The altered methylation of IL21R was semi-quantitatively validated in an independent study with 566 tissue samples (279 BC vs. 287 benign breast tumours) using mass spectrometry. Binary logistic regression analysis was performed to evaluate the association between IL21R methylation and BC. BC-associated IL21R hypomethylation and overexpression were identified in the discovery round. In the validation round, BC patients presented significant IL21R hypomethylation compared to women with benign breast tumours (ORs ≥1.29 per-10% methylation, p-values ≤ 5.69E-14), and this hypomethylation was even enhanced in BC patients with ER-negative and PR-negative tumours as well as with triple-negative tumours. The methylation of IL21R showed efficient discriminatory power to distinguish benign breast tumours from BC (area under curve (AUC) = 0.88), and especially from ER-negative BC (AUC = 0.95), PR-negative BC (AUC = 0.93) and triple-negative BC (AUC = 0.96). We disclosed significant IL21R hypomethylation in patients with BC compared to women with benign breast tumours, and revealed the somatic change of DNA methylation could be a potential biomarker for molecular pathology of BC.

Potential Role of AKR1B1 Gene Methylation in Diagnosis of Patients With Breast Cancer

Background

In addition to the great challenge of early diagnosis and prognosis in breast cancer (BC), the role of gene promoters in BC remains largely unexplored. This study aimed to evaluate aldo-keto reductase family 1 member B1 (AKR1B1) methylation as noninvasive biomarker for early BC diagnosis.

Methods

A total of 200 (120 with BC, 40 with benign breast diseases, 40 healthy) Egyptian women were enrolled. AKR1B1 methylation level was determined using EpiTect Methyl II QPCR assay quantitative polymerase chain reaction.

Results

Findings revealed that hypermethylation AKR1B1 was reported to be associated (P < .0001) with BC cases (93.2 [75.4-98.6]) compared with benign (23.9 [22.6-48.3]) or healthy (15.5 [10.6-16]) controls. It had a great diagnostic power (area under the curve [AUC] = 0.909) that was superior to cancer antigen (CA) 15-3 (AUC = 0.681) and carcinoembryonic antigen (CEA) (AUC = 0.539). Interestingly, AKR1B1 hypermethylation was reported to be significant in identifying BC early stages (AUC = 0.899) and grades (AUC = 0.903). Independent to hormonal status and HER2neu expression, AKR1B1 hypermethylation was related to some tumor severity features, including advanced stages, high histological grades, and lymph node invasion. Also, AKR1B1 high degrees of methylation were significantly correlated with the increase in CEA (r = .195; P = .027), CA-15.3 (r = .351; P = .0001) and tumor stages (r = .274; P = .014), grades (r = .253; P = .024), and lymph node invasion (r = .275; P = .014).

Conclusions

This study revealed that aberrant AKR1B1 methylation could facilitate early BC detection from benign br0east disorders. Hypermethylated AKR1B1 was related to BC aggressiveness suggesting its potential role as diagnostic and prognostic BC biomarker.

Exploring prognostic DNA methylation genes in bladder cancer: a comprehensive analysis

The current study aimed to investigate the status of genes with prognostic DNA methylation sites in bladder cancer (BLCA). We obtained bulk transcriptome sequencing data, methylation data, and single-cell sequencing data of BLCA from public databases. Initially, Cox survival analysis was conducted for each methylation site, and genes with more than 10 methylation sites demonstrating prognostic significance were identified to form the BLCA prognostic methylation gene set. Subsequently, the intersection of marker genes associated with epithelial cells in single-cell sequencing analysis was obtained to acquire epithelial cell prognostic methylation genes. Utilizing ten machine learning algorithms for multiple combinations, we selected key genes (METRNL, SYT8, COL18A1, TAP1, MEST, AHNAK, RPP21, AKAP13, RNH1) based on the C-index from multiple validation sets. Single-factor and multi-factor Cox analyses were conducted incorporating clinical characteristics and model genes to identify independent prognostic factors (AHNAK, RNH1, TAP1, Age, and Stage) for constructing a Nomogram model, which was validated for its good diagnostic efficacy, prognostic prediction ability, and clinical decision-making benefits. Expression patterns of model genes varied among different clinical features. Seven immune cell infiltration prediction algorithms were used to assess the correlation between immune cell scores and Nomogram scores. Finally, drug sensitivity analysis of Nomogram model genes was conducted based on the CMap database, followed by molecular docking experiments. Our research offers a reference and theoretical basis for prognostic evaluation, drug selection, and understanding the impact of DNA methylation changes on the prognosis of BLCA.

Discovery and technical validation of high-performance methylated DNA markers for the detection of cervical lesions at risk of malignant progression in low- and middle-income countries

BACKGROUND

Cervical cancer remains a leading cause of death, particularly in developing countries. WHO screening guidelines recommend human papilloma virus (HPV) detection as a means to identify women at risk of developing cervical cancer. While HPV testing identifies those at risk, it does not specifically distinguish individuals with neoplasia. We investigated whether a quantitative molecular test that measures methylated DNA markers could identify high-risk lesions in the cervix with accuracy.

RESULTS

Marker discovery was performed in TCGA-CESC Infinium Methylation 450 K Array database and verified in three other public datasets. The panel was technically validated using Quantitative Multiplex-Methylation-Specific PCR in tissue sections (N = 252) and cervical smears (N = 244) from the USA, South Africa, and Vietnam. The gene panel consisted of FMN2, EDNRB, ZNF671, TBXT, and MOS. Cervical tissue samples from all three countries showed highly significant differential methylation in squamous cell carcinoma (SCC) with a sensitivity of 100% [95% CI 74.12-100.00], and specificity of 91% [95% CI 62.26-99.53] to 96% [95% CI 79.01-99.78], and receiver operating characteristic area under the curve (ROC AUC) = 1.000 [95% CI 1.00-1.00] compared to benign cervical tissue, and cervical intraepithelial neoplasia 2/3 with sensitivity of 55% [95% CI 37.77-70.84] to 89% [95% CI 67.20-98.03], specificity of 93% [95% CI 84.07-97.38] to 96% [95% CI 79.01-99.78], and a ROC AUC ranging from 0.793 [95% CI 0.68-0.89] to 0.99 [95% CI 0.97-1.00] compared to CIN1. In cervical smears, the marker panel detected SCC with a sensitivity of 87% [95% CI 77.45-92.69], specificity 95% [95% CI 88.64-98.18], and ROC AUC = 0.925 [95% CI 0.878-0.974] compared to normal, and high-grade squamous intraepithelial lesion (HSIL) at a sensitivity of 70% (95% CI 58.11-80.44), specificity of 94% (95% CI 88.30-97.40), and ROC AUC = 0.884 (95% CI 0.822-0.945) compared to low-grade intraepithelial lesion (LSIL)/normal in an analysis of pooled data from the three countries. Similar to HPV-positive, HPV-negative cervical carcinomas were frequently hypermethylated for these markers.

CONCLUSIONS

This 5-marker panel detected SCC and HSIL in cervical smears with a high level of sensitivity and specificity. Molecular tests with the ability to rapidly detect high-risk HSIL will lead to timely treatment for those in need and prevent unnecessary procedures in women with low-risk lesions throughout the world. Validation of these markers in prospectively collected cervical smear cells followed by the development of a hypermethylated marker-based cervical cancer detection test is warranted.

Screening and identification of hub-gene associated with brain metastasis in breast cancer

BACKGROUND

The presence of breast cancer in the brain, also known as brain metastasis (BMS), is the primary reason for a bad prognosis in cases of breast cancer. Breast cancer is the most prevalent malignant tumor seen in women in developing nations. At present, there is no effective method to inhibit brain metastasis of breast cancer. Therefore, it is necessary to conduct a systematic study on BMS of breast cancer, which will not provide ideas and sites for follow-up studies on the treatment and inhibition of BMS.

METHODS

In this study, data set GSE43837 was screened from gene expression omnibus database, and then R language tool was used for differential analysis of its expression spectrum, The gene ontology functional enrichment and Kyoto encyclopedia of genes and genomes signal pathway enrichment analyses, as well as the interactive gene retrieval tool for hub-gene analysis, were performed.

RESULTS

According to the findings, the primary genes linked to breast cancer brain metastases are those that involve interactions between cytokines and their respective receptors and between neuroactive ligands and their respective receptors. The majority of the gene ontology enrichment took place in the extracellular structural tissues, the extracellular matrix tissues, and the second message-mediated signaling. We were able to identify 8 genes that are linked to breast cancer spreading to the brain. The gene score for matrix metallopeptidase1 (MMP-1) was the highest among them, and the genes MMP10, tumor necrosis factor alpha-inducible protein 8, collagen type I alpha 2 chain, vascular cell adhesion molecule 1, and TNF superfamily member 11 were all connected to 1 another in an interaction way.

CONCLUSIONS

There is a possibility that the 8 key genes that were identified in this research are connected to the progression of BMS in breast cancer. Among them, MMP1 is 1 that has the potential to have a role in the diagnosis and treatment of BMS in breast cancer.

Methylation biomarkers for early cancer detection and diagnosis: Current and future perspectives

The increase in recent scientific studies on cancer biomarkers has brought great new insights into the field. Moreover, novel technological breakthroughs such as long read sequencing and microarrays have enabled high throughput profiling of many biomarkers, while advances in bioinformatic tools have made the possibility of developing highly reliable and accurate biomarkers a reality. These changes triggered renewed interest in biomarker research and provided tremendous opportunities for enhancing cancer management and improving early disease detection. DNA methylation alterations are known to accompany and contribute to carcinogenesis, making them promising biomarkers for cancer, namely due to their stability, frequency and accessibility in bodily fluids. The advent of newer minimally invasive experimental methods such as liquid biopsies provide the perfect setting for methylation-based biomarker development and application. Despite their huge potential, accurate and robust biomarkers for the conclusive diagnosis of most cancer types are still not routinely used, hence a strong need for sustained research in this field is still needed. This review provides a brief exposition of current methylation biomarkers for cancer diagnosis and early detection, including markers already in clinical use as well as various upcoming ones. It also outlines how recent big data and novel technologies will revolutionise the next generation of cancer tests in supplementing or replacing currently existing invasive techniques.

Searching for DNA methylation in patients triple-negative breast cancer: a liquid biopsy approach

INTRODUCTION

Liquid biopsies are proving to have diagnostic and prognostic value in many different cancers, and in breast cancer they have the potential to improve outcomes by providing valuable information throughout a patient's cancer journey. However, patients with triple negative breast cancer (TNBC) have received little benefit from such liquid biopsies due to underlying limitations in the discovery and utility of robust biomarkers. Here, we examine the development of DNA methylation-based liquid biopsy assays for breast cancer and how they pertain to TNBC.

AREAS COVERED

We conducted a systematic review of liquid biopsy assays for breast cancer and analyzed their relevance in TNBC. We show that the utility of DNA mutation-based assays is poor for TNBC due to the low mutational frequencies across the genome in this subtype. We offer a detailed review of mDETECT - a liquid biopsy specifically designed for assessing tumor burden in TNBC patients.

EXPERT OPINION

DNA methylation are foundational and robust events that occur in cancer evolution and may differentiate almost all forms of cancer, including TNBC. Longitudinal patient monitoring using DNA methylation-based liquid biopsies offers great potential for improving the detection and management of TNBC.

Evaluating DNA Methylation in Random Fine Needle Aspirates from the Breast to Inform Cancer Risk

Introduction. Critical regulatory genes are functionally silenced by DNA hypermethylation in breast cancer and premalignant lesions. The objective of this study was to examine whether DNA methylation assessed in random fine needle aspirates (rFNA) can be used to inform breast cancer risk. Methods. In 20 women with invasive breast cancer scheduled for surgery at Johns Hopkins Hospital, cumulative methylation status was assessed in a comprehensive manner. rFNA was performed on tumors, adjacent normal tissues, and all remaining quadrants. Pathology review was conducted on blocks from all excised tissue. The cumulative methylation index (CMI) for 12 genes was assessed by a highly sensitive QM-MSP assay in 280 aspirates and tissue from 11 incidental premalignant lesions. Mann–Whitney and Kruskal Wallis tests were used to compare median CMI by patient, location, and tumor characteristics. Results. The median age of participants was 49 years (interquartile range [IQR]: 44–58). DNA methylation was detectable at high levels in all tumor aspirates (median CMI = 252, IQR: 75–111). Methylation was zero or low in aspirates from adjacent tissue (median CMI = 11, IQR: 0–13), and other quadrants (median CMI = 2, IQR: 1–5). Nineteen incidental lesions were identified in 13 women (4 malignant and 15 premalignant). Median CMI levels were not significantly different in aspirates from quadrants ( $p=0.43$ ) or adjacent tissue ( $p=0.93$ ) in which 11 methylated incidental lesions were identified. Conclusions. The diagnostic accuracy of methylation based on rFNA alone to detect premalignant lesions or at-risk quadrants is poor and therefore should not be used to evaluate cancer risk. A more targeted approach needs to be evaluated.

Development of an automated liquid biopsy assay for methylated markers in advanced breast cancer

Current molecular liquid biopsy assays to detect recurrence or monitor response to treatment require sophisticated technology, highly trained personnel, and a turnaround time of weeks. We describe the development and technical validation of an automated Liquid Biopsy for Breast Cancer Methylation (LBx-BCM) prototype, a DNA methylation detection cartridge assay that is simple to perform and quantitatively detects nine methylated markers within 4.5 h. LBx-BCM demonstrated high interassay reproducibility when analyzing exogenous methylated DNA (75-300 DNA copies) spiked into plasma (Coefficient of Variation, CV = 7.1 - 10.9%) and serum (CV = 19.1 - 36.1%). It also demonstrated high interuser reproducibility (Spearman r = 0.887, P < 0.0001) when samples of metastatic breast cancer (MBC, N = 11) and normal control (N = 4) were evaluated independently by two users. Analyses of interplatform reproducibility indicated very high concordance between LBx-BCM and the reference assay, cMethDNA, among 66 paired plasma samples (MBC N = 40, controls N = 26; Spearman r = 0.891; 95% CI = 0.825 - 0.933, P< 0.0001). LBx-BCM achieved a ROC AUC = 0.909 (95% CI = 0.836 - 0.982), 83% sensitivity and 92% specificity; cMethDNA achieved a ROC AUC = 0.896 (95% CI = 0.817 - 0.974), 83% sensitivity and 92% specificity in test set samples. The automated LBx-BCM cartridge prototype is fast, with performance levels equivalent to the highly sensitive, manual cMethDNA method. Future prospective clinical studies will evaluate LBx-BCM detection sensitivity and its ability to monitor therapeutic response during treatment for advanced breast cancer.

High performance methylated DNA markers for detection of colon adenocarcinoma

BACKGROUND

Colon cancer (CC) is treatable if detected in its early stages. Improved CC detection assays that are highly sensitive, specific, and available at point of care are needed. In this study, we systematically selected and tested methylated markers that demonstrate high sensitivity and specificity for detection of CC in tissue and circulating cell-free DNA.

METHODS

Hierarchical analysis of 22 candidate CpG loci was conducted using The Cancer Genome Atlas (TCGA) COAD 450K HumanMethylation database. Methylation of 13 loci was analyzed using quantitative multiplex methylation-specific PCR (QM-MSP) in a training set of fresh frozen colon tissues (N = 53). Hypermethylated markers were identified that were highest in cancer and lowest in normal colon tissue using the 75th percentile in Mann-Whitney analyses and the receiver operating characteristic (ROC) statistic. The cumulative methylation status of the marker panel was assayed in an independent test set of fresh frozen colon tissues (N = 52) using conditions defined and locked in the training set. A minimal marker panel of 6 genes was defined based on ROC area under the curve (AUC). Plasma samples (N = 20 colorectal cancers, stage IV and N = 20 normal) were tested by cMethDNA assay to evaluate marker performance in liquid biopsy.

RESULTS

In the test set of samples, compared to normal tissue, a 6-gene panel showed 100% sensitivity and 90% specificity for detection of CC, and an AUC of 1.00 (95% CI 1.00, 1.00). In stage IV colorectal cancer plasma versus normal, an 8-gene panel showed 95% sensitivity, 100% specificity, and an AUC of 0.996 (95% CI 0.986, 1.00) while a 5-gene subset showed 100% sensitivity, 100% specificity, and an AUC of 1.00 (95% CI 1.00, 1.00), highly concordant with our observations in tissue.

CONCLUSIONS

We identified high performance methylated DNA marker panels for detection of CC. This knowledge has set the stage for development and implementation of novel, automated, self-contained CC detection assays in tissue and blood which can expeditiously and accurately detect colon cancer in both developed and underdeveloped regions of the world, enabling optimal use of limited resources in low- and middle-income countries.

Automated and rapid detection of cancer in suspicious axillary lymph nodes in patients with breast cancer

Preoperative staging of suspicious axillary lymph nodes (ALNs) allows patients to be triaged to ALN dissection or to sentinel lymph node biopsy (SLNB). Ultrasound-guided fine needle aspiration (FNA) and cytology of ALN is moderately sensitive but its clinical utility relies heavily on the cytologist's experience. We proposed that the 5-h automated GeneXpert system-based prototype breast cancer detection assay (BCDA) that quantitatively measures DNA methylation in ten tumor-specific gene markers could provide a facile, accurate test for detecting cancer in FNA of enlarged lymph nodes. We validated the assay in ALN-FNA samples from a prospective study of patients (N = 230) undergoing SLNB. In a blinded analysis of 218 evaluable LN-FNAs from 108 malignant and 110 benign LNs by histology, BCDA displayed a sensitivity of 90.7% and specificity of 99.1%, achieving an area under the ROC curve, AUC of 0.958 (95% CI: 0.928-0.989; P < 0.0001). Next, we conducted a study of archival FNAs of ipsilateral palpable LNs (malignant, N = 72, benign, N = 53 by cytology) collected in the outpatient setting prior to neoadjuvant chemotherapy (NAC). Using the ROC-threshold determined in the prospective study, compared to cytology, BCDA achieved a sensitivity of 94.4% and a specificity of 92.5% with a ROC-AUC = 0.977 (95% CI: 0.953-1.000; P < 0.0001). Our study shows that the automated assay detects cancer in suspicious lymph nodes with a high level of accuracy within 5 h. This cancer detection assay, scalable for analysis to scores of LN FNAs, could assist in determining eligibility of patients to different treatment regimens.

Clinical impact of PTEN methylation status as a prognostic marker for breast cancer

Background

Aberrant DNA methylation of phosphatase and tensin homolog (PTEN) gene has been found in many cancers. The object of this study was to evaluate the clinical impact of PTEN methylation as a prognostic marker in breast cancer. The study includes 153 newly diagnosed females, and they were divided according to their clinical diagnosis into breast cancer patients (n = 112) and females with benign breast lesion (n = 41). A group of healthy individuals (n = 25) were recruited as control individuals. Breast cancer patients were categorized into early stage (0–I, n = 48) and late stage (II–III, n = 64), and graded into low grade (I–II, n = 42) and high grade (III, n = 70). Their pathological types were invasive duct carcinoma (IDC) (n = 66) and duct carcinoma in situ (DCI) (n = 46). Tumor markers (CEA and CA15.3) were detected using ELISA. DNA was taken away from the blood, and the PTEN promoter methylation level was evaluated using the EpiTect Methyl II PCR method.

Results

The findings revealed the superiority of PTEN methylation status as a good discriminator of the cancer group from the other two groups (benign and control) with its highest AUC and increased sensitivity (96.4%) and specificity (100%) over tumor markers (50% and 84% for CEA and 49.1% and 86.4% for CA15.3), respectively. The frequency of PTEN methylation was 96.4% of breast cancer patients and none of the benign and controls showed PTEN methylation and the means of PTEN methylation (87 ± 0.6) were significantly increased in blood samples of breast cancer group as compared to both benign and control groups (25 ± 0.7 and 12.6 ± 0.3), respectively.

Methylation levels of PTEN were higher in the blood of patients with ER-positive than in patients with ER-negative cancers (P = 0.007) and in HER2 positive vs. HER2 negative tumors (P = 0.001). The Kaplan-Meier analysis recognizes PTEN methylation status as a significant forecaster of bad progression-free survival (PFS) and overall survival (OS), after 40 months follow-up.

Conclusions

PETN methylation could be supposed as one of the epigenetic aspects influencing the breast cancer prognosis that might foretell more aggressive actions and worse results in breast cancer patients.

Methylated markers accurately distinguish primary central nervous system lymphomas (PCNSL) from other CNS tumors

BACKGROUND

Definitive diagnosis of primary central nervous system lymphoma (PCNSL) requires invasive surgical brain biopsy, causing treatment delays. In this paper, we identified and validated tumor-specific markers that can distinguish PCNSL from other CNS tumors in tissues. In a pilot study, we tested these newly identified markers in plasma.

RESULTS

The Methylation Outlier Detector program was used to identify markers in TCGA dataset of 48 diffuse large B-cell lymphoma (DLBCL) and 656 glioblastomas and lower-grade gliomas. Eight methylated markers clearly distinguished DLBCL from gliomas. Marker performance was verified (ROC-AUC of ≥ 0.989) in samples from several GEO datasets (95 PCNSL; 2112 other primary CNS tumors of 11 types). Next, we developed a novel, efficient assay called Tailed Amplicon Multiplexed-Methylation-Specific PCR (TAM-MSP), which uses two of the methylation markers, cg0504 and SCG3 triplexed with ACTB. FFPE tissue sections (25 cases each) of PCNSL and eight types of other primary CNS tumors were analyzed using TAM-MSP. TAM-MSP distinguished PCNSL from the other primary CNS tumors with 100% accuracy (AUC = 1.00, 95% CI 0.95-1.00, P < 0.001). The TAM-MSP assay also detected as few as 5 copies of fully methylated plasma DNA spiked into 0.5 ml of healthy plasma. In a pilot study of plasma from 15 PCNSL, 5 other CNS tumors and 6 healthy individuals, methylation in cg0504 and SCG3 was detectable in 3/15 PCNSL samples (20%).

CONCLUSION

The Methylation Outlier Detector program identified methylated markers that distinguish PCNSL from other CNS tumors with accuracy. The high level of accuracy achieved by these markers was validated in tissues by a novel method, TAM-MSP. These studies lay a strong foundation for a liquid biopsy-based test to detect PCNSL-specific circulating tumor DNA.

Comprehensive analysis based on DNA methylation and RNA-seq reveals hypermethylation of the up-regulated WT1 gene with potential mechanisms in PAM50 subtypes of breast cancer

Background

Breast cancer (BC), one of the most widespread cancers worldwide, caused the deaths of more than 600,000 women in 2018, accounting for about 15% of all cancer-associated deaths in women that year. In this study, we aimed to discover potential prognostic biomarkers and explore their molecular mechanisms in different BC subtypes using DNA methylation and RNA-seq.

Methods

We downloaded the DNA methylation datasets and the RNA expression profiles of primary tissues of the four BC molecular subtypes (luminal A, luminal B, basal-like, and HER2-enriched), as well as the survival information from The Cancer Genome Atlas (TCGA). The highly expressed and hypermethylated genes across all the four subtypes were screened. We examined the methylation sites and the downstream co-expressed genes of the selected genes and validated their prognostic value using a different dataset (GSE20685). For selected transcription factors, the downstream genes were predicted based on the Gene Transcription Regulation Database (GTRD). The tumor microenvironment was also evaluated based on the TCGA dataset.

Results

We found that Wilms tumor gene 1 (WT1), a transcription factor, was highly expressed and hypermethylated in all the four BC subtypes. All the WT1 methylation sites exhibited hypermethylation. The methylation levels of the TSS200 and 1stExon regions were negatively correlated with WT1 expression in two BC subtypes, while that of the gene body region was positively associated with WT1 expression in three BC subtypes. Patients with low WT1 expression had better overall survival (OS). Five genes including COL11A1, GFAP, FGF5, CD300LG, and IGFL2 were predicted as the downstream genes of WT1. Those five genes were dysregulated in the four BC subtypes. Patients with a favorable 6-gene signature (low expression of WT1 and its five predicted downstream genes) exhibited better OS than that with an unfavorable 6-gene signature. We also found a correlation between WT1 and tamoxifen using STITCH. Higher infiltration rates of CD8 T cells, plasma cells, and monocytes were found in the lower quartile WT1 group and the favorable 6-gene signature group. In conclusion, we demonstrated that WT1 is hypermethylated and up-regulated in the four BC molecular subtypes and a 6-gene signature may predict BC prognosis.

Urine DNA methylation assay enables early detection and recurrence monitoring for bladder cancer

BACKGROUNDCurrent methods for the detection and surveillance of bladder cancer (BCa) are often invasive and/or possess suboptimal sensitivity and specificity, especially in early-stage, minimal, and residual tumors.METHODSWe developed an efficient method, termed utMeMA, for the detection of urine tumor DNA methylation at multiple genomic regions by MassARRAY. We identified the BCa-specific methylation markers by combined analyses of cohorts from Sun Yat-sen Memorial Hospital (SYSMH), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) database. The BCa diagnostic model was built in a retrospective cohort (n = 313) and validated in a multicenter, prospective cohort (n = 175). The performance of this diagnostic assay was analyzed and compared with urine cytology and FISH.RESULTSWe first discovered 26 significant methylation markers of BCa in combined analyses. We built and validated a 2-marker-based diagnostic model that discriminated among patients with BCa with high accuracy (86.7%), sensitivity (90.0%), and specificity (83.1%). Furthermore, the utMeMA-based assay achieved a great improvement in sensitivity over urine cytology and FISH, especially in the detection of early-stage (stage Ta and low-grade tumor, 64.5% vs. 11.8%, 15.8%), minimal (81.0% vs. 14.8%, 37.9%), residual (93.3% vs. 27.3%, 64.3%), and recurrent (89.5% vs. 31.4%, 52.8%) tumors. The urine diagnostic score from this assay was better associated with tumor malignancy and burden.CONCLUSIONUrine tumor DNA methylation assessment for early diagnosis, minimal, residual tumor detection and surveillance in BCa is a rapid, high-throughput, noninvasive, and promising approach, which may reduce the burden of cystoscopy and blind second surgery.FUNDINGThis study was supported by the National Key Research and Development Program of China and the National Natural Science Foundation of China.

Identification of differentially methylated genes as diagnostic and prognostic biomarkers of breast cancer

Background

Aberrant DNA methylation is significantly associated with breast cancer.

Methods

In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis.

Results

In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994–1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976–1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival.

Conclusions

Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02124-6.

A Novel Promoter CpG-Based Signature for Long-Term Survival Prediction of Breast Cancer Patients

DNA methylation has been reported as one of the most critical epigenetic aberrations during the tumorigenesis and development of breast cancer (BC). This study explored a novel promoter CpG-based signature for long-term survival prediction of BC patients. We used The Cancer Genome Atlas (TCGA) data as training set, and results were validated in an independent dataset from Gene Expression Omnibus (GEO). First, the differential methylation CpG sites were screened in TCGA dataset, of which the candidate promoter CpG sites were preliminarily identified with the univariate Cox regression analysis and the least absolute shrinkage and selection operator regression analysis. Second, the signature was constructed with stepwise regression analysis and multivariate Cox proportional hazards model, which was validated with the survival analysis of two cohorts each from TCGA and GEO databases. The 10-year receiver operating characteristic curves of risk score presented an area under the curve of over 0.7 for both cohorts. A nomogram was also constructed and released. Moreover, Gene Set Enrichment Analysis was performed to identify the more active pathways in high-risk patients. The CpG sites-target gene correlations and differential methylation regions were further explored. In conclusion, the promoter CpG-based signature exhibited good prognostic prediction efficacy in the long-term overall survival of BC patients.

DNA methylation patterns of RAR-β2 and RASSF1A gene promoters in FNAB samples from Greek population with benign or malignant breast lesions

BACKGROUND

Promoter hypermethylation is common in Breast Cancer (BC) with studies mainly in histological specimens showing frequent methylation of tumor suppressor genes (TSGs) compared with normal tissues. The aim of this study was to estimate the frequency of promoter methylation of RAR-β2 and RASSF1A genes in breast FNAB material aiming to evaluate the methylation status of these two genes as biomarker for detecting BC in Greek population.

METHODS

FNAB material from 104 patients was collected for cytological evaluation and epigenetic analysis. DNA was extracted and subjected to bisulfite conversion. A methylation-specific PCR was carried out and the final products were separated with electrophoresis in 2% agarose gels.

RESULTS

From 104 samples, RASSF1A hypermethylation was observed in 78 (75%) and RAR-β2 hypermethylation in 64 (61.6%). 84% and 78% of the cases diagnosed with breast malignancy (n = 50) were methylated for RASSF1A and RAR-β2, respectively. Methylated RASSF1A and RAR-β2 were also detected in 88.3% and 76.5% in samples diagnosed as suspicious for malignancy (n = 17) and in 57.2% of samples diagnosed with atypia (n = 14). The Odds Ratio for breast malignancy was 4.545 in patients with RASSF1A hypermethylation and 9.167 in patients with RAR-β2 hypermethylation underlying their promoter's methylation positive correlation with breast malignancy.

CONCLUSION

To optimize the sensitivity and specificity of this epigenetic setting, more TSGs related to BC should be gradually imported in our evaluated methylation panel and be validated in a larger study sample with the aim that the obtained epigenetic profiles will provide clinicians with valuable tools for management of BC patients in Greece.