Whole-Blood DNA Methylation Markers in Early Detection of Breast Cancer: A Systematic Literature Review

Machine learning unveils an immune-related DNA methylation profile in germline DNA from breast cancer patients

BACKGROUND

There is an unmet need for precise biomarkers for early non-invasive breast cancer detection. Here, we aimed to identify blood-based DNA methylation biomarkers that are associated with breast cancer.

METHODS

DNA methylation profiling was performed for 524 Asian Chinese individuals, comprising 256 breast cancer patients and 268 age-matched healthy controls, using the Infinium MethylationEPIC array. Feature selection was applied to 649,688 CpG sites in the training set. Predictive models were built by training three machine learning models, with performance evaluated on an independent test set. Enrichment analysis to identify transcription factors binding to regions associated with the selected CpG sites and pathway analysis for genes located nearby were conducted.

RESULTS

A methylation profile comprising 51 CpGs was identified that effectively distinguishes breast cancer patients from healthy controls achieving an AUC of 0.823 on an independent test set. Notably, it outperformed all four previously reported breast cancer-associated methylation profiles. Enrichment analysis revealed enrichment of genomic loci associated with the binding of immune modulating AP-1 transcription factors, while pathway analysis of nearby genes showed an overrepresentation of immune-related pathways.

CONCLUSION

This study has identified a breast cancer-associated methylation profile that is immune-related to potential for early cancer detection.

Hypermethylation of the Gene Body in SRCIN1 Is Involved in Breast Cancer Cell Proliferation and Is a Potential Blood-Based Biomarker for Early Detection and a Poor Prognosis

Breast cancer is a leading cause of cancer mortality in women worldwide. Using the Infinium MethylationEPIC BeadChip, we analyzed plasma sample methylation to identify the SRCIN1 gene in breast cancer patients. We assessed SRCIN1-related roles and pathways for their biomarker potential. To verify the methylation status, quantitative methylation-specific PCR (qMSP) was performed on genomic DNA and circulating cell-free DNA samples, and mRNA expression analysis was performed using RT‒qPCR. The results were validated in a Western population; for this analysis, the samples included plasma samples from breast cancer patients from the USA and from The Cancer Genome Atlas (TCGA) cohort. To study the SRCIN1 pathway, we conducted cell viability assays, gene manipulation and RNA sequencing. SRCIN1 hypermethylation was identified in 61.8% of breast cancer tissues from Taiwanese patients, exhibiting specificity to this malignancy. Furthermore, its presence correlated significantly with unfavorable 5-year overall survival outcomes. The levels of methylated SRCIN1 in the blood of patients from Taiwan and the USA correlated with the stage of breast cancer. The proportion of patients with high methylation levels increased from 0% in healthy individuals to 63.6% in Stage 0, 80% in Stage I and 82.6% in Stage II, with a sensitivity of 78.5%, an accuracy of 90.3% and a specificity of 100%. SRCIN1 hypermethylation was significantly correlated with increased SRCIN1 mRNA expression (p < 0.001). Knockdown of SRCIN1 decreased the viability of breast cancer cells. SRCIN1 silencing resulted in the downregulation of ESR1, BCL2 and various cyclin protein expressions. SRCIN1 hypermethylation in the blood may serve as a noninvasive biomarker, facilitating early detection and prognosis evaluation, and SRCIN1-targeted therapies could be used in combination regimens for breast cancer patients.

Pruning and thresholding approach for methylation risk scores in multi-ancestry populations

Recent efforts have focused on developing methylation risk scores (MRS), a weighted sum of the individual's DNA methylation (DNAm) values of pre-selected CpG sites. Most of the current MRS approaches that utilize Epigenome-wide association studies (EWAS) summary statistics only include genome-wide significant CpG sites and do not consider co-methylation. New methods that relax the p-value threshold to include more CpG sites and account for the inter-correlation of DNAm might improve the predictive performance of MRS. We paired informed co-methylation pruning with P-value thresholding to generate pruning and thresholding (P+T) MRS and evaluated its performance among multi-ancestry populations. Through simulation studies and real data analyses, we demonstrated that pruning provides an improvement over simple thresholding methods for prediction of phenotypes. We demonstrated that European-derived summary statistics can be used to develop P+T MRS among other populations such as African populations. However, the prediction accuracy of P+T MRS may differ across multi-ancestry population due to environmental/cultural/social differences.

Underexplored reciprocity between genome-wide methylation status and long non-coding RNA expression reflected in breast cancer research: potential impacts for the disease management in the framework of 3P medicine

Breast cancer (BC) is the most common female malignancy reaching a pandemic scale worldwide. A comprehensive interplay between genetic alterations and shifted epigenetic regions synergistically leads to disease development and progression into metastatic BC. DNA and histones methylations, as the most studied epigenetic modifications, represent frequent and early events in the process of carcinogenesis. To this end, long non-coding RNAs (lncRNAs) are recognized as potent epigenetic modulators in pathomechanisms of BC by contributing to the regulation of DNA, RNA, and histones' methylation. In turn, the methylation status of DNA, RNA, and histones can affect the level of lncRNAs expression demonstrating the reciprocity of mechanisms involved. Furthermore, lncRNAs might undergo methylation in response to actual medical conditions such as tumor development and treated malignancies. The reciprocity between genome-wide methylation status and long non-coding RNA expression levels in BC remains largely unexplored. Since the bio/medical research in the area is, per evidence, strongly fragmented, the relevance of this reciprocity for BC development and progression has not yet been systematically analyzed. Contextually, the article aims at:consolidating the accumulated knowledge on both-the genome-wide methylation status and corresponding lncRNA expression patterns in BC andhighlighting the potential benefits of this consolidated multi-professional approach for advanced BC management. Based on a big data analysis and machine learning for individualized data interpretation, the proposed approach demonstrates a great potential to promote predictive diagnostics and targeted prevention in the cost-effective primary healthcare (sub-optimal health conditions and protection against the health-to-disease transition) as well as advanced treatment algorithms tailored to the individualized patient profiles in secondary BC care (effective protection against metastatic disease). Clinically relevant examples are provided, including mitochondrial health control and epigenetic regulatory mechanisms involved.

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.

The influence of blood sample processing on blood-based DNA methylation signatures

Stability is crucial for the clinical applicable biomarker such as DNA methylation profiles. However, the influence of various blood processing on the DNA methylation signatures have been barely studied. Here, we systematically evaluated the impact of temporary storage and frozen and thaw on the levels of DNA methylation. The methylation intensities of 13 CpG loci from 53 individuals (42 healthy participants and 11 lung cancer patients) whose blood samples were processed by up to 14 various protocols were quantitatively determined by the mass spectrometry, obtaining more than 8,000 quantitative data. We disclosed a trend of accumulatively increased DNA methylation along with time when the blood from healthy people were stored for up to 96 hours at room temperature (RT), whereas the storage at 4℃ had much weaker effects or no impact. On the contrary, the methylation patterns in the blood of lung cancer patients were more stable at both RT and 4℃ even for 96 hours. Multiple cycles of frozen and thaw could result in demethylation, but was more significant to the blood than to the extracted DNA. Our study indicated that the blood processing in vitro could influence the DNA methylation signatures and introduce unexpected biases.

Quantitative Analysis of Plasma Cell-Free DNA and Its DNA Integrity and Hypomethylation Status as Biomarkers for Tumor Burden and Disease Progression in Patients with Metastatic Neuroendocrine Neoplasias

Simple Summary

Neuroendocrine neoplasias (NEN) are a heterogeneous group of frequent slow-progressing malignant tumors for which a reliable marker for tumor relapse and progression is still lacking. Previously, circulating cell-free DNA and its global methylation status and fragmentation rate have been proposed to be valuable prognostic tumor markers in a variety of malignancies. In the current study, we compared plasma cell-free DNA (cfDNA) properties of NEN patients with a healthy control group and a group of surgically cured patients. Our results revealed significantly higher plasma cfDNA concentrations with increased fragmentation and hypomethylation in patients with advanced metastatic NEN, which was strongly associated with tumor load and could help to differentiate between metastasized disease and presumably cured patients. This suggests that the combined analysis of plasma cfDNA characteristics is a potent and sensitive prognostic and therapeutic biomarker for tumor burden and disease progression in patients with neuroendocrine neoplasias.

Abstract

Background: Neuroendocrine neoplasia (NEN) encompasses a diverse group of malignancies marked by histological heterogeneity and highly variable clinical outcomes. Apart from Chromogranin A, specific biomarkers predicting residual tumor disease, tumor burden, and disease progression in NEN are scant. Thus, there is a strong clinical need for new and minimally invasive biomarkers that allow for an evaluation of the prognosis, clinical course, and response to treatment of NEN patients, thereby helping implement individualized treatment decisions in this heterogeneous group of patients. In the current prospective study, we evaluated the role of plasma cell-free DNA concentration and its global hypomethylation and fragmentation as possible diagnostic and prognostic biomarkers in patients with neuroendocrine neoplasias. Methods: The plasma cfDNA concentration, cfDNA Alu hypomethylation, and LINE-1 cfDNA integrity were evaluated prospectively in 63 NEN patients with presumably cured or advanced metastatic disease. The cfDNA characteristics in NEN patients were compared to the results of a group of 29 healthy controls and correlated with clinical and histopathological data of the patients. Results: Patients with advanced NEN showed a significantly higher cfDNA concentration and percentage of Alu hypomethylation and a reduced LINE-1 cfDNA integrity as compared to the surgically cured NET patients and the healthy control group. The increased hypomethylation and concentration of cfDNA and the reduced cfDNA integrity in NEN patients were strongly associated with tumor burden and poor prognosis, while no correlation with tumor grading, differentiation, localization, or hormonal activity could be found. Multiparametric ROC analysis of plasma cfDNA characteristics was able to distinguish NEN patients with metastatic disease from the control group and the cured NEN patients with AUC values of 0.694 and 0.908, respectively. This was significant even for the group with only a low tumor burden. Conclusions: The present study, for the first time, demonstrates that the combination of plasma cfDNA concentration, global hypomethylation, and fragment length pattern has the potential to serve as a potent and sensitive prognostic and therapeutic “liquid biopsy” biomarker for tumor burden and disease progression in patients with neuroendocrine neoplasias.

[Detection of DNA methylation of HYAL2 gene for differentiating malignant from benign thyroid tumors]

OBJECTIVE

To assess the value of DNA methylation level of HYAL2 gene as a molecular marker for differential diagnosis of malignant and benign thyroid tumors.

METHODS

DNA methylation of HYAL2 gene in tissue specimens of 190 patients with papillary thyroid cancer (PTC) and 190 age- and gender-matched patients with benign thyroid tumors was examined by mass spectrometry, and the protein expression of HYAL2 was detected immunohistochemically for another 55 pairs of patients. Logistic regression analysis was performed to calculate the odds ratio (OR) and evaluate the correlation of per 10% reduction in DNA methylation with PTC. Receiver operating characteristic (ROC) curve analysis was performed and the area under curve (AUC) was calculated to assess the predictive value of alterations in HYAL2 methylation.

RESULTS

Hypomethylation of HYAL2_CpG_3 was significantly correlated with early-stage PTC (OR=1.51, P=0.001), even in stage I cancer (OR=1.42, P=0.007). Age-stratified analysis revealed a significantly stronger correlation between increased HYAL2_CpG_ 3 methylation and early-stage PTC in patients below 50 years than in those older than 50 years (OR: 1.89 vs 1.37, P < 0.05); ROC analysis also showed a larger AUC of 0.787 in younger patients. The results of immunohistochemistry showed that patients with PTC had significantly higher protein expressions of HYAL2 than patients with benign tumors.

CONCLUSION

The alterations of DNA methylation level of HYAL2 gene is significantly correlated with early-stage PTC, suggesting the value of DNA methylation level as a potential biomarker for differentiation of malignant from benign thyroid tumors.

DNA methylation in genes associated with the evolution of ageing and disease: A critical review

Ageing is characterised by a physical decline in biological functioning which results in a progressive risk of mortality with time. As a biological phenomenon, it is underpinned by the dysregulation of a myriad of complex processes. Recently, however, ever-increasing evidence has associated epigenetic mechanisms, such as DNA methylation (DNAm) with age-onset pathologies, including cancer, cardiovascular disease, and Alzheimer's disease. These diseases compromise healthspan. Consequently, there is a medical imperative to understand the link between epigenetic ageing, and healthspan. Evolutionary theory provides a unique way to gain new insights into epigenetic ageing and health. This review will: (1) provide a brief overview of the main evolutionary theories of ageing; (2) discuss recent genetic evidence which has revealed alleles that have pleiotropic effects on fitness at different ages in humans; (3) consider the effects of DNAm on pleiotropic alleles, which are associated with age related disease; (4) discuss how age related DNAm changes resonate with the mutation accumulation, disposable soma and programmed theories of ageing; (5) discuss how DNAm changes associated with caloric restriction intersect with the evolution of ageing; and (6) conclude by discussing how evolutionary theory can be used to inform investigations which quantify age-related DNAm changes which are linked to age onset pathology.

[Peripheral blood EMR3 gene methylation level is correlated with breast cancer in Chinese women]

OBJECTIVE

To explore the association of methylation levels of C19orf57, MAP9, EMR3, NEK6 and PCOLCE2 genes in peripheral blood with breast cancer (BC) in Chinese women.

METHODS

We collected peripheral blood samples from 258 early-stage BC patients and 272 healthy women. Agena matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was utilized to quantitatively measure the methylation levels of CpG sites in the genes. The association between DNA methylation and BC was analyzed using a logistic regression model adjusted for covariants. Spearman's correlation analysis was performed to analyze the association between the gene methylation levels and age. The methylation levels of the genes in the BC patients with different clinical characteristics were investigated using non-parametric tests.

RESULTS

In stead of EMR3 gene hypermethylation as found in BC patients as found in the Caucasian population, EMR3 gene hypomethylation was found to correlate with BC in Chinese women, but this correlation was significant only in women beyond the age of 50 years (for every 10% reduction of the methylation level, EMR3_CpG_1: OR=1.40; EMR3_CpG_2: OR=2.31; EMR3_CpG_3: OR=2.76, P < 0.05). EMR3 methylation was not or was only weakly correlated with tumor stage, size, lymphatic metastasis, ER, PR, HER2, or Ki67. Our data did not show a correlation between C19orf57 methylation and BC.

CONCLUSION

Peripheral blood EMR3 gene hypomethylation is associated with BC in Chinese women, especially in those at an old age and in postmenopausal women.

Ten Years of EWAS

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

Discovery of novel DNA methylation biomarkers for non-invasive sporadic breast cancer detection in the Latino population

Human diversity is one of the main pitfalls in the development of robust worldwide biomarkers in oncology. Epigenetic variability across human populations is associated with different genetic backgrounds, as well as variable lifestyles and environmental exposures, each of which should be investigated. To identify potential non-invasive biomarkers of sporadic breast cancer in the Uruguayan population, we studied genome-wide DNA methylation using Illumina methylation arrays in leukocytes of 22 women with sporadic breast cancer and 10 healthy women in a case-control study. We described a panel of 38 differentially methylated CpG positions that was able to cluster breast cancer patients (BCP) and controls, and that also recapitulated methylation differences in 12 primary breast tumors and their matched normal breast tissue. Moving forward, we simplified the detection method to improve its applicability in a clinical setting and used an independent well-characterized cohort of 80 leukocyte DNA samples from BCP and 80 healthy controls to validate methylation results at specific cancer-related genes. Our investigations identified methylation at CYFIP1 as a novel epigenetic biomarker candidate for sporadic breast cancer in the Uruguayan population. These results provide a proof-of-concept for the design of larger studies aimed at validating biomarker panels for the Latin American population.

Methylation of WT1, CA10 in peripheral blood leukocyte is associated with breast cancer risk: a case-control study

Background

Studies have shown that abnormal changes of specific-gene DNA methylation in leukocytes may be associated with an elevated risk of cancer. However, associations between the methylation of the zinc-related genes, WT1 and CA10, and breast cancer risk remain unknown.

Methods

The methylation of WT1 and CA10 was analyzed by methylation-sensitive high-resolution-melting (MS-HRM) in a case-control study with female subjects (N = 959). Logistic regression was used to analyze the associations, and propensity score (PS) method was used to adjust confounders.

Results

The results showed that WT1 hypermethylation was associated with an increased risk of breast cancer, with an odds ratio (OR) of 3.07 [95% confidence interval (CI): 1.67–5.64, P < 0.01]. Subgroup analyses showed that WT1 hypermethylation was specifically associated with an elevated risk of luminal A subtype (OR = 2.62, 95% CI: 1.11–6.20, P = 0.03) and luminal B subtype (OR = 3.23, 95% CI: 1.34–7.80, P = 0.01). CA10 hypermethylation was associated with an increased risk of luminal B subtype (OR = 1.80, 95% CI: 1.09–2.98, P = 0.02).

Conclusion

The results of the present study suggest that the hypermethylation of WT1 methylation in leukocytes is significantly associated with an increased risk of breast cancer. The hypermethylation of WT1 is associated with an increased risk of luminal subtypes of breast cancer, and the hypermethylation of CA10 is associated with an increased risk of luminal B subtype of breast cancer.

Methylation silencing of TGF-β receptor type II is involved in malignant transformation of esophageal squamous cell carcinoma

Background

Although massive studies have been conducted to investigate the mechanisms of esophageal squamous cell carcinoma (ESCC) carcinogenesis, the understanding of molecular alterations during the malignant transformation of epithelial dysplasia is still lacking, especially regarding epigenetic changes.

Results

To better characterize the methylation changes during the malignant transformation of epithelial dysplasia, a whole-genome bisulfite sequencing analysis was performed on a series of tumor, dysplastic, and non-neoplastic epithelial tissue samples from esophageal squamous cell carcinoma (ESCC) patients. Promoter hypermethylation in TGF-β receptor type II (TGFBR2), an important mediator of TGF-β signaling, was identified. Further, we evaluated the methylation and expression of TGFBR2 in tumor samples through The Cancer Genome Atlas multiplatform data as well as immunohistochemistry. Moreover, treatment of ESCC cell lines with5-Aza-2′-deoxycytidine, a DNA methyltransferase inhibitor, reactivated the expression of TGFBR2. The lentiviral mediating the overexpression of TGFBR2 inhibited the proliferation of ESCC cell line by inducing cell cycle G2/M arrest. Furthermore, the overexpression of TGFBR2 inhibited the tumor growth obviously in vivo.

Conclusions

The characterization of methylation silencing of TGFBR2 in ESCC will enable us to further explore whether this epigenetic change could be considered as a predictor of malignant transformation in esophageal epithelial dysplasia and whether use of a TGFBR2 agonist may lead to a new therapeutic strategy in patients with ESCC.

Methylation silencing of TGF-β receptor type II is involved in malignant transformation of esophageal squamous cell carcinoma

BACKGROUND

Although massive studies have been conducted to investigate the mechanisms of esophageal squamous cell carcinoma (ESCC) carcinogenesis, the understanding of molecular alterations during the malignant transformation of epithelial dysplasia is still lacking, especially regarding epigenetic changes.

RESULTS

To better characterize the methylation changes during the malignant transformation of epithelial dysplasia, a whole-genome bisulfite sequencing analysis was performed on a series of tumor, dysplastic, and non-neoplastic epithelial tissue samples from esophageal squamous cell carcinoma (ESCC) patients. Promoter hypermethylation in TGF-β receptor type II (TGFBR2), an important mediator of TGF-β signaling, was identified. Further, we evaluated the methylation and expression of TGFBR2 in tumor samples through The Cancer Genome Atlas multiplatform data as well as immunohistochemistry. Moreover, treatment of ESCC cell lines with5-Aza-2'-deoxycytidine, a DNA methyltransferase inhibitor, reactivated the expression of TGFBR2. The lentiviral mediating the overexpression of TGFBR2 inhibited the proliferation of ESCC cell line by inducing cell cycle G2/M arrest. Furthermore, the overexpression of TGFBR2 inhibited the tumor growth obviously in vivo.

CONCLUSIONS

The characterization of methylation silencing of TGFBR2 in ESCC will enable us to further explore whether this epigenetic change could be considered as a predictor of malignant transformation in esophageal epithelial dysplasia and whether use of a TGFBR2 agonist may lead to a new therapeutic strategy in patients with ESCC.

Methylation profiling in promoter sequences of ATM and CDKN2A (p14ARF/p16INK4a ) genes in blood and cfDNA from women with impalpable breast lesions

The objective of the present study was to evaluate the epigenetic changes occurring in early stages of breast cancer. The present study investigated the methylation profile of the ATM, p14^ARF and p16^INK4a promoters in total blood and plasma cell-free DNA (cfDNA) from women with impalpable breast lesions compared with in total blood of a control cohort of women without breast lesions. The samples were evaluated using the methylation-specific PCR method. The Fisher's exact test was used to evaluate statistical significance between the methylation and clinical variables. A total of 111 women were evaluated, including 56 women with impalpable breast cancer (39/56 also had paired plasma cfDNA) and 55 women in the control cohort (55 blood DNA). For blood DNA from women with malignant impalpable breast lesions, p16^INK4a exhibited the greatest percentage of methylation (48%), followed by ATM (37.5%) and p14^ARF (27%) promoters, regardless of age variation. For plasma cfDNA, the methylation rates for ATM, p14^ARF and p16^INK4a were 26, 26 and 10%, respectively. The methylation rates for the blood DNA of controls were the lowest for ATM (9%), p14^ARF (7%) and p16^INK4a (7%). The women with impalpable breast lesions (benign and malignant lesions) exhibited the highest methylation rate, regardless of age, compared with the paired plasma cfDNA and controls. This epigenetic change was statistically significant for the promoters of ATM (P=0.009) and p16^INK4a (P=0.001) (impalpable breast lesions vs. control). The present study demonstrated that epigenetic changes occurring in the ATM and CDKN2A genes detectable in liquid biopsy were associated with the development of impalpable breast lesions.

The Role of DNA Methylation in Ischemic Stroke: A Systematic Review

Background: Knowledge about the classic risk and protective factors of ischemic stroke is accumulating, but the underlying pathogenesis has not yet been fully understood. As emerging evidence indicates that DNA methylation plays a role in the pathological process of cerebral ischemia, this study aims to summarize the evidence of the association between DNA methylation and ischemic stroke. Methods: MEDLINE, EMBASE, PubMed, and Cochrane Central Register of Controlled Trials were searched for eligible studies. The results reported by each study were summarized narratively. Results: A total of 20 studies with 7,014 individuals finally met the inclusion criteria. Three studies focused on global methylation, 11 studies on candidate-gene methylation, and six on epigenome-wide methylation analysis. Long-interspersed nuclear element 1 was found to be hypomethylated in stroke cases in two studies. Another 16 studies reported 37 genes that were differentially methylated between stroke cases and controls. Individuals with ischemic stroke were also reported to have higher acceleration in Hanuum 's epigenetic age compared to controls. Conclusion: DNA methylation might be associated with ischemic stroke and play a role in several pathological pathways. It is potentially a promising biomarker for stroke prevention, diagnosis and treatment, but the current evidence is limited by sample size and cross-sectional or retrospective design. Therefore, studies on large asymptomatic populations with the prospective design are needed to validate the current evidence, explore new pathways and identify novel risk/protective loci.

Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk

DNA methylation patterns in the blood, genetic risk scores (GRSs), and environmental risk factors can potentially improve breast cancer (BC) risk prediction. We assessed the individual and joint predictive performance of methylation, GRS, and environmental risk factors for BC incidence in a prospective cohort study. In a cohort of 5462 women aged 50–75 from Germany, 101 BC cases were identified during 14 years of follow‐up and were compared to 263 BC‐free controls in a nested case–control design. Three previously suggested methylation risk scores (MRSs) based on methylation of 423, 248, and 131 cytosine‐phosphate‐guanine (CpG) loci, and a GRS based on the risk alleles from 269 recently identified single nucleotide polymorphisms were constructed. Additionally, multiple previously proposed environmental risk scores (ERSs) were built based on environmental variables. Areas under the receiver operating characteristic curves (AUCs) were estimated for evaluating BC risk prediction performance. MRS and ERS showed limited accuracy in predicting BC incidence, with AUCs ranging from 0.52 to 0.56 and from 0.52 to 0.59, respectively. The GRS predicted BC incidence with a higher accuracy (AUC = 0.61). Adjusted odds ratios per standard deviation increase (95% confidence interval) were 1.07 (0.84–1.36) and 1.40 (1.09–1.80) for the best performing MRS and ERS, respectively, and 1.48 (1.16–1.90) for the GRS. A full risk model combining the MRS, GRS, and ERS predicted BC incidence with the highest accuracy (AUC = 0.64) and might be useful for identifying high‐risk populations for BC screening.