BIOMEDIKA
ISSN: 2085-8345.
E-ISSN: 2541-2582
Vol 18.
No.
1 Februari 2026 doi: 10.
23917/biomedika.
THE ROLE OF EPIGENOME-WIDE ASSOCIATION STUDIES (EWAS) IN IDENTIFYING
EPIGENETIC BIOMARKERS FOR BREAST CANCER: A NARRATIVE REVIEW
Karunia1.
Rafika I.
Paramita2,3.
Sonar S.
Panigoro4
AFFILIATIONS
MasterAos Programme in Biomedical Science.
Faculty of Medicine.
Universitas Indonesia.
Jakarta.
Indonesia Department of Medical Chemistry.
Faculty of Medicine.
Universitas Indonesia.
Jakarta.
Indonesia Bioinformatics Core Facilities Ae IMERI.
Faculty of Medicine.
Universitas Indonesia.
Jakarta.
Indonesia Division of Surgical Oncology.
Department of Surgery.
Faculty of Medicine.
Universitas Indonesia.
Jakarta.
Indonesia
ABSTRACT
Breast cancer remains the most common malignancy among women worldwide and a leading cause of cancer-related mortality.
Advances in epigenetics, particularly through the Epigenome-Wide Association Study (EWAS) approach, have provided new opportunities to identify epigenetic biomarkers for early detection, risk assessment, and therapeutic monitoring.
This narrative review aims to describe the role of EWAS in identifying DNA methylation biomarkers relevant to breast cancer and to highlight current methodological challenges.
Literature was retrieved from PubMed.
ScienceDirect, and Google Scholar using the keywords AuEWAS,Ay Aubreast cancer,Ay AuDNA methylation,Ay and Auepigenetic biomarker,Ay focusing on studies published between 2015 and 2025.
Findings indicate that EWAS can reveal methylation patterns associated with cancer risk, prognosis, and potential for noninvasive detection, with alterations detectable even before clinical onset.
Several candidate biomarkers identified include methylation changes in genes such as BRCA1.
RASSF1A.
CDH1, and APC, as well as specific CpG sites associated with hormonal exposure and lifestyle-related risk factors.
Despite technological advances in microarray platforms and bioinformatics, many studies still face issues such as cross-sectional design, cellular heterogeneity, and limited replication.
These challenges highlight the need for standardized analytical pipelines, larger longitudinal cohorts, and multi-omics integration to improve the reliability and clinical applicability of EWAS findings.
Nevertheless, with growing standardization and integration of multi-omics data.
EWAS holds significant promise for advancing precision medicine toward more predictive and preventive breast cancer care.
KEYWORDS:
EWAS.
DNA Methylation.
Epigenetic.
Biomarker.
Breast Cancer This work is licensed under a Creative Commons AttributionNonCommercial 4.
International License.
CORRESPONDING AUTHOR:
Karunia karunia31@ui.
INTRODUCTION
Breast cancer, also known as carcinoma mammae, is currently the most common type of According to the Global Cancer Observatory cancer among women and the second leading (GLOBOCAN), the incidence of breast cancer cause of cancer-related death worldwide.
1 It is a continues to rise across various countries.
In 2020, malignant tumor that develops in breast tissue, there were 2,261,419 new cases worldwide including the mammary glands, fatty tissue, and .
ccounting for 11.
7% of all cancer case.
with an incidence rate of approximately 44 cases per affects women, men can also develop this disease.
100,000 population, making it the most common Currently, breast cancer remains one of the most cancer globally.
In Indonesia, breast cancer also feared illnesses, particularly among women, due to ranks first among all cancer types, with 65,858 new Although it Avalaible online at https://journals2.
id/index.
php/biomedika THE ROLE OF EPIGENOME-WIDE ASSOCIATION STUDIES A (Karuni.
6%) out of 396,914 total new cancer sites recognized as the most common epigenetic cases, and remains the leading cause of cancer- The EWAS approach distinguishes cancer related mortality, with a death rate of 15.
3 per 100,000 population.
It is estimated that one in alterations in DNA methylation patterns that affect every eight diagnosed cancers worldwide is breast cellular phenotypes.
Since its introduction about a cancer, and projections suggest that by 2040, the decade ago, the number of EWAS studies on number of new cases could reach three million various common diseases has grown significantly.
annually, with deaths approaching one million per Similar (GWAS).
EWAS has been widely used to identify Genome-Wide Association Studies In line with this increasing trend, early biomarkers in large populations and to elucidate detection and accurate diagnosis are essential to the molecular mechanisms underlying disease reduce breast cancer mortality.
One promising approach is the utilization of biomarkers, which However, studies specifically investigating enable more precise diagnosis and therapy based EWAS-based epigenetic biomarkers for breast on the molecular characteristics of each patient.
cancer in the Indonesian population remain limited.
Currently, several biomarkers such as estrogen and research in this area is still in its early stages.
receptor (ER), progesterone receptor (PR), and This highlights the need for further investigation to HER2 are widely used in clinical practice.
However, understand population-specific epigenetic patterns new biomarkers are still needed to better capture and to support the development of precision the biological heterogeneity of breast cancer.
medicine strategies in Indonesia.
The Epigenome-Wide Association Study Although this review focuses on studies (EWAS) plays an important role in analyzing the published between 2015 and 2025 to reflect recent impact of genetic and environmental factors on advances, earlier foundational research on DNA epigenetic regulation that contributes to breast cancer risk.
Epigenetics itself is a branch of established the biological relevance of epigenetic genetics that studies changes in gene expression alterations in carcinogenesis.
without altering the DNA sequence, such as DNA Therefore, this review aims to discuss the role methylation and histone modification.
In recent of the Epigenome-Wide Association Study (EWAS) years, epigenomic variation has emerged as a new in identifying epigenetic biomarkers of breast research direction, with DNA methylation at CpG cancer and to explore the potential of this approach BIOMEDIKA.
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in advancing more precise diagnosis and therapy in studies were included to provide a comprehensive the future.
overview of the available evidence.
All METHODS This study employed a narrative review descriptively to identify general research trends, approach to examine the role of the Epigenome- differences in findings among studies, and the Wide Association Study (EWAS) in identifying epigenetic biomarkers for breast cancer.
Relevant biomarkers for breast cancer.
scientific literature was collected through searches Review on PubMed.
ScienceDirect, and Google Scholar Epigenetic Biomarkers EWAS Approach The review included original research articles In cancer research, a biomarker is defined as and systematic reviews published between 2015 a measurable biological molecule .
ound in blood, and 2025, focusing on studies that investigated serum, or tissu.
that reflects the presence of a DNA methylation patterns.
CpG site analyses, and pathological process, such as the transformation of candidate genes associated with breast cancer.
normal cells into malignant ones.
Unlike clinical The keywords used in the search were screening methods such as mammography.
MRI.
AuEpigenome-Wide Association Study (EWAS)Ay.
PET, and biopsy, which are effective only in Aubreast cancerAy.
AuDNA methylationAy.
Auepigenetic biomarkerAy.
Articles were selected biomarkers can identify molecular alterations that based on their relevance to the topic, alignment occur at the earliest stages of breast cancer.
This with the study objectives, and the availability of has driven researchers to search for biological Additional EWAS-based DNA markers capable of distinguishing normal from cancerous tissues, revealing tumor activity even methylation in breast cancer, full-text availability, before a detectable mass forms, and potentially and methodological clarity.
Publications not directly serving as tools for early diagnosis, prognosis, and related to breast cancer or not employing an EWAS therapeutic monitoring.
approach were excluded from the review.
Given Biomarkers are generally classified into three the relatively limited number of EWAS studies major categories: protein biomarkers, gene-based specifically focusing on breast cancer, relevant biomarkers, and metabolite or small-molecule 5 With the advancement of research.
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the focus of biomarker studies has expanded as DNA methylation in the promoter regions of beyond conventional protein and gene molecules tumor suppressor genes, have been shown to to include the epigenetic level, which reflects represent one of the earliest mechanisms in the changes in gene regulation without alterations in process of carcinogenesis, making them ideal the DNA sequence.
Epigenetic modifications, such candidates for early cancer detection.
Figure 1.
Effects of DNA Methylation on Gene Expression in Cancer Several genes, such as GSTP1 and MGMT, patient serum shows both diagnostic and have been clinically tested as promising prognostic potential in distinguishing different epigenetic biomarkers in various cancers.
breast cancer subtypes.
Hypermethylation of GSTP1 serves as a strong In addition to tissue-based approaches, diagnostic marker for prostate cancer, whereas epigenetic biomarkers can also be detected MGMT non-invasively through blood or other body therapeutic response to alkylating agents in This approach, known as liquid biopsy, 7 Meanwhile, several genes such enables the detection of cell-free DNA .
fDNA) as BRCA1.
RASSF1A.
CDH1, and APC have been reported to undergo hypermethylation in the epigenetic signatures of tumors.
Non-invasive RNA cfDNA, considered potential candidates for specific microRNAs, and plasma proteins are now diagnostic markers.
8 Besides acting as markers recognized as potential tools to replace or in tumor initiation.
DNA methylation patterns have also been shown to reflect tumor screening, as they are fast, safe, and capable progression and treatment response in breast of identifying molecular changes long before For example, hypermethylation of the clinical symptoms appear.
TGFBI gene is associated with resistance to Along with these developments, various trastuzumab therapy in the HER2-positive DNA methylation analysis methods such as subtype, while methylation of the ESR1 gene in MethyLight BIOMEDIKA.
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MS-HRM.
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pyrosequencing have been widely used to Similarly.
Sahoo and Sundararajan .
identify epigenetic alterations in specific genes.
stated that microarray-based EWAS is an However, advances in microarray and next- generation sequencing (NGS) technologies now approach for detecting CpG sites that serve as make it possible to analyze DNA methylation diagnostic and prognostic markers.
12 With its comprehensively across the entire genome.
ability to map DNA methylation variations Since the introduction of the EPIC BeadChip comprehensively and link them to disease phenotypes.
EWAS has become one of the key sequencing, the Epigenome-Wide Association drivers in the paradigm shift from genetic Study (EWAS) approach has become a popular research toward epigenetic approaches in the method for discovering epigenetic biomarkers discovery of clinical biomarkers.
genome-scale environmental exposures.
7,10
cost-effective.
Specifically, wide-ranging Epigenome-Wide Association Study (EWAS) is a genome-scale A comprehensive review by Wei et al.
titled AuTen Years of EWAS,Ay explains that the relationship between epigenetic variations.
Epigenome-Wide Association Study (EWAS) approach has undergone rapid development phenotypes or diseases.
EWAS was developed over the past decade and is now recognized as because genetic and environmental factors alone cannot fully explain the variation in 4 The study by Campagna et al.
disease risk, making the epigenome a crucial (Clinical Epigenetics, 2.
also emphasized biological link between the two.
This approach that advancements in Illumina microarray works by comparing DNA methylation levels across the genome between two or more bioinformatics pipelines such as Minfi and groups .
or example, patients and control.
to ChAMP have established EWAS as a standard identify CpG sites that exhibit differential methylation levels.
4,11
EPIC)
reproducible genome-wide DNA methylation analysis across cohorts.
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methylation signal intensity using microarray platforms such as Illumina 450K or EPIC.
The resulting data are then analyzed to quantify the methylation level at each CpG site, expressed diseases from diverse populations and is as a beta () value, which represents the ratio publicly accessible through a web portal and the of methylated signal intensity to total signal R package ewascatalog.
The catalog serves as A value O 0.
25 indicates an a primary repository for researchers to review, unmethylated site, values between 0.
25Ae0.
analyze, and validate EWAS results in a more are considered hemimethylated, and Ou 0.
comprehensive and standardized manner.
indicates a fully methylated site.
These data are Application of EWAS in Breast Cancer further analyzed to identify CpG positions or Biomarker Discovery This DNA regions showing significant differences, which With the rapid advancement of EWAS are then biologically interpreted through gene technologies and the increasing availability of function or molecular pathway analysis.
Today, public databases, this approach has been EWAS is widely applied to identify diagnostic widely applied to identify DNA methylation and prognostic biomarkers and to monitor therapeutic responses based on epigenetic Numerous studies have demonstrated how this 4,11 comprehensive epigenomic analysis contributes With the increasing number of EWAS- to a deeper understanding of the molecular based studies, a centralized data resource mechanisms of cancer, ranging from early risk known as The EWAS Catalog has now been assessment to prognosis and non-invasive established to integrate and compare findings BIOMEDIKA.
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Table 1.
Summary of EWAS studies investigating epigenetic biomarkers in breast cancer Author.
Study Title Key Findings (Yea.
Epigenome-Wide Association Global hypomethylation found in gene body and 3AUTR van Veldhoven Study reveals decreased average regions.
higher methylation associated with reduced K et al.
DNA methylation levels years breast cancer risk, suggesting potential as an early before breast cancer diagnosis blood-based biomarker.
EWAS revealed global hypomethylation and lifestyleJohansson A & Epigenome-wide association associated CpGsAiAHRR.
F2RL3 .
HIF3A.
Flanagan JM studies for breast cancer risk and PHGDH (BMI).
ER-.
E-cadherin .
Aiwith .
risk factors accelerated epigenetic aging increasing postmenopausal breast cancer risk.
Epigenome-Wide Association EWAS identified 694 CpGs associated with ELEE.
a 31Study for lifetime estrogen CpG Methylation Index predicted breast cancer risk.
Johansson A et exposure identifies an epigenetic with higher scores increasing risk .
op quartile OR = .
signature associated with breast Key CpGs included CTNNA2.
GRB10.
RPH3AL, cancer risk and TINCR.
7,315 CpGs identified in normal breast tissue .
DNA Methylation and Breast Bonferroni-adjuste.
key genes LHX2.
TFAP2B.
Ennour-Idrissi Cancer Risk: An Epigenome-Wide JAKMIP1.
SEPT9.
POM121L2.
KCNQ1.
CLEC4C.
K et al.
Study of Normal Breast Tissue and Pathways involved fatty acid metabolism and Wnt/Blood catenin signaling.
blood replication supported potential pre-diagnostic biomarkers.
EWAS revealed CpGs associated with age.
BMI, and Wei S.
Tao J, hormone therapy use, including >800 age-related, 694 Xu J.
Chen X, estrogen-exposure, and 527 hormone therapyAelinked Ten Years of EWAS Wang Z.
Zhang sites (ARHGEF.
Hypermethylation at cg46801642 and N, dkk.
hypomethylation at cg27091787 (HYAL.
were both associated with elevated breast cancer risk.
Deep Survival EWAS identified the F120 CpG island A Deep Survival EWAS approach cluster .
linked to time-to-diagnosis.
estimating risk profile based on methylation correlated with earlier onset.
GSEA showed Massi MC et al.
pre-diagnostic DNA methylation:
enrichment in cancer-related.
PI3K/Akt/mTOR, and .
An application to breast cancer calcium signaling pathways.
AI-based model time to diagnosis outperformed conventional EWAS in detecting biologically relevant pathways.
DNA methylation patterns Fifteen significant CpGs were linked to patient survival, associated with breast cancer Kim et al.
differing by molecular subtype and menopausal status.
prognosis that are specific to .
Key CpGs (DVL1.
SH3PXD2A.
ESYT.
were enriched in tumor subtype and menopausal Wnt and insulin signaling pathways.
Notch.
SUMOylation, and ESRSignificant subtype differences in promoter epimutation Mediated Signalling Are the Main scores were observed.
ER-positive tumors exhibited Molecular Pathways Showing hypomethylation in estrogen signaling pathways.
Corsaro L et al.
Significantly Different Epimutation whereas ER-negative tumors showed hypermethylation .
Scores between Expressing or Not in Notch and SUMOylation pathways, reflecting distinct Oestrogen Receptor Breast Cancer epigenetic regulation involving estrogen signaling and in Three Public EWAS Datasets EMT.
100 CpGs identified across common diseases, including Blood-based epigenome-wide breast cancer.
Hypomethylation at cg06072257 analyses of 19 common disease Hillary RF et al.
(UBIAD.
and cg06123699 (TPRG.
associated with states: A longitudinal, population.
breast cancer risk.
pathways involved vitamin K based linked cohort study of metabolism and estrogen regulation.
Blood methylation 18,413 Scottish individuals showed potential as a non-invasive biomarker.
Cervical and buccal samples showed 21,614 and 585 significant CpGs (FDR < 0.
, while blood showed Systems epigenetic approach Methylation-based classifiers (WID-buccal.
WIDHerzog CMS et towards non-invasive breast cervical.
WID-bloo.
achieved AUCs of 0.
75, 0.
66, and .
cancer detection 51, respectively, with buccal methylation most closely reflecting breast tissue (AUC > 0.
, highlighting its potential for non-invasive detection.
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Based on the findings summarized in Table 1, it can be observed that the Epigenome-Wide predominantly occurring within gene bodies and Association Study (EWAS) approach has made a 3AUTRs, indicates a broad epigenetic deregulation that may reflect genomic instability during the early dynamics of DNA methylation associated with the stages of carcinogenesis.
Interestingly, higher levels risk, progression, and potential early detection of of methylation were associated with a reduced risk breast cancer.
In general, these studies reveal that of cancer (OR = 0.
p = 0.
, suggesting that alterations in DNA methylation patterns do not occur this hypomethylation pattern has potential as an solely at advanced stages of cancer but can also be early risk biomarker.
This finding marked a shift in research focus from single-gene analysis toward manifestations, even among individuals who appear comprehensive epigenome-wide investigations.
These findings were subsequently expanded by to be healthy.
Furthermore, the studies included in Table 1 vary considerably in their objectives, sample Johansson and Flanagan in 2017, who confirmed sources, and analytical approaches.
While some consistently observed across six large prospective investigations focus on identifying risk-associated They highlighted that these epigenetic methylation signatures detectable in peripheral alterations are strongly influenced by lifestyle and blood prior to diagnosis, others emphasize tumor- environmental factors such as smoking, obesity, and specific alterations related to prognosis, molecular alcohol consumption, with specific methylation subtypes, or treatment response.
This diversity markers including AHRR .
F2RL3, reflects the multifaceted role of EWAS in breast HIF3A, and PHGDH.
In addition, they introduced the cancer research but also complicates efforts to establish universally applicable biomarkers.
demonstrating that an accelerated Auepigenetic One of the pioneering studies conducted by van agingAy process is associated with an increased risk Veldhoven et al.
in 2015 represents an important of cancer, particularly among postmenopausal milestone in breast cancer epigenetic research, as it This study reinforced the notion that DNA demonstrated that the average level of DNA methylation profiles also serve as cumulative methylation in peripheral blood was lower in women reflections of environmental exposures and an individualAos biological status.
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The observed global BIOMEDIKA.
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Following this line of research.
Johansson et al.
explored the relationship between lifetime estrogen exposure (ELEE) and breast cancer risk breast cancer and offering potential utility as early screening biomarkers.
In line with these findings.
Wei et al.
through their systematic review AuTen Years of analyzing more than 694 significant CpG sites, they EWAS,Ay highlighted more than 800 age-associated developed a Methylation Index (MI) based on 31 CpG sites and 694 CpG sites influenced by estrogen CpGs that was able to predict breast cancer risk with exposure, including ARHGEF4 .
and 4Ae1.
5-fold increase.
Key contributing genes HYAL2 .
This cross-study analysis included CTNNA2.
GRB10.
RPH3AL, and TINCR, emphasized that aging and hormonal exposure are which are known to be involved in the regulation of two major biological factors that leave measurable cell growth and differentiation.
These findings epigenetic imprints, thereby establishing epigenetic further support the concept that blood DNA
biomarkers as one of the most promising approaches methylation profiles can serve as an Auepigenetic for early detection and risk prediction of breast
recordAy of lifelong hormonal exposure, rather than multi-cohort
EWAS
merely representing a consequence of disease.
A more advanced computational approach was A study focusing on normal breast tissue was implemented by Massi et al.
, who introduced conducted by Ennour-Idrissi et al.
, aiming to the Deep Survival EWAS model to predict time-to- identify pre-neoplastic methylation changes.
They diagnosis based on pre-diagnostic blood DNA reported 7,315 significant CpG sites, of which 52 methylation profiles.
By applying survival neural remained significant after Bonferroni correction.
networks and SHAP analysis, they identified a CpG Genes such as LHX2.
TFAP2B.
JAKMIP1.
SEPT9, and KCNQ1 were implicated in fatty acid metabolism and methylation levels that correlated with earlier Wnt/-catenin signaling pathways, which represent diagnosis and were functionally linked to the two key mechanisms involved in cellular proliferation PI3K/Akt/mTOR and calcium signaling pathways.
and differentiation.
These results strengthen the This study opened a new direction in the application hypothesis that epigenetic alterations may precede of artificial intelligence and machine learning for the neoplastic transformation, suggesting that even interpretation of complex methylation data, while histologically normal tissue may harbor Auearly also demonstrating the predictive potential of epigenetic marksAy reflecting a predisposition to epigenetic biomarkers for disease onset timing.
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From a prognostic perspective.
Kim et al.
identified 15 significant CpG sites in tumor suggesting that the EWAS approach can facilitate more precise subtype characterization.
In a large population-based study.
Hillary et al.
tissues that were associated with patient survival, .
analyzed blood methylation profiles from postmenopausal women.
Most of these CpG sites, more than 18,000 individuals and identified two such as those located in DVL1.
ESYT2, and novel sites, cg06072257 (UBIAD.
and cg06123699 SH3PXD2A, showed that higher methylation levels (TPRG.
, which were associated with a history of were correlated with lower risks of recurrence and breast cancer.
The UBIAD1 gene is involved in mortality, indicating a more favorable prognosis.
vitamin K metabolism, whereas TPRG1 is regulated Conversely.
CpG sites within MZF1 and ELAC1 by estrogen signaling.
both play roles in cellular exhibited the opposite trend (HR > .
, where hypermethylation was associated with an increased suggest that blood DNA methylation alterations may risk of disease progression, reflecting a poorer reflect breast cancer risk at a systemic level rather These findings highlight that DNA than being limited to tumor tissue, thereby offering methylation patterns can serve as prognostic potential as non-invasive risk biomarkers for early biomarkers, as methylation levels at specific sites Luminal Meanwhile.
These Furthermore, the study conducted by Herzog et have the potential to predict clinical outcomes and therapeutic responses in breast cancer patients.
represents the most recent advancement in this field by evaluating the potential of non- conducted by Corsaro et al.
to distinguish the invasive detection through EWAS using cervical, epigenetic profiles between breast cancer subtypes, buccal, and blood samples.
Thousands of significant namely ER-positive and ER-negative.
The ER- CpG positive subtype exhibited hypomethylation in ESR- classification performance observed in the buccal mediated signaling pathways, whereas the ER- WID-index (AUC 0.
75Ae0.
These findings confirm negative subtype displayed hypermethylation in that peripheral epithelial tissues, such as buccal Notch and SUMOylation pathways, which are mucosa, can reflect systemic epigenetic alterations, associated with cellular differentiation and drug These findings reinforce the notion that development of non-invasive screening tests for the the molecular heterogeneity of breast cancer is early detection of breast cancer.
largely reflected in its DNA methylation patterns.
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Overall, these studies illustrate the evolution of This perspective is further supported by Sahoo population-based risk and Sundararajan .
, who highlighted that analyses toward predictive modeling and clinical EWAS has now evolved into an essential tool for diagnosis, prognosis, and therapeutic monitoring.
identification of specific methylation signatures Methylation profiles of genes such as BRCA1 and SEPT9 demonstrate clinical potential for non- environmental factors but also facilitates the invasive detection and monitoring of treatment importance of standardizing analytical workflows, invasive detection.
With the expanding integration of integrating multi-omics data, and applying machine multi-omics learning approaches to enhance the accuracy and EWAS applications EWAS technologies, the EWAS approach is increasingly Furthermore, reproducibility of EWAS findings.
recognized as a key pillar in the pursuit of precise Overall, despite the growing number of EWAS epigenetic biomarkers for breast cancer, offering studies investigating breast cancer, several gaps great potential for the development of non-invasive remain in the current body of evidence.
Findings screening tests for early detection.
across studies are often heterogeneous due to These anticipated clinical implications are differences in study populations, sample sources consistent with the perspective presented by Skinner .
lood versus tissu.
, analytical platforms, and .
, who emphasized that EWAS findings hold statistical approaches.
While some studies report great potential to transform medical practice from a global hypomethylation associated with cancer risk, reactive approach toward preventive precision DNA patterns linked to prognosis or molecular subtypes.
EWAS
risk-indicating Moreover, many studies rely on cross-sectional site-specific designs and relatively small sample sizes, limiting personalized intervention before the onset of clinical In the context of breast cancer, this inconsistencies highlight the need for large-scale opens opportunities for utilizing specific methylation signatures to identify high-risk groups and to establish more targeted strategies for prevention establish robust and clinically applicable epigenetic and disease control.
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Challenges and Limitations of EWAS Research addition, the lack of pre-analytical standardization.
Although EWAS has opened vast opportunities degradation of genetic material, and insufficient for the discovery of epigenetic biomarkers, several inter-laboratory clinical validation remain major challenges still limit its broad application.
Most barriers to the successful translation of EWAS findings into medical practice.
25,26
EWAS
cross-sectional designs, making it difficult to distinguish whether Overall, the future success of EWAS will depend DNA methylation changes are a cause or a on the integration of multi-omics data, cross- population clinical validation, and the harmonization Moreover, cellular heterogeneity within tissues such of international protocols to ensure that the resulting as blood often results in methylation signals that reflect changes in cell composition rather than true implemented and feasibly applied in routine clinical epigenetic alterations.
In addition, the effect sizes of methylation changes are generally small and highly CONCLUSION .
everse influenced by genetic, environmental, and technical batch effects.
EWAS findings should be interpreted carefully.
From a methodological perspective, it is also necessary to standardize analytical pipelines and increase sample sizes to improve the accuracy and reliability of EWAS results.
Tissue heterogeneity, batch effects, and the lack of cross-population replication remain major challenges.
Furthermore, integration of multi-omics data and longitudinal analyses is needed to better understand the temporal dynamics of DNA methylation while minimizing bias arising from environmental factors.
From a technical standpoint.
EWAS based on cell-free DNA still faces several challenges due to the limited quantity of DNA, high fragmentation, and contamination that reduce detection sensitivity.
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Februari 2026, 32 - 45 Advances in microarray technology and the algorithms have established EWAS as a primary method for exploring epigenetic biomarkers.
This approach deepens the understanding of interactions factors, and also opens opportunities for the precision medicine.
The (EWAS) Epigenome-Wide Association Study contribution to understanding the epigenetic basis of Through genome-scale DNA methylation analysis.
EWAS has been able to identify epigenetic patterns associated with risk, prognosis, and the potential for non-invasive detection of the Findings from various studies discussed also THE ROLE OF EPIGENOME-WIDE ASSOCIATION STUDIES A (Karuni.
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FUNDING
This research did not receive any external funding REFERENCES