As the global incidence and mortality rates of cancer continue to rise, it has emerged as a predominant public health concern, the leading cause of death worldwide and a major barrier to increasing life expectancy (1). Esophageal cancer (EC) is a prevalent malignant condition. It ranks among the most frequently diagnosed cancers globally, with the eighth highest incidence rate and the sixth highest mortality rate, with >500,000 new cases diagnosed annually, according to GLOBOCAN (2020) (1). A total of ~80% of new EC cases occur in developing countries, with ~60% of these cases diagnosed in China (2). Despite continuous advancements in diagnostic methods, surgical techniques and adjuvant chemoradiotherapy, most cases of esophageal squamous cell carcinoma (ESCC) are diagnosed at an advanced stage due to a lack of specific symptoms and preventive measures. The overall 5-year survival rate remains low, ranging from 15–50% (3,4). Therefore, effective treatment of EC greatly relies on the identification and prevention of the disease, and implementing screening and early detection methods is crucial for mitigating EC-related fatalities across all demographic groups.

Up to now, the detection of EC has continued to rely on non-molecular methods, which have limited specificity and sensitivity. The use of iodine staining (Lugol's solution) during endoscopic examination remains the gold standard for diagnosing irregularities in the esophageal mucosa (5). However, the widespread use of endoscopic screening in the population faces numerous challenges: Endoscopic targeted biopsy of the upper GI tract is unsuitable for mass screening of the general population due to its invasiveness, limited resources, low patient compliance and high cost, particularly when screening millions of eligible individuals in high-risk areas, such as China (6). Therefore, an urgent need exists to identify a more straightforward, simpler and precise approach for the early detection of EC.

Numerous studies have reported that DNA methylation, as a notable epigenetic alteration, serves a critical role in the progression of EC (7,8). However, traditional DNA methylation detection methods require tissue samples, which limits their clinical application (9). Liquid tumor biopsy, renowned for its procedural simplicity, high sensitivity, specificity and non-invasive or minimally invasive nature, facilitates dynamic monitoring of disease onset, progression and metastasis by detecting relevant tumor markers in the bloodstream, revolutionizing traditional methods of cancer diagnosis and treatment (10). Novel blood biomarkers, such as free DNA, free RNA, metabolites and proteins, have shown potential for the early detection of EC (11–17).

Circulating free (cf)DNA is a type of extracellular DNA commonly found in the plasma or serum of patients with cancer, which has recently attracted the attention of researchers. It is released into the bloodstream by tumor cells (18) and shares the same genetic signatures and epigenetic modifications as tumor cells (19). This suggests that detecting cfDNA in serum could aid in the early diagnosis and treatment of cancer. Numerous studies have supported the potential of cfDNA as a biomarker for the early detection of cancer, making it a valuable analyte for liquid biopsy assessments (20,21), and offering a promising approach for non-invasive cancer detection. DNA methylation is widely recognized as one of the first molecular alterations occurring during cancer progression (22). Additionally, the biological and diagnostic applications of cell-free DNA have gained increasing popularity due to its minimally invasive, convenient and well-accepted characteristics (23). Abnormal methylated cfDNA detected in blood circulation appears to be a useful biomarker for human cancer (24). However, notable gaps remain in this field, with relatively few studies exploring the potential use of cfDNA methylation for the early detection of EC. Therefore, the present study aimed to thoroughly assess the practical use of cfDNA in diagnosing EC, evaluate the feasibility of cfDNA-based methylation as an early biomarker for EC, and provide a comprehensive reference for its clinical application.

As a new diagnostic method for EC, numerous studies have reported that the detection of cfDNA methylation is an accurate and effective diagnostic method (19,20,24). Evidence suggests that cfDNA methylation achieves a sensitivity of 75–92% for early-stage detection, comparable with (and in certain cases exceeding) the 70–85% sensitivity of conventional endoscopic screening (43,44). Whilst endoscopy remains the gold standard for morphological assessment, its sensitivity can vary depending on operator experience and lesion characteristics (44). To date, no comprehensive review has yet been performed to assess the accuracy of the diagnosis, to the best of our knowledge. Therefore, the present systematic review and meta-analysis represents the first comprehensive attempt to evaluate the diagnostic efficacy of cfDNA methylation in EC. The findings indicate that the pooled sensitivity and specificity were 0.83 and 0.98, respectively, indicating high sensitivity and specificity for the differential diagnosis of EC, offering substantial support for clinical diagnosis of this disease.

cfDNA consists of small DNA fragments that are released into the bloodstream following cell death, and these fragments circulate throughout the system (45,46). In healthy individuals, cfDNA predominantly originates from blood-forming cells, though its composition can change under specific physiological or pathological conditions. DNA methylation, a widely investigated epigenetic modification, is characterized by the attachment of methyl groups to the carbon-5 position of cytosine, a process catalyzed by DNA methyltransferase enzymes, predominantly occurring at CpG dinucleotides (47).

An increasing body of evidence indicates that aberrant DNA methylation serves a notable role in the development and progression of cancer, primarily characterized by global hypomethylation, localized hypermethylation across several genomic regions (predominantly at CpG sites), and direct mutations in methylated cytosines (48–50), which positions cfDNA as a potential biomarker for early cancer detection. Concurrently, research has demonstrated that the genetic data encapsulated within cfDNA can accurately identify tumor mutations and gene expression patterns (51). Moreover, the short half-life of cfDNA (ranging from 16 min to 2 h) enables dynamic monitoring of cancer progression (52,53). The methylation pattern of cfDNA is also reflective of the tissue or cell of origin, indicating that detecting aberrant DNA methylation patterns specific to tumors in the plasma of a patient could serve as a method for early cancer diagnosis and prognosis (54). Azad et al (55) reported an association between cfDNA levels in the blood of patients undergoing chemoradiotherapy for EC and tumor progression, metastasis and disease-specific survival rates. Similarly, Egyud et al (56) highlighted the ability of cfDNA to track treatment response and detect relapses in patients with esophageal adenocarcinoma (EAC). These findings align with the conclusions of the present review and provide the foundation for the present research.

Subgroup analyses based on sample size revealed that groups with larger sample sizes demonstrated improved diagnostic performance compared with those with smaller sample sizes. This could be attributed to the fact that elevated cfDNA levels are not exclusive to cancer but can also occur in conditions such as injury, heart attacks, strokes and chronic diseases such as diabetes. Several factors can influence cfDNA levels, including tumor size, location, vascularization and treatments such as surgery, chemotherapy, radiotherapy, and liver and kidney clearance mechanisms (57). Detection sensitivity is also affected by cfDNA molecule quantity, sequencing efficiency and the number of methylation markers. As sample size increases, the influence of these factors is diminished, enhancing diagnostic accuracy. In analyses of DNA methylation assay methods (using techniques such as enzymatic methyl-sequencing), diagnostic accuracy and sensitivity (other, 0.86; 95% CI, 0.82–0.89) and specificity (other, 0.96; 95% CI, 0.94–0.97) were markedly higher than those achieved with MSP methylation assay subgroups. It is recognized that cfDNA methylation identification methods generally fall into two categories: Bisulfite-based and bisulfite-free techniques. Bisulfite treatment involves converting unmethylated cytosines to uracil whilst leaving methylated cytosines unaffected, and the methylation status is determined using PCR amplification and sequencing (58). Bisulfite-free techniques refer to methodologies for detecting DNA methylation that do not rely on bisulfite conversion. Instead, they utilize alternative biochemical strategies to directly distinguish methylated cytosines (5mC/5hmC) from unmodified cytosines. Whole Genome Bisulfite Sequencing (WGBS) is considered the most comprehensive method for assessing DNA methylation, which constructs libraries and performs sequencing following the bisulfite conversion, yielding methylation data for every cytosine, encompassing areas with sparse CpG concentrations and non-CpG locations (CpA, CpT and CpC). Compared with WGBS, although WSP has a lower cost, there are few sites for study, and the design of primers or probes is complex, which may contribute to its lower sensitivity and specificity in certain subgroups (59).

Subgroup analysis by age revealed higher diagnostic accuracy in individuals aged >60 years compared with those aged <60 years. Despite a trend towards cancer incidence in younger individuals, EC remains more prevalent in middle-aged and older populations. The highest incidence peak occurs between 80–84 years of age (60). As age increases, the risk of precancerous lesions, multiple cancers and tumor heterogeneity rises, which may affect cfDNA concentration and methylation levels, influencing diagnostic accuracy.

In addition, EAC and ESCC are two distinct types of EC, with different origins and genetic characteristics (61). Although the present study was unable to perform subgroup analyses on using this variable due to insufficient data, preliminary judgments based on existing literature suggest that there are differences between EAC and ESCC. EAC demonstrates higher sensitivity (85–90%) using markers such as SRY-box transcription factor 17 and hyperplastic polyposis protein 1, whilst ESCC shows moderate sensitivity (75–82%) with markers such as cysteine dioxygenase type 1 or retinoic acid receptor β2 (62). These differences in sensitivity and the specific methylation markers highlight the distinct molecular pathways involved in the development of these two subtypes. However, future studies need to further explore these differences in larger sample sizes to provide more clinically meaningful guidance for subtype-specific applications.

Previous studies have reported that cfDNA methylation has strong diagnostic performance, with an early screening model achieving 74.7% sensitivity and 95.9% specificity (12,30). This outperforms traditional cytology and compares favorably with microRNA (miRNA)-based methods such as the combination of RUNX family transcription factor 3 methylation and carbohydrate antigen-19-9, which offer higher sensitivity in pancreatic cancer but lower specificity compared with cfDNA methylation (63). The superior stability of methylated DNA, compared with the susceptibility of miRNAs to degradation, may explain this advantage. Additionally, emerging technologies, such as machine learning-enhanced cfDNA methylation sequencing, further improve early detection accuracy (AUC, 0.91) and could markedly reduce cancer mortality (64). However, large-scale prospective trials are essential to validate these models across diverse populations and optimize detection thresholds.

Furthermore, despite its high diagnostic accuracy, the cost of cfDNA methylation testing remains a critical barrier to large-scale implementation. Technological advancements and economies of scale may help alleviate this challenge in the future. Furthermore, pre-analytical factors, such as blood collection methods, processing time and storage conditions, can affect test reproducibility. Standardized protocols are, therefore, crucial for clinical adoption. Whilst cfDNA methylation shows strong specificity, integrating it with other biomarkers, such as miRNAs or proteins, may offer a balanced approach for clinical implementation, particularly in resource-limited settings where cost-effectiveness is critical.

Moreover, there are certain limitations of the present study: i) EAC and ESCC were not classified in the study; ii) the impact of different stages of EC on diagnostic results was not taken into account; iii) due to the novelty of several detection techniques, there was no uniform cut-off value, which affected the accuracy of results; vi) the inclusion of English-only literature may have introduced selection bias; v) the findings of the present study were primarily derived from retrospective studies, which may have introduced selection bias and limits generalizability. Only two included studies employed prospective designs, underscoring the need for validation in large, multicenter prospective cohorts; and vi) most of the included studies involved patients from China, USA and UK, which may limit the generalizability of the findings to other populations.

In conclusion, the present study highlights the advancements in utilizing cfDNA for early EC diagnosis, substantiating the feasibility and efficacy of cfDNA methylation sequencing as a diagnostic modality. To the best of our knowledge, the present study is the first meta-analysis evaluating cfDNA methylation for EC diagnosis, demonstrating that the cfDNA methylation detection method has high sensitivity, specificity and AUC values. Moreover, analyzing serum cfDNA is a minimally invasive, rapid and efficient detection method and has potential diagnostic value for EC. However, diagnostic accuracy varies depending on several factors, such as the methylation sequencing methodology, cfDNA yield and cancer stage at detection. Therefore, additional prospective studies are required to validate the precision of cfDNA methylation detection across diverse parameters, facilitating optimization for clinical implementation. Future clinical trials should validate the clinical utility of cfDNA methylation for early EC detection, with potential integration into preventive healthcare paradigms. Such integration may notably improve early detection rates whilst reducing costs and enhancing patient safety.