Cancer Genetics and Epigenetics 2024, Vol.12, No.2, 88-96 http://medscipublisher.com/index.php/cge 90 specific hypermethylated genes that distinguish between cancerous and normal tissues, suggesting their utility as biomarkers for clinical diagnosis and targeted treatments (Radpour et ala., 2019). 3.2 Epigenetic changes and tumorigenesis Epigenetic changes, particularly DNA methylation, play a crucial role in the onset and progression of breast cancer. Abnormal DNA methylation is implicated in tumorigenesis by regulating key processes such as cell proliferation, apoptosis, differentiation, and cell cycle control (Pan et al., 2018). Studies have shown that global DNA hypomethylation and higher epigenetic age are associated with an increased risk of breast cancer, indicating that these epigenetic markers could serve as short-term predictors of breast cancer risk (Ennour-Idrissi et al., 2020). Furthermore, the identification of differentially methylated genes across various cancers has provided insights into cancer-specific methylation patterns, which could be used to develop individualized treatment strategies (Zhang et al., 2015). 3.3 Biomarker discovery and validation The discovery and validation of DNA methylation biomarkers for breast cancer have been a focal point of recent research. Whole-blood DNA methylation markers have been suggested as potential biomarkers for early detection, although their diagnostic value remains modest, with only a few markers showing significant sensitivity and specificity (Guan et al., 2018). A systematic review and meta-analysis have identified common DNA methylation signatures across different breast cancer subtypes, reflecting deregulation of the immune system and alterations to the cell cycle, which could support the identification of novel biomarkers and therapeutic targets (Trasierras-Fresco et al., 2023). Additionally, the automatic detection of circulating cell-free methylated DNA patterns, such as those of CCDC181, GCM2, and ITPRIPL1, has shown promise in improving the accuracy of early breast cancer detection and monitoring surgical treatment responses (Wang et al., 2021). 4 Clinical Applications of DNA Methylation in Early Detection 4.1 Biomarkers for early detection DNA methylation-based biomarkers have shown significant promise in the early detection of breast cancer. Aberrant DNA methylation is an early event in cancer development and can be detected in circulating cell-free DNA (cfDNA), making it a valuable biomarker for cancer detection and prognosis (Cheuk et al., 2017; Constâncio et al., 2020). Studies have identified specific methylation markers, such as RASSF1A and HOXA10, which show significant differences in methylation between breast cancer patients and healthy controls, enhancing the positive predictive value for breast cancer detection. Additionally, the use of multi-gene panels rather than single-gene methylation status has been suggested to increase the sensitivity and specificity of breast cancer screening. 4.2 Non-Invasive detection methods Non-invasive methods for detecting DNA methylation involve analyzing cfDNA from blood samples, which offers a less invasive alternative to traditional biopsy methods. Liquid biopsies, particularly the analysis of cfDNA, have emerged as a promising approach for the non-invasive diagnosis of early-stage cancers (Figure 1) (Luo et al., 2021). Whole-genome bisulfite sequencing and methylation-specific PCR are among the techniques used to detect methylation markers in cfDNA, providing a stable and quantifiable means of early cancer detection (Constâncio et al., 2020; Liu et al., 2021). The combination of liquid biopsy with traditional diagnostic imaging has been shown to improve diagnostic accuracy and reduce false-positive rates, thereby avoiding unnecessary biopsies (Roy and Tiirikainen, 2020; Zhang et al., 2023). The CCGA study demonstrated the clinical potential of DNA methylation analysis by using cfDNA methylation analysis for early multi-cancer detection. By examining fragment-level methylation patterns, the test is able to distinguish cancer from non-cancer based on methylation signatures unique to cancer cells. For non-cancer participants, cfDNA was derived from cells throughout the body, including leukocytes, and their methylation markers reflected the characteristics of blast cells. As shown in the example of chromosome 10 region in the figure, most of the cfDNA fragments appear turquoise, indicating that they are predominantly unmethylated. In lung cancer patients, plasma contains a mixture of methylated (burgundy) and unmethylated (turquoise) cfDNA
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