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Cancer-associated differentially methylated regions (DMRs) are promising biomarkers for cancer diagnosis, prognosis, and therapeutic response, but their biological significance and potential applications remain to be systematically explored across datasets. To support this, we released MethMarkerDB 2.0 (https://methmarkerdb.hzau.edu.cn/v2), which provides several improvements over the previous version: (i) Expands the data resource from 13 to 21 cancer types and from 658 to 1236 whole-genome methylome samples, comprising ∼5.6 million candidate DMRs and 6411 literature-curated biomarker records.(ii) Integrates 450K DNA methylation data from The Cancer Genome Atlas and Epigenome-Wide Association Study Atlas and transcript annotations into the "MethMarker Gene Search" module. These data provide complementary evidence from independent datasets and platforms and allow users to examine CpG-level information for individual DMRs. Additionally, cell-type-resolved reference methylation data allow users to check cellular-background methylation. (iii) Introduces four analysis modules to characterize DMR methylation patterns across age groups and spatial ecotypes, and connect DMRs with transcription factor binding evidence and cancer cell-line drug responses. Moreover, the "Methylation-Cas Designer" supports guide RNA design for methylation-sensitive restriction enzyme-Cas assays and targeted epigenome editing. In summary, MethMarkerDB 2.0 provides expanded resources, diverse functional analyses, and experimental design tools, facilitating the interpretation and application of cancer-associated DMRs.
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Sun et al. (2026) studied this question.
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