Comprehensive Database for Cancer Research: CanASM

Strategic Insights -

Research has demonstrated that allele-specific DNA methylation (ASM) is critical in understanding the complex genetic and epigenetic mechanisms that regulate gene transcription. Recent studies have shown that ASM is enriched in gene enhancer regions and is increased in cancer tissues compared to normal tissues. A new study has developed CanASM, the first comprehensive database specifically designed to identify and annotate ASM in cancer.

Key Takeaways:

  • CanASM is the first database designed to identify and annotate allele-specific DNA methylation in cancer contexts, providing a valuable resource for researchers investigating cancer-associated genetic variations and epigenetic regulation.
  • The database includes 5,003,877 unique SNV-CpG pairs, including 3,056,776 index SNVs, of which 2,634,406 are single-nucleotide polymorphisms (SNPs), and 4,157,508 CpGs.
  • CanASM provides extensive regulatory annotations for ASMs, including associated genes, cis-regulatory elements, and transcription factor binding colocalizations.
  • The database is designed for browsing, querying, analyzing, and downloading, making it a valuable tool for researchers studying cancer-associated genetic variations and epigenetic regulation.
  • The study was conducted by researchers from the Big Data Management and Application, College of Management, Beijing University of Chinese Medicine, and was published in the journal BMC Genomics.
  • The database includes data from 31 cancer types and their matched normal tissue samples.

Statistics:

  • 5,003,877 unique SNV-CpG pairs
  • 3,056,776 index SNVs
  • 2,634,406 single-nucleotide polymorphisms (SNPs)
  • 4,157,508 CpGs
  • 31 cancer types and their matched normal tissue samples

Sources:

  • CanASM: a comprehensive database for genome-wide allele-specific DNA methylation identification and annotation in cancer. BMC Genomics, 2025;26(1):648.
  • Bmc, Campus, 4 Crinan St, London N1 9XW, England. (BioMed Central - www.biomedcentral.com/; BMC Genomics - www.biomedcentral.com/bmcgenomics/)
  • Zeyu Zhao, Big Data Management and Application, College of Management, Beijing University of Chinese Medicine, Beijing, People's Republic of China.
  • Jianmei Zhao, Hongfei Li, Haojie Yu, Hao Lin, Hanqi Chen, Xuecang Li, Di Liu, Yiming Wang, and Guohua Wang.