AUTHOR=Liu Xingyu , Chen Jiarui , Li Jiali , Zeng Zihang , Jiang Xueping , Gao Yanping , Huang Zhengrong , Wu Qiuji , Gong Yan , Xie Conghua 

TITLE=Integrated analysis reveals common DNA methylation patterns of alcohol-associated cancers: A pan-cancer analysis

JOURNAL=Frontiers in Genetics

VOLUME=14

YEAR=2023

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1032683

DOI=10.3389/fgene.2023.1032683

ISSN=1664-8021

ABSTRACT=<p><bold>Background:</bold> The role of alcohol in carcinogenesis has received increasing attention in recent years. Evidence shows its impacts on various aspects, including epigenetics alteration. The DNA methylation patterns underlying alcohol-associated cancers are not fully understood.</p><p><bold>Methods:</bold> We investigated the aberrant DNA methylation patterns in four alcohol-associated cancers based on the Illumina HumanMethylation450 BeadChip. Pearson coefficient correlations were identified between differential methylated CpG probes and annotated genes. Transcriptional factor motifs were enriched and clustered using MEME Suite, and a regulatory network was constructed.</p><p><bold>Results:</bold> In each cancer, differential methylated probes (DMPs) were identified, and 172 hypermethylated and 21 hypomethylated pan-cancer DMPs (PDMPs) were examined further. Annotated genes significantly regulated by PDMPs were investigated and enriched in transcriptional misregulation in cancers. The CpG island <italic>chr19:58220189–58220517</italic> was hypermethylated in all four cancers and silenced in the transcription factor <italic>ZNF154</italic>. Various biological effects were exerted by 33 hypermethylated and seven hypomethylated transcriptional factor motifs grouped into five clusters. Eleven pan-cancer DMPs were identified to be associated with clinical outcomes in the four alcohol-associated cancers, which might provide a potential point of view for clinical outcome prediction.</p><p><bold>Conclusion:</bold> This study provides an integrated insight into DNA methylation patterns in alcohol-associated cancers and reveals the corresponding features, influences, and potential mechanisms.</p>