Clinical epigenetics · 2026
Characterization and clinical implications of CpG island methylator phenotypes of resistant tumors.
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Hou Fei, Zhou Xu, Huang Yu-E, Liu Haizhou, Yuan Mengqin, Chen Jiahao, Wang Quan, Jiang Wei
Аннотация
BACKGROUND: Drug resistance, characterized by high heterogeneity and complex mechanisms, poses a significant challenge in cancer treatment. Stratifying resistant tumors into biologically and clinically meaningful subgroups can improve prognostic evaluation and help guide treatment decisions. However, the DNA methylation-based subtypes of resistant tumors have not yet been comprehensively characterized.
RESULTS: DNA methylation profiles from resistant tumors were retrieved from public database including TCGA and GEO. For each tumor type resistant to a specific treatment drug, consensus clustering based on the most variable methylated probes was conducted to identify the DNA methylation subtypes of resistant tumors. For low-grade glioma (LGG) resistant to Temozolomide, consensus clustering of highly variable CpGs identified two subtypes: cancer resistance CpG island methylator phenotype-positive (CR_CIMP+) and -negative (CR_CIMP-). The CR_CIMP- subtype associates with poorer prognosis, reduced drug response, and more advanced histology, exhibiting higher tumor mutation burden and greater activity in drug resistance-related pathways, such as PI3K/AKT/mTOR signaling. CR_CIMP subtypes with distinct clinical or molecular features were also identified in pancreatic adenocarcinoma and bladder urothelial carcinoma resistant to Gemcitabine, as well as in non-small cell lung cancer resistant to anti-PD1/PD-L1 immunotherapy. Based on predicted drug responses, the study screens candidate drugs for each CR_CIMP subtype. Finally, a random forest model is proposed to predict CR_CIMP subtypes in LGG patients resistant to Temozolomide.
CONCLUSIONS: This study uncovers DNA methylation subtypes within resistant tumors, enabling more precise stratification to inform prognosis and therapy selection.
RESULTS: DNA methylation profiles from resistant tumors were retrieved from public database including TCGA and GEO. For each tumor type resistant to a specific treatment drug, consensus clustering based on the most variable methylated probes was conducted to identify the DNA methylation subtypes of resistant tumors. For low-grade glioma (LGG) resistant to Temozolomide, consensus clustering of highly variable CpGs identified two subtypes: cancer resistance CpG island methylator phenotype-positive (CR_CIMP+) and -negative (CR_CIMP-). The CR_CIMP- subtype associates with poorer prognosis, reduced drug response, and more advanced histology, exhibiting higher tumor mutation burden and greater activity in drug resistance-related pathways, such as PI3K/AKT/mTOR signaling. CR_CIMP subtypes with distinct clinical or molecular features were also identified in pancreatic adenocarcinoma and bladder urothelial carcinoma resistant to Gemcitabine, as well as in non-small cell lung cancer resistant to anti-PD1/PD-L1 immunotherapy. Based on predicted drug responses, the study screens candidate drugs for each CR_CIMP subtype. Finally, a random forest model is proposed to predict CR_CIMP subtypes in LGG patients resistant to Temozolomide.
CONCLUSIONS: This study uncovers DNA methylation subtypes within resistant tumors, enabling more precise stratification to inform prognosis and therapy selection.