DNA methylation profile of inflammatory breast cancer and its impact on prognosis and outcome - Faldoni, Flavia Lima Costa [UNESP]; Bizinelli, Daniela; Souza, Cristiano Pádua; Santana, Iara Viana Vidigal; Marques, Márcia Maria Chiquitelli; Rainho, Claudia Aparecida [UNESP]; Marchi, Fabio Albuquerque; Rogatto, Silvia Regina (Springer Nature, 2024)
Background: Inflammatory breast cancer (IBC) is a rare disease characterized by rapid progression, early metastasis, and a high mortality rate. Methods: Genome-wide DNA methylation analysis (EPIC BeadChip platform, Illumina) and somatic gene variants (105 cancer-related genes) were performed in 24 IBCs selected from a cohort of 140 cases. Results: We identified 46,908 DMPs (differentially methylated positions) (66% hypomethylated); CpG islands were predominantly hypermethylated (39.9%). Unsupervised clustering analysis revealed three clusters of DMPs characterized by an enrichment of specific gene mutations and hormone receptor status. The comparison among DNA methylation findings and external datasets (TCGA-BRCA stages III-IV) resulted in 385 shared DMPs mapped in 333 genes (264 hypermethylated). 151 DMPs were associated with 110 genes previously detected as differentially expressed in IBC (GSE45581), and 68 DMPs were negatively correlated with gene expression. We also identified 4369 DMRs (differentially methylated regions) mapped on known genes (2392 hypomethylated). BCAT1, CXCL12, and TBX15 loci were selected and evaluated by bisulfite pyrosequencing in 31 IBC samples. BCAT1 and TBX15 had higher methylation levels in triple-negative compared to non-triple-negative, while CXCL12 had lower methylation levels in triple-negative than non-triple-negative IBC cases. TBX15 methylation level was associated with obesity. Conclusions: Our findings revealed a heterogeneous DNA methylation profile with potentially functional DMPs and DMRs. The DNA methylation data provided valuable insights for prognostic stratification and therapy selection to improve patient outcomes. Graphical Abstract: (Figure presented.)
Keywords: Biomarker; Differentially methylated sites; DNA methylation, epigenetic regulation; Driver mutations; Gene expression