Inflammatory breast cancer microenvironment repertoire based on DNA methylation data deconvolution reveals actionable targets to enhance the treatment efficacy.

BACKGROUND: Although the clinical signs of inflammatory breast cancer (IBC) resemble acute inflammation, the role played by infiltrating immune and stromal cells in this aggressive disease is uncharted. The tumor microenvironment (TME) presents molecular alterations, such as epimutations, prior to morphological abnormalities. These changes affect the distribution and the intricate communication between the TME components related to cancer prognosis and therapy response. Herein, we explored the global DNA methylation profile of IBC and surrounding tissues to estimate the microenvironment cellular composition and identify epigenetically dysregulated markers. METHODS: We used the HiTIMED algorithm to deconvolve the bulk DNA methylation data of 24 IBC and six surrounding non-tumoral tissues (SNT) (GSE238092) and determine their cellular composition. The prognostic relevance of cell types infiltrating IBC and their relationship with clinicopathological variables were investigated. CD34 (endothelial cell marker) and CD68 (macrophage marker) immunofluorescence staining was evaluated in an independent set of 17 IBC and 16 non-IBC samples. RESULTS: We found lower infiltration of endothelial, stromal, memory B, dendritic, and natural killer cells in IBC than in SNT samples. Higher endothelial cell (EC) and stromal cell content were related to better overall survival. EC proportions positively correlated with memory B and memory CD8+ T infiltration in IBC. Immune and EC markers exhibited distinct DNA methylation profiles between IBC and SNT samples, revealing hypermethylated regions mapped to six genes (CD40, CD34, EMCN, HLA-G, PDPN, and TEK). We identified significantly higher CD34 and CD68 protein expression in IBC compared to non-IBC. CONCLUSIONS: Our findings underscored cell subsets that distinguished patients with better survival and dysregulated markers potentially actionable through combinations of immunotherapy and epigenetic drugs.

DNA methylation profile of inflammatory breast cancer and its impact on prognosis and outcome.

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.