METHODS: Various techniques including qRT-PCR, western blotting, and immunohistochemistry assays were utilized to examine gene expression patterns. Functional assays such as wound-healing assay, transwell invasion assay, 5-Ethynyl-2'-deoxyuridine assay, and metabolic assays were conducted to assess the impact of CEP55 on the behaviors of TNBC cells. CD163-positive macrophages were quantified by flow cytometry. The chromatin immunoprecipitation assay and dual-luciferase reporter assay were performed to assess the association of SPI1 with CEP55. A xenograft mouse model experiment was used to analyze the impact of SPI1 on tumor development in vivo.
RESULTS: CEP55 and SPI1 expression levels were significantly upregulated in TNBC tissues and cells. The depletion of CEP55 led to decreased TNBC cell migration, invasion, proliferation, glucose metabolism, and M2 macrophage polarization, indicating its crucial role in promoting TNBC progression. Moreover, SPI1 transcriptionally activated CEP55 in TNBC cells, and its overexpression was associated with accelerated tumor growth in vivo. Further, CEP55 overexpression relieved SPI1 silencing-induced inhibitory effects on TNBC cell migration, invasion, proliferation, glucose metabolism, and M2 macrophage polarization.
CONCLUSION: SPI1-mediated transcriptional activation of CEP55 plays a key role in enhancing TNBC cell migration, invasion, proliferation, glucose metabolism, and M2 macrophage polarization. These insights provide valuable information for potential targeted therapies to combat TNBC progression by modulating the SPI1-CEP55 axis.
METHODS: Studying breast cancer, we established genome-scale DNA methylation profiles of prospectively collected buffy coat samples (n = 702) from a case-control study nested within the EPIC-Heidelberg cohort using reduced representation bisulphite sequencing (RRBS).
RESULTS: We observed cancer-specific DNA methylation events in buffy coat samples. Increased DNA methylation in genomic regions associated with SURF6 and REXO1/CTB31O20.3 was linked to the length of time to diagnosis in the prospectively collected buffy coat DNA from individuals who subsequently developed breast cancer. Using machine learning methods, we piloted a DNA methylation-based classifier that predicted case-control status in a held-out validation set with 76.5% accuracy, in some cases up to 15 years before clinical diagnosis of the disease.
CONCLUSIONS: Taken together, our findings suggest a model of gradual accumulation of cancer-associated DNA methylation patterns in peripheral blood, which may be detected long before clinical manifestation of cancer. Such changes may provide useful markers for risk stratification and, ultimately, personalized cancer prevention.