Background: Breast cancer (BC) is a major health concern and better understanding of its biology might improve treatment decisions and patient outcomes. Histone3 Lysine27 tri-methylation (H3K27me3) is a post-translational histone modification frequently associated with altered gene expression. In BC patients, lower H3K27me3 expression has been associated with worse prognosis. We assessed H3K27me3 immunoexpression with digital imaging software assistance, in a cohort of luminal-like BC patients with long-term follow-up time and evaluated its association with clinically relevant endpoints and its clinical usefulness. Methods: H3K27me3 immunoexpression was assessed, by means of digital-imaging system, in archival tissue samples of 160 luminal A/B-like HER2-negative invasive BC, stages I-III. Survival analysis was performed using Kaplan-Meier and Cox regression. Cases were categorized as 'low' or 'high' expression based on cut-off defined by receiver operating characteristic (ROC) curve analysis. Results: The patient cohort showed a median age of 61-years, with a median follow-up time of 11.7 years. Low H3K27me3 expression (below 85% cut-off) was significantly associated with recurrence, both in univariable (HR = 1.99, 95%CI 1.066-3.724) and multivariable analysis when adjusting for grade and age (HR = 1.89, 95%CI 1.004-3.559). A trend for higher risk of death in low H3K27me3 expression BC was observed (p = 0.069), reaching statistical significance in younger patients (p = 0.021). Conclusions: H3K27me3 immunoexpression assessed by digital imaging scoring software is an independent prognosis biomarker in luminal-like BC patients and may assist in more individualized adjuvant treatment decisions, thus potentially reducing recurrences after curative-intent treatment, while sparing unnecessary toxicity.
CITATION STYLE
Fontes-Sousa, M., Lobo, J., Lobo, S., Salta, S., Amorim, M., Lopes, P., … Jerónimo, C. (2020). Digital imaging-assisted quantification of H3K27me3 immunoexpression in luminal A/B-like, HER2-negative, invasive breast cancer predicts patient survival and risk of recurrence. Molecular Medicine, 26(1). https://doi.org/10.1186/s10020-020-0147-5
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