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Bermejo, B.

Publications and source records attributed to Bermejo, B..

2 recordsLinked to original sources

A breast tissue-specific epigenetic clock provides accurate chronological age predictions and reveals de-correlation of age and DNA methylation in tumor-adjacent and tumor samples

Epigenetic clocks have been widely used to estimate biological age across various tissues, but their accuracy in breast tissue remains suboptimal. Pan-tissue models such as Horvaths and Hannums clocks, perform poorly in predicting chronological age in breast tissue, underscoring the need for a tissue-specific approach. In this study, we introduce a Breast Tissue-specific Epigenetic Clock (BTEC), developed using DNA methylation data from 553 healthy breast tissue samples across seven different studies. BTEC significantly outperformed pan-tissue clocks, demonstrating superior correlation with chronological age (r=0.88) and lower prediction errors (MAE=3.27 years) without requiring for dataset-specific regressions adjustments. BTECs chronological age predictions for tumor-adjacent samples showed distortions, with an average deviation of -1.76 years, which was even more pronounced in tumor samples, where the average difference between predicted and chronological age was -12.29 years. When analyzed by molecular subtype, the distortion was greater in the more aggressive HER2+ and TNBC tumors compared to HR+ tumors. The probes used by BTEC were associated with known oncogenes, genes involved in estrogen metabolism, cadherin binding and fibroblast growth factor binding. Despite the general rejuvenation observed in tumor tissue compared to normal breast, the correlation between BTECs predictions and cancer-related survival indicated that TNBC tumors with increased epigenetic ages had significant lower survival.

cancer biology↗

The GATA3 X308_Splice breast cancer mutation is a hormone context-dependent oncogenic driver

As the catalogue of oncogenic driver mutations is expanding, it is becoming clear that alterations in a given gene should not be lumped into one single class, since they might have different functions. The transcription factor GATA3 is a paradigm of this. Here, we address the functions of the most common GATA3 mutation (X308_Splice) which generates a neoprotein that we designate as neoGATA3, associated with good patient prognosis. Based on extensive analyses of molecular and clinical data from approximately 3000 breast cancer patients, supported by mechanistic studies in vitro, we show that neoGATA3 interferes with the transcriptional programs controlled by estrogen and progesterone receptors, without fully abrogating them. This has opposite outputs in the pre- or post-menopausal hormonal context, having pro- or anti-proliferative effects, respectively. NeoGATA3 is an example of a context- and stage-dependent driver mutation. Our data call for functional analyses of putative cancer drivers to guide clinical application.

cancer biology↗