In 2015, our Chief AI Officer, Matías Butti, co-authored one of the early molecular profiling studies of ductal carcinoma in situ (DCIS) — the pre-invasive form of breast cancer.
At the time, the goal was simple but ambitious: to identify the molecular signals that might distinguish indolent lesions from those more likely to progress to invasive disease.
The study highlighted key alterations in driver genes, chromosomal instability, and epigenetic shifts — helping lay the groundwork for how we think about risk stratification in early-stage breast cancer.
While the tools and datasets have evolved dramatically since then, the core insight remains: not all DCIS is the same.
Today, advances like single-cell sequencing, multi-omic integration, and AI-powered pathology are pushing that vision further than we could have imagined — giving clinicians new ways to personalize care and predict risk with greater precision. But every step forward builds on the work that came before.
We’re proud that this early contribution helped move the field toward a more precise, personalized approach — and it continues to inspire the work we do every day at Nubaio to transform breakthrough research into real-world tools for smarter, safer cancer care.
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View the original paper: https://pubmed.ncbi.nlm.nih.gov/26249178/
Nubaio #PrecisionOncology #CancerResearch #BreastCancer #EarlyDetection #AIinHealthcare #HealthcareInnovation #TeamNubaio
