High Definition Disease Modelling Lab: Stem Cell and Organoid Epigenetics
|Location|| Building 13 |
Via Adamello 16, Milano
The accelerated generation of multiple, digitally compatible datasets across scales of cellular and organismal function is transforming biomedicine, promising unprecedented precision for prevention, diagnosis and treatment. Central to this challenge is the need to resolve the specificity, heterogeneity and dynamics of disease in physiopathologically relevant and experimentally tractable models. To this end we spearhead stem cell and organoid-based patient-specific models for human cancer and neurodevelopmental disorders, focusing on genetic and environmental causes of chromatin dysregulation as a shared and increasingly relevant layer of pathogenic mechanisms.
Specifically, we start from densely phenotyped clinical cohorts and integrate multi-layered omics, single cell dynamics and high end computing to advance a foundational framework for precision oncology and neuropsychiatry. Our oncological research focuses on ovarian cancer, glioblastoma and thymomas, for which we pursue the functional dissection of the gene regulatory pathways and druggable hubs of epigenetic vulnerability that fuel tumorigenesis, metastasis or relapse. Within neurodevelopmental disorders, we study a uniquely informative panel of Autism Spectrum Disorder (ASD) and Intellectual Disability (ID) syndromes, caused by point mutations or copy number variations in interrelated chromatin regulators and transcription factors, probing the molecular mechanisms of their convergence/distinction at single cell resolution and across multiple layers of regulation.
Most Relevant Publications
KMT2B is selectively required for neuronal transdifferentiation and its loss exposes dystonia candidate genes
Cell Rep, 2018
Polycomb dysregulation in gliomagenesis targets a Zfp423-dependent differentiation network.
Nat Commun, 2016
7q11.23 dosage-dependent dysregulation in human pluripotent stem cells affects transcriptional programs in disease-relevant lineages.
Nat Genet, 2015
PhD Student Bioinformatician