Andrea Bertotti

This study introduces a method to infer lineage hierarchies and drug response mechanisms in cancer cell populations without single-cell tracking, demonstrating its effectiveness through simulations and experiments.

This study shows that TGF-β1-induced differentiation in colorectal cancer organoids enhances chemotherapy response by reducing clonogenic capacity and increasing oxaliplatin cytotoxicity.

This study identifies on-target WRN mutations as resistance mechanisms in MSI cancer cells to WRN helicase inhibitors and suggests combination therapies to prevent resistance.

ConSTRain is a novel STR variant caller that accounts for copy number alterations, enabling accurate genotyping in polyploid and aneuploid organisms.

The paper measures mutation rates in microsatellite stable colorectal cancers and finds they vary between tumors and increase during metastasis.

This paper introduces μSeq, a method for accurately quantifying mutation rates using deep sequencing of single clonal expansions, showing it outperforms existing methods in robustness and accuracy.

The paper trains an ensemble classifier to predict cetuximab sensitivity in colorectal cancer PDXs using multi-omic data, achieving high accuracy and demonstrating its utility for therapeutic biomarker development.

CONNECTOR analyzes longitudinal tumor growth data to identify clusters and reveal new molecular associations with therapy response.

INKA identifies active phosphokinases in cancer by integrating kinase and substrate phosphorylation data from phosphoproteomics.