Cinzia Esposito

The paper identifies an RFX-driven ciliogenic cell state in colorectal cancer that is sensitive to FGFR inhibitors and associated with poor prognosis.

The paper integrates single-cell transcriptomes and spatial transcriptomics to identify therapeutic targets in pancreatic cancer by analyzing cell states and ligand-receptor interactions in tumoroids.

This study shows eosinophils inhibit CRC metastasis by blocking SPP1+ macrophage differentiation, using transcriptomics and a murine model.

scROSHI identifies cell types without training data by using pre-existing gene sets and hierarchical relationships, outperforming methods in low-data and high-diversity scenarios.

SCIM matches single-cell measurements across technologies by learning a technology-invariant latent space and applying bipartite matching, achieving high accuracy in real-world datasets.