Salvatore Albani

CyNET analyzes immune system networks to identify functional hubs and maturation patterns across age groups using single-cell transcriptomics.

The paper develops a bioengineered vascularized pancreatic cancer model and uses multi-omics and functional assays to reveal an immunosuppressive and therapy-resistant tumor niche.

This study characterizes the tumor microenvironment of steatotic liver-related hepatocellular carcinoma using single-cell and spatial transcriptomic analyses, identifying immunosuppressive features and Treg-CAF interactions linked to immunotherapy resistance.

This study compares scRNA-seq methods with and without sample multiplexing, showing Parse detects rare cell types better despite lower efficiency, while 10X has platform-specific gene length and GC content distributions.

This study identifies IL-11 as a key driver of HSC-to-myofibroblast transformation in NASH, showing that targeting IL-11 reduces fibrosis and inflammation in preclinical models.