Francisco Sánchez-Vega

Tracking ongoing chromosomal instability using single-cell whole-genome sequencing

This paper develops a computational framework using single-cell whole-genome sequencing to identify ongoing chromosomal instability, showing its utility in cancer models and clinical samples.

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkers

The paper develops Mosaic, a machine learning system that classifies tumors into detailed subtypes and identifies molecular phenotypes using histopathologic and genomic data from a large patient cohort.

Paired primary-metastasis patient-derived organoids and mouse models identify phenotypic evolution and druggable dependencies of peritoneal metastasis from appendiceal cancer

The paper develops patient-derived organoids and mouse models of appendiceal cancer to identify phenotypic changes and drug targets in peritoneal metastasis.