Integrated in vivo combinatorial functional genomics and spatial transcriptomics of tumours to decode genotype-to-phenotype relationships

Abstract

Advancing spatially resolved in vivo functional genomes will link complex genetic alterations prevalent in cancer to critical disease phenotypes within tumour ecosystems. To this end, we developed PERTURB-CAST, a method to streamline the identification of perturbations at the tissue level. By adapting RNA-templated ligation probes, PERTURB-CAST leverages commercial 10X Visium spatial transcriptomics to integrate perturbation mapping with transcriptome-wide phenotyping in the same tissue section using a widely available single-readout platform. In addition, we present CHOCOLAT-G2P, a scalable framework designed to study higher-order combinatorial perturbations that mimic tumour heterogeneity. We apply it to investigate tissue-level phenotypic effects of combinatorial perturbations that induce autochthonous mosaic liver tumours.