Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics

A key challenge in cancer research is to reconstruct the somatic evolution within a tumor over time and across space. Spatially resolved transcriptomics (SRT) measures gene expression at thousands of spatial locations in a tumor, but does not directly reveal genetic aberrations. We introduce CalicoST, an algorithm to simultaneously infer allele-specific copy number aberrations (CNAs) and a spatial model of tumor evolution from SRT of tumor slices. By modeling CNA-induced perturbations in both total and allele-specific gene expression, CalicoST identifies important types of CNAs – including copy-neutral loss of heterozygosity (CNLOH) and mirrored subclonal CNAs– that are invisible to total copy number analysis. On SRT data from nine patients from the Human Tumor Atlas Network (HTAN) with matched whole exome sequencing (WES) data, CalicoST achieves an average accuracy of 86%, approximately 21% higher than existing methods. On two patients with SRT data from multiple adjacent slices, CalicoST reconstructs a tumor phylogeography that describes the spread of cancerous clones in three-dimensional space. CalicoST analysis of multiple SRT slices from a cancerous prostate organ reveals five spatially coherent clones, with mirrored subclonal CNAs distinguishing clones on the two sides of the prostate, forming a bifurcating phylogeography in both genetic and physical space.