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Nature Papers Describe Cancer Cell-Surface Protein Catalog, Spatial Genomics Approach to Study Clonal Heterogeneity

The Cancer Surfaceome Atlas, a catalog of cell-surface proteins (SPs) across multiple cancers, is presented in Nature Cancer this week. SPs have been proposed as a rich source for the identification of targets for immune and targeted therapy, and genes encoding SPs (GESPs) currently serve as direct targets for more than 60 percent of approved anticancer immune and targeted therapy drugs. Yet challenges to the systematic characterization of the surfaceome across healthy and tumor tissues has limited their use in anticancer drug discovery. To address this, a team from the University of Pennsylvania comprehensively identified and annotated GESPs pan-cancer, characterizing GESP expression patterns, recurrent genomic alterations, essentiality, receptor–ligand interactions, and therapeutic potential. The results are available online within the Penn's Functional Cancer Genome Portal. GenomeWeb has more on this, here.

The use of a new spatial genomics technique for the study of clonal heterogeneity in tissues is reported by researchers from Harvard University and the Broad Institute in Nature this week. The state and behavior of a cell can be influenced by both genetic and environmental factors, with tumor cells in particular affected by genetic aberrations and the tumor microenvironment. Since understanding the roles of these factors requires the precise measurement of the spatial location of genomic sequence along with phenotypic readouts, the investigators developed slide-DNA-seq, a method for capturing spatially resolved DNA sequences from intact tissue sections. They demonstrate its use in a mouse model of metastasis and a primary human cancer, showing that clonal populations are confined to distinct spatial regions. Integrating the method with spatial transcriptomics, they also find distinct sets of genes that are associated with clone-specific genetic aberrations, the local tumor microenvironment, or both. While spatially resolved DNA sequencing holds promise in cancer genomics, it may also prove useful in other areas including spatially resolved metagenomics, the evaluation of gene therapy delivery, synthetic DNA data storage, and lineage tracing in healthy tissue, the researchers write.