Spatial genomics enables multi-modal study of clonal heterogeneity in tissues

Area of Science:

• Genomics
• Cell Biology
• Cancer Research

Background:

• Tumor progression is influenced by genetic aberrations and the tumor microenvironment.
• Accurate measurement of spatial genomic and phenotypic data is needed to quantify these influences.
• Existing technologies may not fully capture the spatial context of genomic alterations within tissues.

Purpose of the Study:

• To develop a novel method for spatially resolved DNA sequencing in intact tissue sections.
• To enable the discovery of tumor clones and their copy number alterations in their native spatial context.
• To integrate spatial genomics with spatial transcriptomics to link genetic aberrations with gene expression and microenvironment.

Main Methods:

• Development of slide-DNA-seq, a method for capturing spatially resolved DNA sequences from intact tissue sections.
• Application of slide-DNA-seq to a mouse metastasis model and a primary human cancer.
• Integration of slide-DNA-seq data with spatial transcriptomics.

Main Results:

• Slide-DNA-seq accurately preserves local tumor architecture.
• The method enabled de novo discovery of distinct tumor clones and their copy number alterations.
• Clonal populations were found to be confined to distinct spatial regions.
• Integration with spatial transcriptomics identified genes associated with clone-specific aberrations, microenvironment, or both.

Conclusions:

• Slide-DNA-seq is a versatile platform for multi-modal spatial genomics.
• This approach allows quantification of cell-intrinsic and cell-extrinsic factor contributions to cellular phenotypes.
• The technology provides new insights into the spatial organization of tumor heterogeneity and its drivers.