Methods Mol Biol. 2026;2995:119-127. doi: 10.1007/978-1-0716-5027-1_8.
ABSTRACT
Understanding complex diseases such as cancer requires insight into both the intrinsic properties of individual cells and their interactions within the tumor microenvironment. Integrating single-cell RNA sequencing (scRNA-seq), which captures transcriptional states, with spatial proteomics, which provides spatially resolved protein expression data, offers a powerful opportunity to unravel disease mechanisms. In this protocol, we describe a framework that unifies scRNA-seq and spatial proteomics into a joint graph-based representation. This approach enables accurate prediction of disease pathologies and reveals critical cell-cell interactions that drive disease progression.
PMID:42062682 | DOI:10.1007/978-1-0716-5027-1_8
