Computational analysis of super-resolved in situ sequencing data reveals genes modified by immune-tumor contact events

RNA. 2024 Apr 4:rna.079801.123. doi: 10.1261/rna.079801.123. Online ahead of print.ABSTRACTCancer cells can manipulate immune cells and escape from the immune system response. Quantifying the molecular changes that occur when an immune cell is touching a tumor cell can increase our understanding of the underlying mechanisms. Recently, it became possible to perform such measurements in situ, for example using expansion sequencing, which enabled in situ sequencing of genes with super-resolution. We systematically examined whether individual immune cells from specific cell types express genes differently when in physical proximity to individual tumor cells. First, we demonstrated that a dense mapping of genes in situ can be utilized for the segmentation of cell bodies in 3D, thus improving our ability to detect likely touching cells. Next, we utilized three different computational approaches to detect the molecular changes that are triggered by proximity: differential expression analysis, tree-based machine learning classifiers, and matrix factorization analysis. This systematic analysis revealed tens of genes, in specific cell types, whose expression separates immune cells that are proximal to tumor cells from those that are not proximal, with a significant overlap between the different detection methods. Remarkably, an order of magnitude more genes are trigger by proximity to tumor cells in CD8 T cells compared to CD4 T cells, in line with the ability of CD8 T cells to directl...
Source: RNA - Category: Genetics & Stem Cells Authors: Source Type: research