Computational approach enables spatial mapping of single-cell data within tissues

A new approach developed by researchers at The University of Texas MD Anderson Cancer Center combines data from parallel gene-expression profiling methods to create spatial maps of a given tissue at single-cell resolution. The maps can provide insights into the cancer microenvironment.

The study will be presented at the American Association for Cancer Research Annual Meeting in 2022.

The tool uses data from single-cellRNA-seq together with that of spatial transcriptomics to accurately locate the location. The researchers presented findings from the analysis of the brain and kidneys.

Nicholas Navin, a professor of Genetics and Bioinformatics, said that single-cell RNA sequencing provides tremendous information about the cells within a tissue, but, ultimately, you want to know where these cells are distributed, particularly in tumor samples.

The location of cells within a tissue can't be determined with single-cell RNA sequencing because it doesn't provide information on the expression of many individual cells from a sample. The ability to measure spatial gene expression by analyzing many small groups of cells across a tissue is not enough to provide single-cell resolution.

Deconvolution techniques can identify different cell types, but they are not capable of providing detailed information at the single-cell level.

The co-first authors led the efforts to develop CellTrek as a tool to combine the advantages of scRNA-seq and ST assays and create accurate spatial maps of tissue samples.

The most accurate and detailed spatial resolution of the methods evaluated was achieved by CellTrek. The CellTrek approach was able to distinguish subtle gene expression differences within the same cell type to gain information on their heterogeneity.

The researchers collaborated with the professor of Pathology to study breast cancer tissues. The team discovered that different groups of tumor cells were evolving in different areas of the tumor. The ability of CellTrek to reconstruct the spatial tumor-immune microenvironment within a tumor tissue was demonstrated by the second DCIS sample.

There are obvious applications for better understanding cancer, and this approach is not restricted to analyzing tumor tissues.

Collaborating Anderson authors include MD Shanshan Bai, PhD, and Min Hu, all of Genetics, and Ken Chen, PhD, of Bioinformatics. The additional authors include an M.D. from the college of medicine. There are no conflicts of interest for the authors.

More information: Nicholas Navin, Spatial charting of single-cell transcriptomes in tissues, Nature Biotechnology (2022). DOI: 10.1038/s41587-022-01233-1. www.nature.com/articles/s41587-022-01233-1 Journal information: Nature Biotechnology Citation: Computational approach enables spatial mapping of single-cell data within tissues (2022, March 21) retrieved 21 March 2022 from https://phys.org/news/2022-03-approach-enables-spatial-single-cell-tissues.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.