New Computational Approach Creates Spatial Maps of Single-Cell Data Within Tissues

A new computational method created by researchers at The University of Texas MD Anderson Cancer Center successfully matches data from correspondent gene-expression profiling techniques to develop spatial maps of an offered tissue at single-cell resolution. The resulting maps can supply special biological insights into the cancer microenvironment and many other tissue types.

The study was published in Nature Biotechnology and presented at the upcoming American Association for Cancer Cells Research (AACR) Annual Meeting 2022 (Abstract 2129).

The device, called CellTrek, uses data from single-cell RNA sequencing (scRNA-seq) together with that of spatial transcriptomics (ST) assays -; which measure spatial gene expression in several small cells -; to precisely identify the location of individual cell types within a tissue. The researchers showed findings from an evaluation of kidney and brain cells and samples of ductal carcincoma in situ (DCIS) breast cancer.

Single-cell RNA sequencing is a settled technique to examine the gene expression of several individual cells from a sample, but it can not give data on the location of cells within a tissue. On the other hand, ST assays can determine spatial gene expression by assessing numerous little groups of cells across a tissue yet are not efficient in giving single-cell resolution.

Present computational strategies, known as deconvolution strategies, can pinpoint different cell kinds existing from ST data; however, they cannot give detailed data at the single-cell level, Navin clarified.

Therefore, co-first authors Runmin Wei, Ph.D., and Siyuan He of the Navin Lab led the efforts to establish CellTrek as a tool to combine the unique advantages of scRNA-seq and ST assays and create precise spatial maps of tissue samples.

Utilizing publicly accessible scRNA-seq and ST data from brain and kidney tissues, the scientists showed that CellTrek accomplished the most accurate spatial resolution of the evaluated approaches. The CellTrek approach also could differentiate subtle gene expression differences within the same cell kind to gain details on their heterogeneity within an example.

The scientists also collaborated with Savitri Krishnamurthy, M.D., professor of Pathology, to use CellTrek to study DCIS breast cancer tissues. In an analysis of 6,800 single cells and 1,500 ST regions from a single DCIS sample, the group discovered that distinct subgroups of tumor cells were developing in unique patterns within particular areas of the tumor. Evaluation of a second DCIS sample demonstrated the capacity of CellTrek to rebuild the spatial tumor-immune microenvironment within tumor tissue.

“While this approach is not restricted to evaluating tumor tissues, there are obvious applications for better understanding cancer,” Navin stated. “Pathology drives cancer diagnoses and, with this device, we can map molecular data on top of pathological information to allow even deeper classifications of tumors and better guide treatment approaches.”

Source:

University of Texas M. D. Anderson Cancer Center

Journal reference:

Wei, R., et al. (2022) Spatial charting of single-cell transcriptomes in tissues. Nature Biotechnology. doi.org/10.1038/s41587-022-01233-1.