Background: Single-cell RNA-sequencing (scRNA-Seq) characterizes transcriptomes at a single-cell resolution, allowing for direct comparison of differential gene expression between tissue types. For pathological conditions such as cancer, the normal transcriptional state of affected tissues is needed to conduct direct test between the cellular landscape of the tumour microenvironment and its normal tissue counterpart.
Methods: Lung normal tissue (LN) were enzymatically dissociated into cell suspensions. Single-cell cDNA libraries were prepared per 10X Genomics Chromium 3â€™v3.1 protocol Libraries were sequenced using Illumina NovaSeq S4. Barcode deconvolution was done with cellranger. Cell QC, clustering and marker gene identification was conducted with Scanpy.
Results: Cell suspensions were made in parallel for LT and LN samples from 74 patients. After quality control assessment for cell count and viability, paired LT and LN cDNA Libraries from 52 patients were sequenced. A total of 179,932 cells were captured in normal libraries. Cell clustering revealed an array of lung cell types including Alveolar Type 1, Alveolar Type 2, Claria Cells, Ciliated cells, Fibroblast, Endothelial cells, secretory cells, and smooth muscle cell types. Immune types include Alveolar Macrophages, Denedtric cells, Neutrophils, Mast cells, Helper T cells and Natural Killer cells.
Conclusions: High quality single cell transcriptomes were produced for a very large number of lung and lung resident immune cells. This will serve as a basis of comparison for tumor analysis.