Single-cell RNA sequencing identifies of early-stage lung cancer biomarkers from circulating blood

Lung cancer accounts for more than half of the new cancers diagnosed world-wide with poor survival rates. Despite the development of chemical, radiological, and immunotherapies, many patients do not benefit from these therapies, as recurrence is common. Dalhousie University researchers performed single-cell RNA-sequencing (scRNA-seq) analysis using Fluidigm C1 systems to characterize human lung cancer transcriptomes at single-cell resolution. Validation of scRNA-seq differentially expressed genes (DEGs) through quantitative real time-polymerase chain reaction (qRT-PCR) found a positive correlation in fold-change values between C-X-C motif chemokine ligand 1 (CXCL1) and 2 (CXCL2) compared with bulk-cell level in 34 primary lung adenocarcinomas (LUADs) from Stage I patients. Furthermore, the researchers discovered an inverse correlation between chemokine mRNAs, miR-532-5p, and miR-1266-3p in early-stage primary LUADs. Specially, miR-532-5p was quantifiable in plasma from the corresponding LUADs. Collectively, they identified markers of early-stage lung cancer that were validated in primary lung tumors and circulating blood.

Single-cell RNA-seq workflow and clustering analyses

Fig. 1

a Individual cells from A549 (blue), H460 (orange), H1299 (green), and Calu3 (red) were captured in separate Fluidigm C1 HT IFCs and pre-indexed with Fluidigm cell-specific barcodes at 3′-end of polyadenylated mRNAs during pre-amplification of cDNAs synthesized from total RNAs isolated from single cells, followed by library construction. Dual-indexed and 3′-end enriched cDNA libraries (n = 1,600) were sequenced in Illumina NextSeq 500 systems, followed by DEG detection. b Single cells (n = 1,441) in clusters (n = 4) re-arranged from NSCLC cell lines (n = 4). Parentheses include the number of cells in clusters or cell lines. c Cluster presentation in three dimensions. Subcluster, Cluster 1–1, is presented between Cluster 2 and 4. d Heatmap analysis of DEGs (n = 2,632). Z-scores of the read-count DEG dataset were adjusted from −1.50 (black) to 1.50 (yellow). Color-matching numbers represent A549 (blue; 1), H460 (orange; 2), H1299 (green; 3), and Calu3 (red; 4) as shown in (ac). DEGs specific to a cluster or cell line are highlighted in orange and purple, respectively. DEGs specific to Cluster 1–1 and Cluster 4 are highlighted in black. Representative DEGs per cluster, cell line and, Cluster 1–1 & Cluster 4-specific expression shown in the color-matching panels. See Supplementary Data 1 for full gene names. All DEGs are statistically significant at FDR-corrected P value < 0.05 showing fold changes >|2|.

Kim J, Xu Z, Marignani PA. (2021) Single-cell RNA sequencing for the identification of early-stage lung cancer biomarkers from circulating blood. NPJ Genom Med 6(1):87. [article]

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