Evaluation of circulating small extracellular vesicle-derived miRNAs as diagnostic biomarkers for differentiating between different pathological types of early lung cancer

Abstract

Lung cancer is the leading cause of cancer-related death worldwide. MicroRNAs (miRNAs) in circulating small extracellular vesicles (sEVs) have been suggested to be potential biomarkers for cancer diagnosis. The present study was designed to explore whether plasma-derived sEV miRNAs could be utilized as diagnostic biomarkers for differentiating between early-stage small cell lung cancer (SCLC) and early-stage non-small cell lung cancer (NSCLC). We compared the miRNA profiles of plasma-derived sEVs from healthy individuals, patients with early-stage SCLC and patients with early-stage NSCLC. Next-generation sequencing was used to screen for differentially expressed miRNAs (DEMs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to predict the potential functions of these DEMs. Weighted gene coexpression network analysis (WGCNA) was used to identify the different pathology-related miRNA modules. We found that 22 DEMs were significantly different among healthy individuals, patients with early-stage SCLC, and patients with early-stage NSCLC. We selected six representative DEMs for validation by qRT‒PCR, which confirmed that miRNA-483-3p derived from plasma sEVs could be used as a potential biomarker for the diagnosis of early-stage SCLC, miRNA-152-3p and miRNA-1277-5p could be used for the diagnosis of early-stage NSCLC respectively.

Figure 1

Flow chart of the study.

Figure 2

Isolated sEV-enriched fractions from participants’ plasma (a–c) TEM images showing that sEVs of three groups are oval or bowl-shaped capsules without a nucleus. d. The Western blot analysis of sEVs, markers CD9, CD63and TSG101were all detected in the sEV-enriched fractions isolated from plasma, and Calnexin, a negative marker of sEVs was absent in our isolated sEVs-enriched fraction samples. (e–g) NTA showed that the diameter and concentration of EVs for three groups. CL, control cell lysate.

Figure 3

Identification and functional enrichment analysis of differentially expressed sEV-derived miRNAs. Volcano plot of differentially expressed sEV-derived miRNAs in CT versus SCLC, CT versus NSCLC and SCLS versus NSCLC (a–c). Each point represents an miRNA, red represents upregulated miRNA, green represents downregulated miRNA, and blue represents non-differentially expressed miRNAs. Heatmap of differentially expressed sEV miRNAs in CT versus SCLC, CT versus NSCLC and SCLS versus NSCLC (d–f). Red indicates high relative expression, and green indicates low relative expression.

Figure 4

Plasma sEV-enriched fraction-derived miRNAs profiles that could be used to discriminate SCLC from NSCLC. (a) Venn diagram comparing the differential expression of sEV-derived miRNAs, each circle representing the number of differentially expressed sEV-derived miRNAs between two conditions. (b) Heat map of the 22 DEM expression levels across all 35 samples in our plasma sEV-enriched fraction miRNA dataset. (c) The specificity and sensitivity of each DEM for identifying SCLC versus NSCLC patients in our plasma sEV-enriched fraction miRNA dataset.

Figure 5

GO enrichment and KEGG pathway analysis of the 22 DEMs comparing SCLC and NSCLC. Advanced bubble chart shows enrichment of genes in signaling pathways. BP, biological processes; CC, cellular component; MF, molecular function.

Figure 6

WGCNA network module mining, GO enrichment and KEGG pathway analysis of MEgreen and MEbrown. (a) The plasma-derived sEV miRNAs analyzed by the WGCNA method. (b) Module-pathological type relationships of consensus module eigengenes and different pathological types of lung cancer. Intensity and direction of correlations are indicated on the right side of the heatmap (red, positively correlated; blue, negatively correlated. (c, d) GO enrichment and KEGG pathway analysis of miRNAs in the MEgreen. (e, f) GO enrichment and KEGG pathway analysis of miRNAs in the MEbrown.

Figure 7

The expression levels and AUC of miR-483-3p, miR-152-3p, and miR-1277-5p of plasma-derived sEVs for validation. (a–c). The expression levels of miR-483-3p, miR-152-3p, and miR-1277-5p, respectively. The ordinate (y axis) is relative expression of miRNA. The abscissa of the upper edge is P-values, estimated by Mann–Whitney independent t-testing. (d–f) The AUC result of miR-483-3p, miR-152-3p, and miR-1277-5p from CT versus SCLC (d), CT versus NSCLC(e) , and SCLS versus NSCLC (f) , and combinations of two or three of these miRNAs.