Expression Profiles of circRNAs and Identification of hsa_circ_0007608 and hsa_circ_0064656 as Potential Biomarkers for COPD-PH Patients

Abstract

Introduction: Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD), which can worsen the prognosis and increase the mortality of COPD patients. Circular RNA (circRNA) has been discovered to participate in the occurrence and progression of PH in COPD and may have significant prospects for advanced diagnostics and prognosis evaluation. However, the expression profile of circRNAs in human lung tissues with definite diagnosis of COPD-PH remains to be further explored and validated.

Methods: Twelve human lung tissue samples (6 each from COPD-PH and control groups) were collected and subjected to high-throughput sequencing. QRT-PCR was performed to validate the differential expression levels of the top 10 dysregulated circRNAs in patients' plasma samples, HPAECs and HPASMCs. Functional and pathway enrichment analysis on target genes was performed to explore the potential functions and pathways of those circRNAs. Hub genes obtained after conducting bioinformatics analysis on the predicted target mRNAs were verified by qRT-PCR in HPAECs and HPASMCs, and then we selected VCAN as a potential key gene involved in the pathogenesis of COPD-PH for immunohistochemistry validation in lung tissue.

Results: A total of 136 circRNAs (39 up-regulated and 97 down-regulated) were differentially expressed between the two groups. Following qRT-PCR validation, two circRNAs (hsa_circ_0007608 and hsa_circ_0064656) were believed to be involved in the pathogenesis. GO and KEGG pathway analysis suggested that these two DECs were mainly related to the celluar proliferation, migration and EndMT. PPI network revealed 11 pairs of key mRNAs. VCAM1, VCAN and THBS1, three hub mRNAs with the highest reliability among all, were validated and proven to be up-regulated in COPD-PH. We innovatively found that VCAN may be involved in COPD-PH.

Conclusion: This study identified the functional circRNAs, providing insights into the molecular mechanisms and predictions of COPD-PH, and may provide potential diagnostic biomarkers or therapeutic targets for COPD-PH.

Keywords: RNA-sequencing; bioinformatics analysis; biomarker; chronic obstructive pulmonary disease; circular RNA; pulmonary hypertension.

Figure 1

The workflow of study.

Figure 2

Microarray analysis of differential expression of circRNAs in COPD-PH patients. (A) A box plot of circRNAs expression in all samples. (B) Hierarchical cluster analysis revealed the expression profile of the dysregulated circRNAs in the two groups. (C) Volcano map of differentially expressed circRNAs in COPD-PH group. The two vertical lines show differentially expressed circRNAs of 2-fold up and down, and the horizontal line represents p=0.05. Green dots and red dots indicate circRNAs that were differentially expressed with statistical significance. (D) Scatter plot demonstrates the expression variation of circRNAs in the two groups. The values of x and y-axes represent the normalized values of the samples (log2 scaled). The red dots outside the top grey line indicate the up-regulated circRNAs with ≥2‑fold change and the green dots outside bottom grey line indicate the down‑regulated circRNAs with ≥2‑fold change.

Figure 3

qRT-PCR validation of circRNAs expression in serum and pulmonary vascular cell. (A and B) Two significantly up-regulated circRNAs in serum, n=12. (C) hsa_circ_0007608 was constantly up-regulated with the prolongation of hypoxia in HPAECs, n=3. (D and E) hsa_circ_0064656 decreased significantly in HPAECs, while increased in HPASMCs, n=3. (*P<0.05, **P<0.01, *** P<0.001).

Figure 4

Identification of key mRNAs. (A) Cluster heatmap revealed the expression profile of the dysregulated mRNAs in two groups. (B) Volcano map of differentially expressed mRNAs in two group. (C) A Venn of target mRNAs and DEmRNAs. (D) The circRNA-miRNA-mRNA regulatory network. circRNA, miRNA and mRNA are indicated by red triangles, blue diamonds and green squares, respectively.

Figure 5

A bar plot of top 10 GO enriched biological process, cellular component and molecular process of linear counterparts of DECs in COPD-PH. The -log10 (p-value) yields an enrichment score representing the significance of GO term enrichment between differently expressed circRNAs.

Figure 6

A dot plot of top 10 KEGG pathway of linear counterparts of DECs in COPD-PH. KEGG analysis according to rich factor, q-value and the number of enriched genes.

Figure 7

Identification and validation of hub mRNAs. (A) Correlation heat map of 35 key mRNA. (B) The protein–protein interaction (PPI) of key mRNAs.(C–E) VCAM1, VCAN and THBS1 were up-regulated in HPAECs after 48 hours of hypoxia treatment, n=3 (**P<0.01, *** P<0.001). (F–H) VCAM1, VCAN and THBS1 were up-regulated in HPASMCs after 48 hours of hypoxia treatment, n=3 (*** P<0.001). (I and J) Representative immunohistochemistry staining and quantitative analysis of VCAN in two groups of human lung tissue, ×200, scale bar: 100μm, n=3. (***P< 0.001, normal vs COPD-PH group, Student t test).