FRDEGs of IPF
After integrating 293 FRGs and the DEGs identified in the GSE110147, 47 up-regulated and 24 down-regulated FRDEGs were identified (Figure 2A-2B).
PPI network
The PPI network was constructed based on the 71 FRDEGs according to the STRING database (average node degree: 5.6, PPI enrichment p-value: < 1.0e-16), which was visualized by Cytoscape [20, 21]. We removed the nodes with no connections, Therefore, the final network contained 66 nodes and 196 edges (Figure 2C). Ceruloplasmin (CP) was the highest up-regulated gene, and angiopoietin like 4 (ANGPTL4) was the highest down-regulated gene in the PPI network. We calculated the connectivity degree of each node, and selected those with degrees ≥ 15, as follows: mitogen-activated protein kinase 3 (MAPK3, down-regulated), heme oxygenase 1 (HMOX1, down-regulated), KRAS proto-oncogene, GTPase (KRAS, up-regulated), heat shock protein family A member 5 (HSPA5, up-regulated) and ATM serine/threonine kinase (ATM, up-regulated). In addition, one module (Figure S1) were selected after MCODE analysis of the whole network, and the results of enrichment analysis of FRDEGs within the module were showed in Figure S2 by R package “clusterProfiler” [19], which revealed the important pathways: cell growth and death, and pathways associated cancer.
Key gene ontology and pathways enriched in IPF
In order to reveal the biological significance of 71 FRDEGs regulating IPF at a single level, we used R package “clusterProfiler” [19] to conduct biological pathway enrichment and biological process annotation for the 71 genes mentioned above. The 20 most significantly KEGG pathways were selected (Supplementary Table 2, Figure 3A, 3F). More importantly, cell growth and death, pathways associated cancer and signal transduction were the main pathways, implying that FRDGEs may participate in the process of IPF according to these pathways (Figure S3A). Hsa04216 (Ferroptosis, including 11 FRDEGs) was the first significantly enriched pathway (FigureS3B). FRDEGs-related top 20 biological processes (BP), cellular component (CC) and molecular function (MF) were showed in Figure 3B-3D respectively. The top 20 GOs were showed in Supplementary Table 3 and Figure 3E, which were consisted of cellular responses to stimulus and various situations.
Some potential biomarkers had been found in IPF
A total of 1638 miRNA-target interactions associated with 68 of 71 FRDEGs and 463 related miRNAs were derived from miRDB [17] and visualized by Cytoscape (Figure 4). The related nodes with degrees ≥ 25 were shown in Table 2. The more interactions with miRNAs, the more degree is. Therefore, integrin subunit beta 8 (ITGB8) was considered the hub node. In addition, for miRNA, the related nodes with degrees ≥ 9 were shown in Table 3. The top 5 hub nodes with higher degrees were hsa-miR-513a-3p, hsa-miR-513c-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-3065-5p.
Identify of key genes
The top 12 genes with high degrees in Table 2 and the top 7 genes with high degrees or high DEG level as mentioned above in the PPI network were selected as the candidate key genes. Subsequently, the expression levels of 19 candidate key genes were compared between IPF patients and healthy control in the GSE32537 dataset. Finally, acyl-CoA synthetase long chain family member 1 (ACSL1, down-regulated), CP (up-regulated), tumor protein p63 (TP63, up-regulated), ITGB8 (up-regulated) and MYB proto-oncogene, and transcription factor (MYB, up-regulated) were selected as the key genes (Figure 5A-5E). According to linear regression, ASCL1 was negatively associated with FVC% predicted, Dlco% predicted, and positively associated with SGRQ score, and the Spearman correlation coefficients were calculated as -0.4132, -0.3609 and 0.2964, respectively (Figure 6A-6C). In addition, CP and ITGB8 were only negatively associated with FVC% predicted, the Spearman correlation coefficients were calculated as -0.2095 and -0.2345, respectively (Figure 6D, 6G). However, the correlations between CP and Dlco% predicted or SGRQ score were not significant (Figure 6E-6F), ITGB8 showed the same result (Figure 6H-6I)
Drug discovery
According to DrugBank [22], 16 drugs have been found to be acted on CP, and 2 drugs have been found to be acted on ACSL1. According to searching from PubMed, 2 drugs [Benzimidazole series (compound 13) [23] and Aspirin [24]] were found to be acted on ACSL1, however, no additional drugs associated with CP or ITGB8 were found. These drugs and related papers were listed in Table 4.