Table 1.
The detail clinical information of 6 samples.
Fig 1.
Fig 1 display SCI-DEGs and SCI-DRGs.
Fig 1A heatmap shows the 20 upregulated and downregulated of 7387 SCI-DEGs genes with the most significant differences, the red color represents upregulated genes, the wathet color represents downregulated genes, and the distribution of differentially expressed genes in spinal cord injury, control group, and each dataset. Fig 1B highlights the significant DEGs associated with SCI in a volcano plot. Fig 1C illustrates the identification of SCI-DRGs, through the Fisher’s exact test, the P value is 0.01841296. The two gene sets are not independent, that is, there is a significant correlation. Fig 1D shows the expression heatmap of 15 SCI-DRGs in each sample, the red color represents upregulated genes, the wathet color represents downregulated genes, and the distribution of differentially expressed genes in spinal cord injury, control group.
Fig 2.
Fig 2 presents the results of the GO and KEGG analyses of SCI-DEGs.
Fig 2A shows the GO analysis, displaying top 10 enriched terms (BP, CC, MF) related to SCI according to the fold enrichment,; detailed results can be found in S3 Table. Fig 2B represents the KEGG pathway analysis, revealing top 30 enriched pathways in SCI according to the fold enrichment and P Value, detailed results can be found in S4 Table.
Fig 3.
Fig 3 displays the differential expression of CAPZB, SCL3A2, and TLN1 in peripheral blood leukocytes within 7 days after SCI, as revealed by our qRT-PCR analysis in humans.
Ultimately, we observed that there were differential expressions of the three genes, CAPZB, SCL3A2, and TLN1 and chosen CAPZB, SCL3A2, and TLN1 for subsequent analysis in hSCI-DRGs. In the figure, * indicates a P-value less than or equal to 0.05, and ** indicates a P-value less than or equal to 0.01.
Fig 4.
Fig 4 depicts the expression profiles of hSCI-DRGs in the experimental cohort, validation cohort, and spatial transcriptomic data.
7D-SCI represents the spatial transcriptomic expression profile data of mice 7 days after SCI, while Norm denotes the control group spatial transcriptomic data. Fig 4A shows the expression levels and trends of Capzb in the experimental cohort (A1), validation cohort (A2), and spatial transcriptomic data GSE234774-GSM7474508 (A3), both datasets show consistent expression trends, the spatial transcriptomics data show that the Capzb is expressed at higher levels in the tissue surrounding spinal cord injury lesions. Fig 4B shows the expression levels and trends of Slc3a2 in the experimental cohort (B1), validation cohort (B2), and spatial transcriptomic data GSE234774-GSM7474508 (B3), both datasets show consistent expression trends, the spatial transcriptomics data show that the Slc3a2 is expressed at higher levels in the tissue surrounding spinal cord injury lesions. Fig 4C shows the expression levels and trends of Tln1 in the experimental cohort (C1), validation cohort (C2), and spatial transcriptomic data GSE234774-GSM7474508 (C3), both datasets show consistent expression trends, the spatial transcriptomics data show that the Tln1 is expressed at higher levels in the tissue surrounding spinal cord injury lesions.
Fig 5.
Fig 5 shows the single-gene GSEA-KEGG analysis top 5 result in SCI group of hSCI-DRGs, and the P value of the presented pathways were all less than 0.05.
Fig 5A, 5C and 5E represents the enrichment analysis results of CAPZB, SLC3A2 and TLN1 in the high-expression group, while Fig 5B, 5D and 5F shows the enrichment analysis results of CAPZB, SLC3A2 and TLN1 in the low-expression group.
Fig 6.
Fig 6 presents immune cell infiltration analysis of hSCI-DRGs.
Fig 6A demonstrates the exploration of differences in the immune microenvironment between SCI and normal samples using the CIBERSORT algorithm, the results showed that hSCI-DRGs were associated with B cells naive, NK cells resting and NK cells activated, detailed results can be found in S5 Table. Fig 6B shows that CAPZB is positively correlated with T cell follicular helper and negatively correlated with Dendritic cells resting. Fig 6C, 6Dshows that SLC3A2 and TLN1 was positively correlated with Dendritic cells resting and Mast cells resting, and negatively correlated with Mast cells activated and Macrophages M1. Red font markers in the figure indicate a P-value less than or equal to 0.05.
Fig 7.
Fig 7A displays the transcription factor functional enrichment analysis of hSCI-DRGs. Through analysis, we retrieved seven transcription factors related to hSCI-DRGs and analyzed the regulatory pathways related to the transcription factors, detailed results can be found in S6 Table. Fig 7B shows the hSCI-DRGs-transcription factor-drug regulatory network and 140 transcription factor-related regulatory drugs. 43 of the drugs marked by purple circles have now been validated.