Fig. 5
CAV2 knockdown generated a multi-gene regulatory network that influenced PUFA accumulation, potentially targeting mitochondria in OSCC. (A) Chord plots of canonical correlation analysis (CCA) showing correlations between differential genes and differential lipids. The CCA correlation chord diagram was sorted by correlation, and the top 20 pairs with the strongest correlation were selected with a correlation cut-off of 0.9958. Nodes (genes/lipids) were arranged along the circumference, and weighted lines connected nodes. Genes or lipids were on the edge of the circle in the figure, and the connecting line in the circle represented the correlation between genes and lipids; red is a positive correlation, and blue is a negative correlation. Correlation analysis was performed using Spearman correlation analysis. (B) Interaction map of the CCA correlation network between differential genes and differential lipids. Each point in the figure represented a gene or a lipid. The more lines between the points, the more genes or lipids it might regulate. Green dots represented genes, yellow dots represented lipids, connecting lines between dots, red lines represented positive correlations, and blue lines represented negative correlations. Correlation analysis was performed by Spearman correlation analysis. (C) Venn diagram of differential genes and differential lipids involvement pathways. The numbers in the overlapping area of circles represented the number of pathways that were shared/specific between the two omics. (D) Bubble plot of differential gene and differential lipids pathway enrichment analysis. The X-axis is the RichFactor; the larger the value, the greater the ratio of differential genes and differential lipids annotated to the pathway. The triangles in the figure represented functional gene pathways, the circles represented metabolic pathways, the size of the figure represented the number of differential genes and differential lipids annotated to the pathway, and the color represented the significance of the pathway. (E-H) Molecular docking analysis among the nuclear magnetic resonance (NMR) structure of FA(20:4), FA(20:5), FA(22:5), and FA(24:6) with carnitine O-palmitoyltransferase 1 A (CPT1A), respectively. (I) Immunohistochemical analysis of CPT1A in CAL27 and SCC25 cells transduced with CAV2 shRNAs. KD represented cells treated with shRNA targeting CAV2 (labeled with GFP for green fluorescence tracking), and NC represented cells treated with scrambled control shRNA (labeled with GFP for green fluorescence tracking). Mean integrated optical density (IOD) was used to quantify CPT1A protein levels in KD and NC groups. Data were expressed as the mean ± SD (n=3). *P<0.05, **P<0.01. The Student’s t-test determined significance. (J) The GO Cellular component bubble chart related to mitochondrion with significance. The Q-value is the false discovery rate adjusted P-value. CAV2: Caveolin2; PUFAs: polyunsaturated fatty acids; OSCC: oral squamous cell carcinoma; CCA: canonical correlation analysis; RichFactor: the enrichment factor; NMR: nuclear magnetic resonance; CPT1A: carnitine O-palmitoyltransferase 1 A; KD: shRNA targeting CAV2, labeled with GFP for green fluorescence tracking; NC: scrambled control shRNA, labeled with GFP for green fluorescence tracking; IOD: integrated optical density