Development and validation of biomarkers related to anoikis in liver cirrhosis based on bioinformatics analysis

Figure 1 Identification and functional enrichment analysis of differentially expressed anoikis-related genes. A: Volcano maps of differentially expressed genes (DEGs); B: Heat map of DEGs; C: Venn diagram of differentially expressed anoikis-related genes (DEARGs); D: Gene ontology analysis of DEARGs based on three domains, namely, cellular component, molecular function, and biological process; E: Kyoto Encyclopedia of Genes and Genome pathway analysis. DEGs: Differentially expressed gene; ARG: Anoikis-related gene.

Figure 2 Identification of biomarkers through machine learning algorithms. A: Least absolute shrinkage and selection operator coefficients profiles; B: Cross-validation for tuning parameter selection. Variables with non-zero coefficients were excluded; C: When n was 3, the classifier had the minimum error in the support vector machine recursive feature elimination model; D: Interpretation chart of two important evaluation indices; E: Venn diagram showing three biomarkers for cirrhosis.

Figure 3 Assessment and validation of the diagnostic efficacy of biomarkers. A: Principal component analysis was performed to analyze whether the three biomarkers could distinguish between control and cirrhotic samples; B: Receiver operating characteristic (ROC) curves of the biomarkers in the GSE89377 dataset; C: ROC curves of the biomarkers in the GSE14323 dataset; D: Expression of the biomarkers in the GSE89377 and GSE14323 datasets; E: A nomogram based on the biomarkers; F: Calibration curve of the nomogram; G: Decision curve analysis of the nomogram. AUC: Area under curve.

Figure 4 Gene set enrichment analysis. A: Gene ontology (GO) enrichment analysis of ACTG1; B: Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of ACTG1; C: GO enrichment analysis of CCR7; D: KEGG enrichment analysis of CCR7; E: GO enrichment analysis of STAT1; F: KEGG enrichment analysis of STAT1. COVID-19: Coronavirus disease 2019.

Figure 5 Analysis of classical signaling pathways and immune infiltration. A: Classical pathways involving the three biomarkers; B: Idiopathic pulmonary fibrosis-related signaling pathway; C: Proportional stacking plot of immune cell distribution in each sample; D: Boxplot of immune cell distribution between the cirrhosis and control groups; E: Correlation between the biomarkers and differential immune cells.

Figure 6 Analysis of classical signaling pathways and immune infiltration. A: Classical pathways involving the three biomarkers; B: Idiopathic pulmonary fibrosis-related signaling pathway; C: Proportional stacking plot of immune cell distribution in each sample; D: Boxplot of immune cell distribution between the cirrhosis and control groups; E: Correlation between the biomarkers and differential immune cells.

Figure 7 Expression of biomarkers in clinical samples. A: ACTG1; B: STAT1; C: CCR7; NS: Not significant.