Bioinformatic analysis
All the omics datasets were based on unified gene symbol. For proteomic data, the highest interquartile range of transcript or peptide was chosen if multiple of them were mapped to the same gene. Differentially expressed genes (DEGs) were defined as FDR<0.05 and absolute value of fold change >1.5. The DEG dataset for further analysis consisted of those genes differentially expressed on both mRNA and protein levels. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and Ingenuity Pathway Analysis (IPA) were subsequently conducted to identify biological characteristics, biomarkers, and pathways related. We used molecular complex detection (MCODE) plugin from Cytoscape to analyze top clusters from the network of interactions between DEGs. We picked out the top 5 clusters and performed CentiScaPe to calculate centrality indexes and identify hub genes. Canonical pathway analysis in IPA led pathways based on these genes. Target gene was decided after comprehensively incorporating pathways and hub genes enriched. Finally, we selected DEGs positively correlated with targes gene and investigate potential pathways.