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.