Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules

Abstract

To enhance understanding of polycystic ovary syndrome (PCOS) at the molecular level; this investigation intends to examine the genes and pathways associated with PCOS by using an integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing data GSE84958 derived from the Gene Expression Omnibus (GEO) database, the differentially expressed genes (DEGs) between PCOS samples and normal controls were identified. We performed a functional enrichment analysis. A protein-protein interaction (PPI) network, miRNA- target genes and TF - target gene networks, were constructed and visualized, with which the hub gene nodes were identified. Validation of hub genes was performed by using receiver operating characteristic (ROC) and RT-PCR. Small drug molecules were predicted by using molecular docking. A total of 739 DEGs were identified, of which 360 genes were up regulated and 379 genes were down regulated. GO enrichment analysis revealed that up regulated genes were mainly involved in peptide metabolic process, organelle envelope and RNA binding and the down regulated genes were significantly enriched in plasma membrane bounded cell projection organization, neuron projection and DNA-binding transcription factor activity, RNA polymerase II-specific. REACTOME pathway enrichment analysis revealed that the up regulated genes were mainly enriched in translation and respiratory electron transport and the down regulated genes were mainly enriched in generic transcription pathway and transmembrane transport of small molecules. The top 10 hub genes (SAA1, ADCY6, POLR2K, RPS15, RPS15A, CTNND1, ESR1, NEDD4L, KNTC1 and NGFR) were identified from PPI network, miRNA - target gene network and TF - target gene network. The modules analysis showed that genes in modules were mainly associated with the transport of respiratory electrons and signaling NGF, respectively. We find a series of crucial genes along with the pathways that were most closely related with PCOS initiation and advancement. Our investigations provide a more detailed molecular mechanism for the progression of PCOS, detail information on the potential biomarkers and therapeutic targets.

Keywords: biomarkers; differentially expressed gene; expression profiling by high throughput sequencing; pathway enrichment analysis; polycystic ovary syndrome.

Fig. 1

Volcano plot of differentially expressed genes. Genes with a significant change of more than two-fold were selected. Green dot represented up regulated significant genes and red dot represented down regulated significant genes

Fig. 2

Heat map of differentially expressed genes. Legend on the top left indicate log fold change of genes. (A1 – A2 = normal control samples; B1 – B30 = PCOS samples)

Fig. 3

PPI network and the most significant modules of DEGs. a The PPI network of DEGs was constructed using Cytoscape. b The most significant module was obtained from PPI network with 26 nodes and 160 edges for up regulated genes. c The most significant module was obtained from PPI network with 26 nodes and 71 edges for up regulated genes. Up regulated genes are marked in green; down regulated genes are marked in red

Fig. 4

a Target gene - miRNA regulatory network between target genes and miRNAs. b Target gene - TF regulatory network between target genes and TFs. Up regulated genes are marked in green; down regulated genes are marked in red; The purple color diamond nodes represent the key miRNAs; the blue color triangle nodes represent the key TFs.

Fig. 5

ROC curve validated the sensitivity, specificity of hub genes as a predictive biomarker for PCOS prognosis. a SAA1, b ADCY6, c POLR2K, d RPS15, e RPS15A, f ESR1, g LCK, h S1PR5, i CCL28, j CTNND1

Fig. 6

Validation of hub genes by RT- PCR. a SAA1, b ADCY6, c POLR2K, d RPS15, e RPS15A, f ESR1, g LCK, h S1PR5, i CCL28, j CTNND1

Fig. 7

Structures of Designed Molecules

Fig. 8

2D Binding of Molecule ETE with 4IP8

Fig. 9

3D Binding of Molecule ETE with 4IP8