Application Of Weighted Gene Co-Expreesion Network Analysis In Oral Squamous Cell Carcinomas

Genes play a key role in many complex human diseases,and the occurrence of tumors is closely related to genetic changes.Constructing a gene co-expression network(GCN)is an effective way to characterize the correlation patterns among genes.Weighted gene co-expression network analysis(WGCNA)uses a scale-free network criterion to perform power exponential weighting of similarities between nodes and divides a group of genes with high topological overlap to a gene module,which can effectively identify biologically meaningful gene modules and hub genes.WGCNA is widely used in the international biomedical field.Oral squamous cell carcinomas(OSCC)is the most common head and neck cancer worldwide,with more than 300,000 new cases being diagnosed annually.Studies have shown that miRNAs are involved in the process of growth,differentiation,apoptosis,invasion and metastasis of OSCC tumor cells.How miRNAs work together to contribute to this process is still largely unknown.In this paper,we applied WGCNA to the miRNA expression profile data from a paired design study contributed by Shiah et al.,aiming to find miRNA modules significantly associated with OSCC.We first demonstrated that it is feasible to construct the co-expression networks using Pearson correlation for paired data.To account for the within-pair correlation,a linear mixed-effects model(LMM)was constructed to test the associations of miRNA modules to cancer status.Two significant modules(turquoise module with 254 miRNAs and grey module with 309 miRNAs)were identified.The miRNA miR-let-7c was the hub miRNA in the turquoise module in terms of node degree.Studies have shown that let-7 members are closely associated with oral squamous cell carcinomas.Finally,we used miRsystem to perform the target gene prediction and KEGG pathway enrichment analysis of miRNAs within the two modules.Interestingly,the two modules have similar sets of target genes so that the top 6 enriched KEGG pathways(PATHWAYS IN CANCER,WNT SIGNALING PATHWAY,NEUROTROPHIN SIGNALING PATHWAY,FOCAL ADHESION,MAPK SIGNALING PATHWAY and AXON GUIDANCE)for the 2 modules were the same.Compared with the probe-wise test used by Shiah et al.,we took the network approach and identified significant OSCC-associated miRNA modules,which could help uncover the mechanism that miRNAs interplay each other to contribute to OSCC.Gene expression profiles of OSCC have been analyzed by means of WGCNA for data with independent samples in previous studies.In our study,we optimized the general WGNCA pipeline to make it suitable for the data form paired design.We used a linear mixed model to account for the within-pair correlation instead of Pearson correlation.