Abstract

BackgroundOsteosarcoma is a type of bone cancer casting huge threat to the human health worldwide. Previously, gene expression analyses were performed to identify biomarkers for cancer; however, systemic co-expression analysis for osteosarcoma is still in need. The aim of this study was to construct a gene co-expression network that predicts clusters of candidate genes associated with the pathogenesis of osteosarcoma.MethodsHere, we extracted the large scale of datasets from the GEO database. With systematical approaches, we identified the co-expression modules by using weighted gene co-expression network analysis (WGCNA) and investigated the functional enrichments of important modules at GO and KEGG terms.ResultsFirst, seven co-expression modules, which contain different genes, were conducted for 2228 genes in the 22 human osteosarcoma samples. Then, correlation study showed that the hub genes between pairwise modules displayed great differences. Lastly, functional enrichments of the co-expression modules showed that the module 5 enriched in immune response, antigen processing, and presentation, which is in consistence with GO result. Therefore, we speculated that the module 5 may play a key role in the pathogenesis of osteosarcoma.ConclusionsHere, we speculated that genes of the module 5 were the essential genes that were associated to human osteosarcoma. Together, our findings not only provided outline of co-expression gene modules for human osteosarcoma, but also promoted the understanding of these modules at functional aspects.

Highlights

  • Osteosarcoma is a type of bone cancer casting huge threat to the human health worldwide

  • Data processing Datasets for weighted gene co-expression network analysis (WGCNA) related to osteosarcoma were obtained from the NCBI Gene Expression Omnibus (GEO) with accessing number GSE12512

  • Pre-processing of the osteosarcoma datasets To generate gene co-expression networks, the raw gene expression of osteosarcoma datasets were downloaded from the GEO data repository

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Summary

Introduction

Osteosarcoma is a type of bone cancer casting huge threat to the human health worldwide. Gene expression analyses were performed to identify biomarkers for cancer; systemic coexpression analysis for osteosarcoma is still in need. Osteosarcoma (OS), the most common primary bone malignancy, has an overall incidence of 0.2–3/100000 per year. In the age group of 15–19 years, osteosarcoma is even more common with an incidence of 0.8–11/ 100,000 per year globally [1, 2]. Despite its rarity, it was reported as the third most common cancer in adolescence, occurring only less frequently than brain tumor and lymphomas in this age group.

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