Gene Expression Profiling of Ewing Sarcoma Tumors Reveals the Prognostic Importance of Tumor-Stromal Interactions: A Report from the Children's Oncology Group

J Pathol Clin Res. 2015 Apr;1(2):83-94. doi: 10.1002/cjp2.9.

Abstract

Relapse of Ewing sarcoma (ES) can occur months or years after initial remission and salvage therapy for relapsed disease is usually ineffective. Thus, there is great need to develop biomarkers that can predict which patients are at risk for relapse so that therapy and post-therapy evaluation can be adjusted accordingly. For the current study we performed whole genome expression profiling on two independent cohorts of clinically annotated ES tumors in an effort to identify and validate prognostic gene signatures. ES specimens were obtained from the Children's Oncology Group (COG) and whole genome expression profiling performed using Affymetrix Human Exon 1.0 ST arrays. Lists of differentially expressed genes between survivors and non-survivors were used to identify prognostic gene signatures. An independent cohort of tumors from the Euro-Ewing cooperative group was similarly analyzed as a validation cohort. Unsupervised clustering of gene expression data failed to segregate tumors based on outcome. Supervised analysis of survivors vs. non-survivors revealed a small number of differentially expressed genes and several statistically significant gene signatures. Gene specific enrichment analysis (GSEA) demonstrated that integrin and chemokine genes were associated with survival in tumors where stromal contamination was present. Tumors that did not harbor stromal contamination showed no association of any genes or pathways with clinical outcome. Our results reflect the challenges of performing RNA-based assays on archived bone tumor specimens. In addition, they reveal a key role for tumor stroma in determining ES prognosis. Future biologic and clinical investigations should focus on elucidating the contribution of tumor:microenvironment interactions on ES progression and response to therapy. Key words: ES, gene expression profiling, prognostic signature.