Expression profiling targeting chromosomes for tumor classification and prediction of clinical behavior

Abstract

Tumors are associated with altered or deregulated gene products that affect critical cellular functions. Here we assess the use of a global expression profiling technique that identifies chromosome regions corresponding to differential gene expression, termed comparative expressed sequence hybridization (CESH). CESH analysis was performed on a total of 104 tumors with a diagnosis of rhabdomyosarcoma, leiomyosarcoma, prostate cancer, and favorable-histology Wilms tumors. Through the use of the chromosome regions identified as variables, support vector machine analysis was applied to assess classification potential, and feature selection (recursive feature elimination) was used to identify the best discriminatory regions. We demonstrate that the CESH profiles have characteristic patterns in tumor groups and were also able to distinguish subgroups of rhabdomyosarcoma. The overall CESH profiles in favorable-histology Wilms tumors were found to correlate with subsequent clinical behavior. Classification by use of CESH profiles was shown to be similar in performance to previous microarray expression studies and highlighted regions for further investigation. We conclude that analysis of chromosomal expression profiles can group, subgroup, and even predict clinical behavior of tumors to a level of performance similar to that of microarray analysis. CESH is independent of selecting sequences for interrogation and is a simple, rapid, and widely accessible approach to identify clinically useful differential expression.