Exon-based clustering of tumor transcriptomes reveals alternative exons associated with metastasis in breast cancer

ABSTRACT: Exonic profiling is an emerging topic in disease-associated transcriptome analysis, but is still facing major limitations. In this study, we performed a microarray-based analysis of the transcriptome at the exon level of mouse primary mammary tumors having different abilities to give rise to metastases. First, we developed a bioinformatics platform and used a stringent algorithm to identify 679 genes with differentially expressed exons in primary tumors of the 4T1 mouse model of mammary tumor progression. We tested 152 alternative exons by RT-PCR and validated 97 of them as being differentially expressed across primary tumors with different metastasis capability. Many of the 679 identified genes are involved in cellular morphology and movement. This analysis not only pointed to genes involved in cellular functions relevant to tumor progression, but also hinted to protein features targeted by variations at the exon level. Second, we developed a novel exon-based clustering analysis of tumor transcriptomes and identified alternative exons associated with the ability of cells to disseminate from primary mammary tumors into the lungs. A large set of these alternatively spliced exons was differentially expressed across normal tissues and/or conserved during evolution. These data indicated that the splicing events identified by comparing primary tumors were not aberrant events. Finally, we demonstrated that a set of differentially expressed variants, which we identified in the murine model, were associated with poor prognosis in a large cohort of breast cancer patients. In conclusion, this approach constitutes a valuable resource for both the understanding and the development of prognosis/diagnosis markers of tumor metastatic potential.

ORGANISM(S): Mus musculus

PROVIDER: GSE19086 | GEO | 2009/11/19

SECONDARY ACCESSION(S): PRJNA120501

REPOSITORIES: GEO