Exon-based clustering of murine breast tumor transcriptomes reveals alternative exons whose expression is associated with metastasis

Abstract

In the field of bioinformatics, exon profiling is a developing area of disease-associated transcriptome analysis. In this study, we performed a microarray-based transcriptome analysis at the single exon level in mouse 4T1 primary mammary tumors with different metastatic capabilities. A novel bioinformatics platform was developed that identified 679 genes with differentially expressed exons in 4T1 tumors, many of which were involved in cell morphology and movement. Of 152 alternative exons tested by reverse transcription-PCR, 97 were validated as differentially expressed in primary tumors with different metastatic capability. This analysis revealed candidate progression genes, hinting at variations in protein functions by alternate exon usage. In a parallel effort, we developed a novel exon-based clustering analysis and identified alternative exons in tumor transcriptomes that were associated with dissemination of primary tumor cells to sites of pulmonary metastasis. This analysis also revealed that the splicing events identified by comparing primary tumors were not aberrant events. Lastly, we found that a subset of differentially spliced variant transcripts identified in the murine model was associated with poor prognosis in a large clinical cohort of patients with breast cancer. Our findings illustrate the utility of exon profiling to define novel theranostic markers for study in cancer progression and metastasis.