Citations

Abstract Emerging evidence indicates that tumors can follow several evolutionary paths over a patient's disease course. With the use of serial genomic analysis of samples collected at different points during the disease course of 28 patients with multiple myeloma, we found that the genomes of standard-risk patients show few changes over time, whereas those of cytogenetically high-risk patients show significantly more changes over time. The results indicate the existence of 3 temporal tumor types, which can either be genetically stable, linearly evolving, or heterogeneous clonal mixtures with shifting predominant clones. A detailed analysis of one high-risk patient sampled at 7 time points over the entire disease course identified 2 competing subclones that alternate in a back and forth manner for dominance with therapy until one clone underwent a dramatic linear evolution. With the use of the Vk*MYC genetically engineered mouse model of myeloma we modeled this competition between subclones for predominance occurring spontaneously and with therapeutic selection.

Abstract Fusion genes and fusion gene products are widely employed as biomarkers and therapeutic targets in hematopoietic cancers, but their applications have yet to be appreciated in solid tumors. Here, we report the use of SnowShoes-FTD, a powerful new analytic pipeline that can identify fusion transcripts and assess their redundancy and tumor subtype-specific distribution in primary tumors. In a study of primary breast tumors, SnowShoes-FTD was used to analyze paired-end mRNA-Seq data from a panel of estrogen receptor (ER)+, HER2+, and triple-negative primary breast tumors, identifying tumor-specific fusion transcripts by comparison with mRNA-Seq data from nontransformed human mammary epithelial cell cultures plus the Illumina Body Map data from normal tissues. We found that every primary breast tumor that was analyzed expressed one or more fusion transcripts. Of the 131 tumor-specific fusion transcripts identified, 86 were “private” (restricted to a single tumor) and 45 were “redundant” (distributed among multiple tumors). Among the redundant fusion transcripts, 7 were unique to ER+ tumors and 8 were unique to triple-negative tumors. In contrast, none of the redundant fusion transcripts were unique to HER2+ tumors. Both private and redundant fusion transcripts were widely expressed in primary breast tumors, with many mapping to genomic loci implicated in breast carcinogenesis and/or risk. Our finding that some fusion transcripts are tumor subtype-specific suggests that these entities may be critical determinants in the etiology of breast cancer subtypes, useful as biomarkers for tumor stratification, or exploitable as cancer-specific therapeutic targets. Cancer Res; 72(8); 1921–8. ©2012 AACR.