Abstract
Abstract Massively parallel sequencing using Next Gen sequencing approaches have opened a new window into our understanding of the molecular architecture of breast cancer. A significant advantage of these technologies are that they are digital in nature because the measurement technology begins with single DNA molecules attached to a substrate. As a result, not only do these technologies provide an efficient means to identify somatic mutations, information is also provided on the frequency with which any given mutation is observed within the population of DNA molecules in the sample under analysis. The first and most striking feature of Next Gen analysis of breast cancer is the large numbers of somatic mutations that have been identified. Genome wide, thousands of mutations can be present in a single tumor. While this finding generates immense complexity from the perspective of defining biological drivers versus passengers, it does open up a new opportunity to study variations in mutation frequency. In a perfectly monoclonal tumor with a diploid genome and no contaminating normal cell DNA the mutation frequencies generated by digital sequencing will be 50% for a heterozygous mutation or 100% for homozygous mutations. Very few breast cancers subjected to whole genome sequencing exhibit this pattern, rather mutations occur with a wide variation of frequencies from the detection limit, around 5%, through to 100%. Furthermore mutation frequency clustering often occurs, a phenomenon best explained by the presence of a repertoire of mutations present in a founder clone that are present in all tumors, combined with additional less common mutations that represent a subdominant or minority population of cells that have arisen through additional clonal outgrowth. In a multiclonal model one of the most critical questions is “which clone determines the prognosis?”. One way to begin to answer this question is to sequence tumors before and after therapy and to compare primary tumors versus metastases. In our initial experience of a patient with a basal-like breast cancer in which a whole cancer genome was generated from her primary, her subsequent brain metastasis and a mouse xenograft generated from the breast primary, there was clear evidence of a shift in mutation frequency primary to metastasis, suggesting the brain metastasis arose from a minor sub-clone. The mutational profile of the xenograft more closely resembled the metastasis rather than the primary, suggesting the grafting process captured the metastatic clone (1). In this invited lecture we will present an extension of our sequencing experiences with further human progenitor-mouse xenograft comparisons, comparisons between human primaries and paired metastases and also examples of ER+ breast cancer genomes obtained before and after neoadjuvant endocrine therapy. In all these experiments multiclonality appears to be the rule rather than the exception. The clinical and biological implications of these findings will be discussed. 1. Ding L, Ellis MJ, Li S, Larson DE, Chen K, Wallis JW, et al. Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature. 2010;464(7291):999–1005. PMCID: 2872544. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr MS1-3.
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