Uncovering the Hidden Molecular Signatures of Breast Cancer
Abstract
Breast cancer is a heterogeneous disease, consisting of at least five transcriptional subtypes described by distinct, but poorly understood, molecular profiles. As the cause, aggressiveness, and outcome vary greatly between patients, it is essential to characterize the different ways in which the disease can grow and spread. Transcriptional subtyping operates by capturing the "loudest" molecular events within a tumor. While these events are both biologically and clinically important, they only represent a fraction of the total cellular pathways and responses. Subtle information is overshadowed by these responses. Such information lies orthogonally to the subtypes, and may be of equal or greater clinical importance. We have constructed a framework to address this challenge. Our methodology is different from what has been done in the past, because it is able to break down tumors using individual signatures. The analysis is done on a large-scale, and does not require tumors to be binned into distinct classes. In a similar way, murine and cell-line models have been analyzed, allowing us to determine which models best reflect the human disease, and in what way. This is in turn allowing us to understand how different tumor processes work together, and to refine our models to better reflect the human disease. We?ve aimed to produce an open and accessible framework that will be used to quickly and thoroughly understand the processes that are at play in new tumour cases. This framework will have immediate research applications through the generation of better models for breast cancer. Ultimately, we intend for it to provide patients with more accurate, appropriate, and personalized treatments.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2013
- Accession Number
- ADA581641
Entities
People
- Robert Lesurf
Organizations
- McGill University