Robust unmixing of tumor states in array comparative genomic hybridization data

Motivation: Tumorigenesis is an evolutionary process by which tumor cells acquire sequences of mutations leading to increased growth, invasiveness, and eventually metastasis. It is hoped that by identifying the common patterns of mutations underlying major cancer sub-types, we can better understand the molecular basis of tumor development and identify new diagnostics and therapeutic targets. This goal has motivated several attempts to apply evolutionary tree reconstruction methods to assays of tumor state. Inference of tumor evolution is in principle aided by the fact that tumors are heterogeneous, retaining remnant populations of different stages along their development along with contaminating healthy cell populations. In practice, though, this heterogeneity complicates interpretation of tumor data because distinct cell types are conflated by common methods for assaying tumor state. We previously proposed a method to computationally infer cell populations from measures of tumor-wide...

• Type: Journal
• Year: 2010
• Where: BIOINFORMATICS
• Authors: David Tolliver, Charalampos E. Tsourakakis, Ayshwarya Subramanian, Stanley Shackney, Russell Schwartz
• Keywords: BIOINFORMATICS 2010, Tumor, Tumor Cells, Tumor States