Computational methods for array CGH analysis for improved diagnosis of human cancers

Chromosomal instability is a hallmark of tumour cells in human cancer. Regions of chromosomal instability can have various forms including single point mutations, rearrangements, whole chromosome loss or duplication, or chromosomal segments containing DNA copy number change. The alterations change the expression of cellular constituents and eventually result in cells that do not function normally. Finding regions of chromosomal instability provides important locations in the human genome that are both symptomatic and diagnostic markers of various cancers. Recently developed techniques called array comparative genomic hybridization (aCGH) have allowed scientists an unprecedented high degree of resolution to detect regions of chromosomal instability in cancer patients. The experiments produce both a high volume of data and noisy signals that are not cleanly interpretable. Therefore, robust computational techniques must be developed that can automatically identify regions of chromosomal instability. Sohrab Shah is developing computational methods and statistical models that, given aCGH data for one or more patients, can accurately and reliably detect chromosomal aberrations. His research will first evaluate this method on standard data sets where the location of the aberrations are known, and then apply the method to three large scale genomic studies to discover chromosomal locations affected in lung, brain and lymphoma tumours. He will also assess the diagnostic utility of chromosomal alterations that are recurrent across patients and develop prototype diagnostic tests that may ultimately be put into clinical practice.