Develop novel visualisations of genomic rearrangements in cancer
Finding novel ways to characterize and visualize genomic changes in cancer
Cancer results from alterations in DNA. Substantial evidence shows that the DNA of tumor cells contains a range of alterations, ranging from point mutations (changes in a single base pair) to large chromosomal alterations. The latter includes deletions and chromosomal translocations in which a part of one chromosome is transferred to (or exchanged for) another part on another chromosome. When such alterations accumulate over time, the cells sometimes acquire the ability to proliferate uncontrolled (or, if one likes, loose the ability to control cell growth) resulting in cancer.
When sections of DNA are lost in the genome, and others are duplicated, and many such alterations (often overlapping) are accumulated over time, the result can be a very messy genome. Small parts of one chromosome may be inserted into multiple sites on several other chromosomes, and the resulting chromosomes may bear little resemblance with any of the original chromosomes.
A compact way of describing the accumulated effect of such alterations, is to measure for several genomic loci (where 'loci' now refers to positions in a normal genome) how many copies are present in the cell of the DNA normally present at these loci. So, for example, a copy number of two would mean that two copies of DNA are present (which is what we would expect in a normal genome for chromosomes 1-22, and for chromosome X in females). A copy number of zero would mean that no copies of DNA are present, hence both copies present in the normal genome are lost. A copy number of four would mean that two extra copies are present (which may be located anywhere within the cancer cell's genome). With present technologies, one may measure the copy number at millions of genomic loci in a cancer cell (or pool of cancer cells). Such copy number data form the basis for the master thesis described here.
The purpose of the thesis project will be (a) to implement methods for compact whole-genome characterization of a cancer cell's copy number profile; (b) if possible, as the last part of the thesis project, to suggest novel methods for such characterization; (c) based on available data (from Norway and abroad) and the above characteristics seek to classify tumors into clinically different subgroups (e.g. aggressive and non-aggressive). The implementation language will be R. No previous knowledge of biology is required for this project. Some knowledge of statistics is desirable (but now an absolute requirement).
The project will be closely coordinated with the CARMA (Copy-number Aberration Regional Mapping Algorithms) project which is an ongoing activity involving researchers at the University of Oslo, Oslo University Hospital, and the Sanger Institute (UK).