Grant: CIHR Fellowship

Lung cancer has the highest cancer-related mortality rate, with estimates of 26,100 new cases and 20,500 deaths in Canada and 1.59 million deaths worldwide during 2014. While targeted therapies for gene mutations have improved lung cancer survival, regrettably, the survival rate beyond 5 years is still low. Cancer is a genomic disease. A tumour can evolve over time by acquiring new DNA mutations that confer fitness advantages. Cancer cells (or clones) with these new mutations will expand to co-exist with predecessor cells, leading to clonal diversity and heterogeneity. Dissecting this clonal diversity to understand its clinical impact, such as treatment resistance, has been underappreciated. To address this, I propose to study the patterns of tumour evolution from a large cohort of lung cancers. I will design, develop and apply computational methods to identify mutations from whole genome sequences. Next, using data generated from state-of-the-art technologies, including assays for analyzing the genomes in single isolated cancer cells, I will reconstruct the evolutionary relationships between tumour clones. The outcome of this study will feature new biological models of tumour evolution that will have an immediate impact for identifying clinically actionable targets and guide future therapeutic strategies. Also, the proposed methodology will be applicable to future studies of other cancer types.