Human tumours develop through the accumulation of mutations in their DNA. The process by which mutations accrue has a random component, meaning that individual cells within a tumour can acquire different mutations, thus responding differently to therapy or acquiring different abilities to invade and spread. Genetic diversity within tumours is rarely considered in treatment protocols, yet it contributes to drug resistance, spread and disease progression.
Recent breakthroughs in DNA sequencing technology have enabled researchers to precisely decode the genomes of individual tumour cells. Translating single-cell sequencing data into improved understanding of tumour evolution and clinically actionable insights requires both automated computational methods for data analysis and software systems that enable researchers to “see” their data. Although the computational methods are under active development, there are no tools to effectively visualize the millions of genomes that exist in a single tumour.
Dr. Sohrab Shah of the University of British Columbia is leading a team to address this analysis bottleneck by introducing highly scalable search-engine technology, called Elasticsearch, to the field of single-cell genomics. The team will evaluate for the first time the ability of Elasticsearch to drive real-time interactive visual exploration of single-cell cancer genomics data. This technology may have immediate impact in the international cancer research community, where it has potential to accelerate data interpretation and discovery and reveal insights into tumour composition and dynamics. Ultimately their work may be translated towards understanding how the genomes of individual tumour cells influence their response to treatments, revealing mechanisms of resistance and new therapeutic targets.