Cancer Diagnostics

Despite the 15 million lines of code in the Android operating system, sudden and irrecoverable smartphone crashes are rare. One important source of this reliability is decades of computer science research into how to debug these systems, resulting in methods that can pinpoint a single problematic line of code in a system that is otherwise too complex for humans to fully understand. We are so good at doing this that the tenets of our society (such as food, safety, and infrastructure) are practically built on it; there is a 94% chance that you own a smartphone. Despite our unprecedented progress at pinpointing errors in computer code, mystery still surrounds how errors in the genetic code arise in cancer cells.


Somatic copy number aberrations (SCNAs) are genomic amplicifcations or deletions, and they are prevalent in the majority of cancers. However, pinpointing the cause from the myriad of possible defects in accurate cell division has not yet been achieved with current methods. This research draws inspiration from complex system design and applies it to cancer cells. By treating cancer as a bug in software running on biological hardware, we can use the same logic used by software developers to understand how errors in cellular mechanisms lead to cancer. Our method will interpret the complex patterns of SCNAs in a cancer cell to easily and rapidly determine whether a mechanism (such as DNA replication) is disrupted, thus identifying a pathway for targeted, personalised treatment to improve patient survival.  This project is ongoing and is in a rapid state of growth - check back soon for more details!



Barts Cancer Institute