Carcinogenesis is typically driven by the accumulation of deleterious mutations. Combined with other clinical observations, driver mutations allow experts to discriminate between different types of cancer, which is essential to accurately predict prognoses of available treatments and to develop new ones. However, many types of cancer cause genetic instability, introducing a multitude of passenger mutations in afficted cells. Typical passenger mutations have no direct clinical relevance, but their abundance complicates the identification of driver mutations. Previous research has shown that some known driver genes do not always act in the expected pathological manner (e.g. KRAS and NPM1), whereas other genes do (e.g. MAP2K4). This research will attempt to identify possible driver mutations in the protein coding gene NPM1. Primary analysis was done using a mutation visualisation tool from cBioPortal and Python. Results show two mutation hotspots for NPM1 in acute myeloid leukaemia, but no other significant mutations. An interesting correlation between tissue expression rate of a protein coding gene and the types of cancer in which it is mutated was found.