Locus-specific databases (LSDBs) are curated compilations of sequence variants in genes associated with disease and have been invaluable tools for both basic and clinical research. These databases contain extensive information provided by the literature and benefit from manual curation by experts. Cancer genome sequencing projects have generated an explosion of data that are stored directly in centralized databases, thus possibly alleviating the need to develop independent LSDBs. A single cancer genome contains several thousand somatic mutations. However, only a handful of these mutations are truly oncogenic and identifying them remains a challenge. However, we can expect that this increase in data and the development of novel biocuration algorithms will ultimately result in more accurate curation and the release of stable sets of data. Using the evolution and content of the TP53 LSDB as a paradigm, it is possible to draw a model of gene mutation analysis covering initial descriptions, the accumulation and organization of knowledge in databases, and the use of this knowledge in clinical practice. It is also possible to make several assumptions on the future of LSDBs and how centralized databases could change the accessibility of data, with interfaces optimized for different types of users and adapted to the specificity of each region of the genome, coding or noncoding, associated with tumor development.