HotSpotAnnotations—a database for hotspot mutations and annotations in cancer

Abstract

Abstract Hotspots, recurrently mutated DNA positions in cancer, are thought to be oncogenic drivers because random chance is unlikely and the knowledge of clear examples of oncogenic hotspots in genes like BRAF, IDH1, KRAS and NRAS among many other genes. Hotspots are attractive because provide opportunities for biomedical research and novel treatments. Nevertheless, recent evidence, such as DNA hairpins for APOBEC3A, suggests that a considerable fraction of hotspots seem to be passengers rather than drivers. To document hotspots, the database HotSpotsAnnotations is proposed. For this, a statistical model was implemented to detect putative hotspots, which was applied to TCGA cancer datasets covering 33 cancer types, 10 182 patients and 3 175 929 mutations. Then, genes and hotspots were annotated by two published methods (APOBEC3A hairpins and dN/dS ratio) that may inform and warn researchers about possible false functional hotspots. Moreover, manual annotation from users can be added and shared. From the 23 198 detected as possible hotspots, 4435 were selected after false discovery rate correction and minimum mutation count. From these, 305 were annotated as likely for APOBEC3A whereas 442 were annotated as unlikely. To date, this is the first database dedicated to annotating hotspots for possible false functional hotspots.