If mutation frequency, corrected for mutation context, gene length, and other parameters, cannot reliably identify modestly mutated driver genes, what can? In our experience, the best way to identify Mut-driver genes is through their pattern of mutation rather than through their mutation frequency. The patterns of mutations in well-studied oncogenes and tumor suppressor genes are highly characteristic and nonrandom. Oncogenes are recurrently mutated at the same amino acid positions, whereas tumor suppressor genes are mutated through protein-truncating alterations throughout their length (Fig. 4 and table S2A).
On the basis of these mutation patterns rather than frequencies, we can determine which of the 18,306 mutated genes containing a total of 404,863 subtle mutations that have been recorded in the Catalogue of Somatic Mutations in Cancer (COSMIC) database (30 (link)) are Mut-driver genes and whether they are likely to function as oncogenes or tumor suppressor genes. To be classified as an oncogene, we simply require that >20% of the recorded mutations in the gene are at recurrent positions and are missense (see legend to table S2A). To be classified as a tumor suppressor gene, we analogously require that >20% of the recorded mutations in the gene are inactivating. This “20/20 rule” is lenient in that all well-documented cancer genes far surpass these criteria (table S2A).
The following examples illustrate the value of the 20/20 rule. When IDH1 mutations were first identified in brain tumors, their role in tumorigenesis was unknown (2 (link), 31 (link)). Initial functional studies suggested that IDH1 was a tumor suppressor gene and that mutations inactivated this gene (32 (link)). However, nearly all of the mutations in IDH1 were at the identical amino acid, codon 132 (Fig. 4). As assessed by the 20/20 rule, this distribution unambiguously indicated that IDH1 was an oncogene rather than a tumor suppressor gene, and this conclusion was eventually supported by biochemical experiments (33 (link), 34 (link)). Another example is provided by mutations in NOTCH1. In this case, some functional studies suggested that NOTCH1 was an oncogene, whereas others suggested it was a tumor suppressor gene (35 (link), 36 (link)). The situation could be clarified through the application of the 20/20 rule to NOTCH1 mutations in cancers. In “liquid tumors” such as lymphomas and leukemias, the mutations were often recurrent and did not truncate the predicted protein (37 (link)). In squamous cell carcinomas, the mutations were not recurrent and were usually inactivating (38 (link)–40 (link)). Thus, the genetic data clearly indicated that NOTCH1 functions differently in different tumor types. The idea that the same gene can function in completely opposite ways in different cell types is important for understanding cell signaling pathways.