DOTS-Finder: a comprehensive tool for assessing driver genes in cancer genomes

Table 3 Inference of biological classification by structural effect of mutational landscape

		Structural landscape
	Missense	Clustered	No	Clustered	Any
	Truncating	No	Diffuse	Diffuse	Clustered
Biological classification	Oncogene	Typical (gain-of-function) for example, KRAS	None found	None found	Atypical (gain of function through loss of inhibition) for example, NPM1
	Tumor suppressor	Atypical (dominant negative, gain-of-function)	Typical (loss-of-function)	Atypical (possible dominant negative, gain-of-function*)	None found
	Tumor suppressor	for example, SMARCA4 in lymphoma	for example, RB1	for example, TP53 in UCEC or DNMT3A in AML	None found

Inferring the biological role of OGs and TSGs in cancer via the mutational landscape can lead to borderline results in the classification. While for the majority of known cancer genes there is a clear correspondence between the mutational landscape and the biological classification, other genes require a careful evaluation to assess their functional characteristics (Figure 4).
*A mixed mutational landscape with diffuse truncating and clustered missense in the same tumor type must be carefully analyzed. We should understand whether truncating and missense mutations are mutually exclusive and what is the allelic status (heterozygosity or homozygosity) of the two different patterns.

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