PT  - JOURNAL ARTICLE
AU  - Aleksey V. Belikov
TI  - Erlang distribution predicts the number of driver events for childhood and young adulthood cancers
AID  - 10.1101/231027
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 231027
4099  - http://biorxiv.org/content/early/2017/12/07/231027.short
4100  - http://biorxiv.org/content/early/2017/12/07/231027.full
AB  - It is assumed that cancers develop upon randomly acquiring (epi)mutations in driver genes, but their exact number for each cancer type is not known. I have recently shown that the age distribution of incidence for 20 most prevalent cancers of old age is closely approximated by the Erlang probability distribution. I then used it to predict the number of driver events for these cancer types, as it describes the probability of several successive random events occurring precisely by the given time. However, 4 other probability distributions out of 16 tested also provided acceptable fits to the incidence data, leaving some doubt about the validity of predictions. Here I show that the Erlang distribution is the only classical probability distribution that can adequately model the age distribution of incidence for all studied childhood/young adulthood cancers. This validates it as the universal law describing cancer development at any age and as a useful tool to predict the number of driver events for any cancer type.