TCGA PanCanAtlas data analysis suggests multiple possibilities for personalized cancer therapy

Personalized cancer medicine holds promise for the future of cancer treatment. The key to success is the knowledge of exact molecular alterations that drive tumorigenesis in a given patient, so that a suitable targeted therapy can be selected. However, the extent of such alterations, i.e. number of various kinds of driver mutations per patient, is still not known. We have utilized the largest database of human cancer mutations – TCGA PanCanAtlas, multiple popular algorithms for cancer driver prediction and several custom scripts to estimate the number of various kinds of driver mutations in primary tumors. We have found that there are on average 19.6 driver mutations per patient’s tumor, of which 2.4 are hyperactivating SNA mutations in oncogenes, 9.2 are CNA amplifications of oncogenes, 0.6 have both in the same oncogene, 0.2 are homozygous inactivating SNA mutations in tumor suppressors, 1.1 have inactivating SNA mutation in one allele and CNA deletion in the other allele of a tumor suppressor, 1.5 are driver chromosome losses, 2 are driver chromosome gains, 1 is driver chromosome arm loss, and 1.6 are driver chromosome arm gains. The number of driver mutations per tumor gradually increased with age, from 12.5 for <25 y.o. to 23.6 for >85 y.o. There was no big difference between genders (19.9 in males vs 19.2 in females). The number of driver mutations per tumor varied strongly between cancer types, from 1.5 in thyroid carcinoma to 43 in lung squamous cell carcinoma. Overall, our results provide valuable insights into the extent of driver alterations in tumors and suggest that multiple possibilities to choose a suitable targeted therapy exist in each patient.