You are currently viewing the abstract.
View Full TextLog in to view the full text
AAAS login provides access to Science for AAAS members, and access to other journals in the Science family to users who have purchased individual subscriptions.
Register for free to read this article
As a service to the community, this article is available for free. Existing users log in.
More options
Download and print this article for your personal scholarly, research, and educational use.
Buy a single issue of Science for just $15 USD.
Uncovering a tumor’s family tree
In the era of targeted anticancer drugs, correctly identifying the mutations in a tumor becomes an essential part of optimizing cancer treatment. This is not necessarily straightforward because tumors can contain both “driver” mutations, which control tumor growth and therefore should be blocked with specific drugs, and “passenger” mutations, which, as their name suggests, may not contribute to the progression of a tumor and are unlikely to be useful therapeutic targets. McGranahan et al. identified patterns of driver event evolution in a wide variety of tumor types, revealing specific patterns of mutations that will be important in the design of future therapeutic regimens for cancer.
Abstract
Deciphering whether actionable driver mutations are found in all or a subset of tumor cells will likely be required to improve drug development and precision medicine strategies. We analyzed nine cancer types to determine the subclonal frequencies of driver events, to time mutational processes during cancer evolution, and to identify drivers of subclonal expansions. Although mutations in known driver genes typically occurred early in cancer evolution, we also identified later subclonal “actionable” mutations, including BRAF (V600E), IDH1 (R132H), PIK3CA (E545K), EGFR (L858R), and KRAS (G12D), which may compromise the efficacy of targeted therapy approaches. More than 20% of IDH1 mutations in glioblastomas, and 15% of mutations in genes in the PI3K (phosphatidylinositol 3-kinase)–AKT–mTOR (mammalian target of rapamycin) signaling axis across all tumor types were subclonal. Mutations in the RAS–MEK (mitogen-activated protein kinase kinase) signaling axis were less likely to be subclonal than mutations in genes associated with PI3K-AKT-mTOR signaling. Analysis of late mutations revealed a link between APOBEC-mediated mutagenesis and the acquisition of subclonal driver mutations and uncovered putative cancer genes involved in subclonal expansions, including CTNNA2 and ATXN1. Our results provide a pan-cancer census of driver events within the context of intratumor heterogeneity and reveal patterns of tumor evolution across cancers. The frequent presence of subclonal driver mutations suggests the need to stratify targeted therapy response according to the proportion of tumor cells in which the driver is identified.
- Copyright © 2015, American Association for the Advancement of Science
