RT Journal Article
SR Electronic
T1 Prominent features of the amino acid mutation landscape in cancer
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 136002
DO 10.1101/136002
A1 Zachary A. Szpiech
A1 Nicolas B. Strauli
A1 Katharine A. White
A1 Diego Garrido Ruiz
A1 Matthew P. Jacobson
A1 Diane L. Barber
A1 Ryan D. Hernandez
YR 2017
UL http://biorxiv.org/content/early/2017/07/24/136002.abstract
AB Cancer can be viewed as a set of different diseases with distinctions based on tissue origin, driver mutations, and genetic signatures. Accordingly, each of these distinctions have been used to classify cancer subtypes and to reveal common features. Here, we present a different analysis of cancer based on amino acid mutation signatures. Non-negative Matrix Factorization and principal component analysis of 29 cancers revealed six amino acid mutation signatures, including four signatures that were dominated by either arginine to histidine (Arg>His) or glutamate to lysine (Glu>Lys) mutations. Sample-level analyses reveal that while some cancers are heterogeneous, others are largely dominated by one type of mutation. Using a non-overlapping set of samples from the COSMIC somatic mutation database, we validate five of six mutation signatures, including signatures with prominent arginine to histidine (Arg>His) or glutamate to lysine (Glu>Lys) mutations. This suggests that our classification of cancers based on amino acid mutation patterns may provide avenues of inquiry pertaining to specific protein mutations that may generate novel insights into cancer biology.