Litcius/Paper detail

Selection of Oncogenic Mutant Clones in Normal Human Skin Varies with Body Site

Joanna C. Fowler, Charlotte King, Chris Bryant, Michael W.J. Hall, Roshan Sood, Swee Hoe Ong, Eleanor Earp, David Fernández‐Antorán, Jonas Koeppel, Stefan C. Dentro, David Shorthouse, Amer Durrani, Kate Fife, Edward Rytina, Doreen Milne, Amit Roshan, Krishnaa Mahububani, Kourosh Saeb‐Parsy, Benjamin A. Hall, Moritz Gerstung, Philip H. Jones

2020Cancer Discovery101 citationsDOIOpen Access PDF

Abstract

Abstract Skin cancer risk varies substantially across the body, yet how this relates to the mutations found in normal skin is unknown. Here we mapped mutant clones in skin from high- and low-risk sites. The density of mutations varied by location. The prevalence of NOTCH1 and FAT1 mutations in forearm, trunk, and leg skin was similar to that in keratinocyte cancers. Most mutations were caused by ultraviolet light, but mutational signature analysis suggested differences in DNA-repair processes between sites. Eleven mutant genes were under positive selection, with TP53 preferentially selected in the head and FAT1 in the leg. Fine-scale mapping revealed 10% of clones had copy-number alterations. Analysis of hair follicles showed mutations in the upper follicle resembled adjacent skin, but the lower follicle was sparsely mutated. Normal skin is a dense patchwork of mutant clones arising from competitive selection that varies by location. Significance: Mapping mutant clones across the body reveals normal skin is a dense patchwork of mutant cells. The variation in cancer risk between sites substantially exceeds that in mutant clone density. More generally, mutant genes cannot be assigned as cancer drivers until their prevalence in normal tissue is known. See related commentary by De Dominici and DeGregori, p. 227. This article is highlighted in the In This Issue feature, p. 211

Topics & Concepts

MutantSelection (genetic algorithm)BiologyGeneticsComputational biologyMutationGeneComputer scienceArtificial intelligenceCancer Genomics and DiagnosticsMolecular Biology Techniques and ApplicationsCRISPR and Genetic Engineering