Publications
Translating genomic risk into an early detection strategy for sarcoma
Abstract
Sarcomas have a strong genetic etiology, and the study of families affected by sarcomas has informed much of what we now understand of modern cancer biology. The recent emergence of powerful genetic technologies has been democratized by both astonishing reductions in costs and increased throughput over the past decade. The application of these technologies in clinics is revealing a previously unappreciated and rich landscape of genetic cancer risk. In addition to identifying previously unrecognised carriers of both known and new cancer risk mutations, the use of genome-wide association studies and massively parallel sequencing is cataloguing complex and polygenic risk patterns, which collectively may explain between 15-25% of apparently sporadic sarcoma cases. This information is increasingly being used to guide treatment choices, genetic counselling, reproductive decision-making and surveillance strategies. This is exemplified by Li-Fraumeni Syndrome, perhaps the most penetrant cancer syndrome known, in which sarcomas are common. The recent demonstration that whole body magnetic resonance imaging can identify surgically resectable cancers in up to one in ten individuals with Li-Fraumeni Syndrome has enormously transformed options for affected families. Taken together, parallel developments in genomics, therapeutics and imaging technologies promise to drive a closer engagement between genetics and multidisciplinary care of the sarcoma patient in the 21(st) century. This article is protected by copyright. All rights reserved.
Type | Journal |
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ISBN | 1098-2264 (Electronic) 1045-2257 (Linking) |
Authors | Ballinger, M. L.; Pinese, M.; Thomas, D. M. |
Responsible Garvan Author | Dr Mandy Ballinger |
Publisher Name | GENES CHROMOSOMES & CANCER |
Published Date | 2019-01-30 |
Published Volume | 58 |
Published Pages | 130-136 |
Status | Published in-print |
DOI | 10.1002/gcc.22697 |
URL link to publisher's version | https://www.ncbi.nlm.nih.gov/pubmed/30382615 |