Chapter title |
Digital PCR of Genomic Rearrangements for Monitoring Circulating Tumour DNA.
|
---|---|
Chapter number | 27 |
Book title |
Circulating Nucleic Acids in Serum and Plasma – CNAPS IX
|
Published in |
Advances in experimental medicine and biology, October 2016
|
DOI | 10.1007/978-3-319-42044-8_27 |
Pubmed ID | |
Book ISBNs |
978-3-31-942042-4, 978-3-31-942044-8
|
Authors |
Hongdo Do, Daniel Cameron, Ramyar Molania, Bibhusal Thapa, Gareth Rivalland, Paul L. Mitchell, Carmel Murone, Thomas John, Anthony Papenfuss, Alexander Dobrovic, Do, Hongdo, Cameron, Daniel, Molania, Ramyar, Thapa, Bibhusal, Rivalland, Gareth, Mitchell, Paul L, Murone, Carmel, John, Thomas, Papenfuss, Anthony, Dobrovic, Alexander, Mitchell, Paul L. |
Editors |
Peter B. Gahan, Michael Fleischhacker, Bernd Schmidt |
Abstract |
Identifying circulating tumour DNA (ctDNA) for monitoring of cancer therapy is dependent on the development of readily designed, sensitive cancer-specific DNA markers. Genomic rearrangements that are present in the vast majority of cancers provide such markers.Tumour DNA isolated from two fresh-frozen lung tumours underwent whole genome sequencing. Genomic rearrangements were detected using a new computational algorithm, GRIDSS. Four genomic rearrangements from each tumour were chosen for further study using rearrangement-specific primers. Six of the eight rearrangements tested were identified as tumour-specific, the remaining two were present in the germline. ctDNA was quantified using digital PCR for the tumour genomic rearrangements in patient blood. Interestingly, one of the patients had no detectable ctDNA either prior to or post surgery although the rearrangements were readily detectable in the tumour DNA.This study demonstrates the feasibility of using digital PCR based on genomic rearrangements for the monitoring of minimal residual disease. In addition, whole genome sequencing provided further information enabling therapeutic choices including the identification of a cryptic EGFR exon 19 deletion in one patient and the identification of a high somatic mutation load in the other patient. This approach can be used as a model for all cancers with rearranged genomes. |
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