| dc.description.abstract | The potential of circulating tumour DNA (ctDNA) for tumour monitoring in pancreatic ductal
adenocarcinoma (PDAC) has not been fully realised beyond mutation tracking of known KRAS
variants. Here, we aimed to characterise and track patient-specific somatic ctDNA variants from
an exploratory cohort of 9 patients with PDAC, to assess longitudinal changes in disease burden
and explore the landscape of actionable alterations.
We followed 3 patients with resectable disease and 6 patients with unresectable disease,
including 6 patients with >3 serial follow-up samples, of whom 2 are rare long survivors (>5 years).
Whole exome sequencing was performed on tumour and germline gDNA, and plasma ctDNA
(n=26) collected over a ~2-year period from diagnosis through treatment to death (n=5) or final
follow-up (n=4). Plasma from 3 chronic pancreatitis cases was used to differentiate ctDNA
mutations from variants in benign pancreatic disease.
ctDNA mutations were identified within known PDAC driver genes, (KRAS, TP53, SMAD4,
CDKN2A), as well as multiple patient-specific variants within alternative cancer drivers (NRAS,
HRAS, MTOR, ERBB2, EGFR, PBRM1), with a trend towards higher overall mutation loads in
advanced disease. Prognostically relevant structural alterations were detected across tumour and
ctDNA, including amplifications at ERBB2 co-localising with kataegis events and KRAS copy
number gains co-occurring with somatic KRAS G12 variants. ctDNA alterations with potential for
therapeutic actionability were identified across all patients, including DNA damage repair (DDR)
variants predictive of response to platinum chemotherapy. Longitudinal tracking in patients with >3 serial plasma samples demonstrated that ctDNA fractional 1 abundances and clonal trends were
consistent with CA19-9 measurements and/or clinically reported disease burden in most cases.
These findings show that broad genomic profiling can enable extensive characterisation of tumour-derived alterations though ctDNA in PDAC, leading to the identification of important
molecular features with clinical implications for prognosis, monitoring and predicting treatment
response in patients. | en_US |
