Molecular characteristics of BRCA1/2 and PALB2 mutations in pancreatic ductal adenocarcinoma
Open Access
- 1 January 2020
- journal article
- research article
- Published by Elsevier BV in ESMO Open
- Vol. 5 (6), e000942
- https://doi.org/10.1136/esmoopen-2020-000942
Abstract
Introduction Poly-(ADP)-ribose polymerase (PARP) inhibitors are successfully used for treatment of BRCA-mutated (mut) breast cancers and are under extensive evaluation for BRCA- and PALB2-mutated pancreatic ductal adenocarcinoma (PDAC). However, the optimal treatment regimen for BRCA/PALB2-mutated PDCA has yet to be established. Moreover, limited data are available on the association of BRCA/PALB2 gene alterations with other comutations and immunological biomarkers. Material and methods Tumour samples of 2818 patients with PDAC were analysed for BRCA1/2 PALB2 mutations and other genes by next-generation sequencing (NGS) (MiSeq on 47 genes, NextSeq on 592 genes). TMB was calculated based on somatic non-synonymous missense mutations. MSI-H/dMMR was evaluated by NGS, and PD-L1 expression was determined using immunohistochemistry. Results In 4.2% (n=124) of all PDAC samples BRCA mutations have been detected. BRCA2 mutations were more commonly observed than BRCA1 mutations (3.1%(n=89) vs 1.1% [n=35], p1.0% (BRCA: 21.8% vs wt 11.2%, pPALB2: 0.0% vs 12.4 %, p=0.38) and high TMB (BRCA: mean 8.7 vs 6.5 mut/MB, pPALB2: 10.6 mut/Mb vs 6.6 mut/Mb, p=0.0007). Also, PD-L1 expression and TMB differed between BRCA and PALB2 mutation and wt samples in MSS tumours (pBRCA-mutated and PALB2-mutated PDACs were characterised by a different mutational profile than was observed in wt tumours. Conclusions BRCA and PALB2 mutations were found in a significant subgroup of PDACs. These mutations were associated with a distinct molecular profile potentially predictive for response to immune-checkpoint inhibitor therapy. Therefore, these data provide a rationale to evaluate PARP inhibitors in combination with immune-checkpoint inhibitors in patients with BRCA/PALB2-mutated PDAC.Keywords
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