Unknown

Dataset Information

0

SUMO pathway inhibition targets an aggressive pancreatic cancer subtype.


ABSTRACT: OBJECTIVE:Pancreatic ductal adenocarcinoma (PDAC) still carries a dismal prognosis with an overall 5-year survival rate of 9%. Conventional combination chemotherapies are a clear advance in the treatment of PDAC; however, subtypes of the disease exist, which exhibit extensive resistance to such therapies. Genomic MYC amplifications represent a distinct subset of PDAC with an aggressive tumour biology. It is clear that hyperactivation of MYC generates dependencies that can be exploited therapeutically. The aim of the study was to find and to target MYC-associated dependencies. DESIGN:We analysed human PDAC gene expression datasets. Results were corroborated by the analysis of the small ubiquitin-like modifier (SUMO) pathway in a large PDAC cohort using immunohistochemistry. A SUMO inhibitor was used and characterised using human and murine two-dimensional, organoid and in vivo models of PDAC. RESULTS:We observed that MYC is connected to the SUMOylation machinery in PDAC. Components of the SUMO pathway characterise a PDAC subtype with a dismal prognosis and we provide evidence that hyperactivation of MYC is connected to an increased sensitivity to pharmacological SUMO inhibition. CONCLUSION:SUMO inhibitor-based therapies should be further developed for an aggressive PDAC subtype.

SUBMITTER: Biederstadt A 

PROVIDER: S-EPMC7398468 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications


<h4>Objective</h4>Pancreatic ductal adenocarcinoma (PDAC) still carries a dismal prognosis with an overall 5-year survival rate of 9%. Conventional combination chemotherapies are a clear advance in the treatment of PDAC; however, subtypes of the disease exist, which exhibit extensive resistance to such therapies. Genomic MYC amplifications represent a distinct subset of PDAC with an aggressive tumour biology. It is clear that hyperactivation of MYC generates dependencies that can be exploited th  ...[more]

Similar Datasets

| S-EPMC7851129 | biostudies-literature
| S-EPMC3685283 | biostudies-literature
2019-01-01 | GSE119423 | GEO
| S-EPMC8408135 | biostudies-literature
| S-EPMC5290184 | biostudies-literature
| PRJNA489233 | ENA
2021-08-30 | GSE172356 | GEO
| S-EPMC8272721 | biostudies-literature
| S-EPMC8134763 | biostudies-literature
2023-10-12 | GSE223909 | GEO