Metabolomics

Dataset Information

0

Oxidative phosphorylation is a metabolic vulnerability of endocrine therapy and palbociclib resistant metastatic breast cancers


ABSTRACT: Resistance to endocrine treatments and CDK4/6 inhibitors is considered a near-inevitability in most patients with estrogen receptor positive breast cancers (ER + BC). By genomic and metabolomics analyses of patients' tumours, metastasis-derived patient-derived xenografts (PDX) and isogenic cell lines we demonstrate that a fraction of metastatic ER + BC is highly reliant on oxidative phosphorylation (OXPHOS). Treatment by the OXPHOS inhibitor IACS-010759 strongly inhibits tumour growth in multiple endocrine and palbociclib resistant PDX. Mutations in the PIK3CA/AKT1 genes are significantly associated with response to IACS-010759. At the metabolic level, in vivo response to IACS-010759 is associated with decreased levels of metabolites of the glutathione, glycogen and pentose phosphate pathways in treated tumours. In vitro, endocrine and palbociclib resistant cells show increased OXPHOS dependency and increased ROS levels upon IACS-010759 treatment. Finally, in ER + BC patients, high expression of OXPHOS associated genes predict poor prognosis. In conclusion, these results identify OXPHOS as a promising target for treatment resistant ER + BC patients.

INSTRUMENT(S): Q Exactive

SUBMITTER: Elisabetta Marangoni  Emily Pepper 

PROVIDER: MTBLS3342 | MetaboLights | 2023-06-27

REPOSITORIES: MetaboLights

altmetric image

Publications


Resistance to endocrine treatments and CDK4/6 inhibitors is considered a near-inevitability in most patients with estrogen receptor positive breast cancers (ER + BC). By genomic and metabolomics analyses of patients' tumours, metastasis-derived patient-derived xenografts (PDX) and isogenic cell lines we demonstrate that a fraction of metastatic ER + BC is highly reliant on oxidative phosphorylation (OXPHOS). Treatment by the OXPHOS inhibitor IACS-010759 strongly inhibits tumour growth in multipl  ...[more]

Similar Datasets

2011-11-01 | E-GEOD-28987 | biostudies-arrayexpress
2023-07-24 | GSE237769 | GEO
2023-07-24 | GSE237768 | GEO
2021-12-12 | GSE171073 | GEO
2021-12-12 | GSE171072 | GEO
2021-12-12 | GSE171071 | GEO
2021-12-12 | GSE171070 | GEO
2021-12-12 | GSE171069 | GEO
2021-12-12 | GSE171066 | GEO
2023-05-16 | GSE176534 | GEO