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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.
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http://dx.doi.org/10.1038/s41467-023-40022-5 | DOI Listing |
The addition of CDK4/6 inhibitors to endocrine therapy has significantly improved outcomes in HR+/HER2- breast cancer. However, variable patient responses and acquired resistance remain a clinical challenge. We therefore defined the comprehensive molecular response to palbociclib, the most clinically used CDK4/6 inhibitor.
View Article and Find Full Text PDFFront Oncol
August 2025
Tennessee Valley Healthcare System (TVHS) Department of Veterans Affairs, Nashville, TN, United States.
Introduction: Inhibitors of cyclin-dependent kinase 4 and 6 (CDK4/6) are approved for the treatment of locally advanced or metastatic breast cancer, but not for melanoma.
Methods: In this study, we evaluated the effectiveness of the CDK4/6 inhibitor, palbociclib, the CDK2 inhibitor, PF-07104091, the dual CXCR1 and CXCR2 (CXCR1/2) antagonist, SX-682, and the combination of these inhibitors for effective treatment of melanoma in preclinical models.
Results: Both palbociclib and SX-682 inhibited the growth of BRAF/NRAS B16-F10 and NRAS 1014 melanoma tumors and in both models, SX-682 created a more anti-tumor immune microenvironment.
ESMO Open
September 2025
SOLTI Cancer Research Group, Barcelona, Spain; Department of Medical Oncology, 12 de Octubre University Hospital, Madrid, Spain; Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, Spain; Medical Oncology Department, HM Hospitales, Madrid, Spain. Electronic address: eva.ci
Background: The SOLTI-1303-PATRICIA trial (NCT02448420) is a phase II study investigating palbociclib and trastuzumab, with or without endocrine therapy, in hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC). This manuscript presents final overall survival (OS) results and biomarker analyses.
Patients And Methods: Patients previously treated with trastuzumab and two to four regimens were eligible.
EMBO Mol Med
August 2025
Aix Marseille University, INSERM, CNRS, Institut Paoli-Calmettes, CRCM-Cancer Research Center of Marseille, Marseille, France.
The heterogeneity of leukemic cells is the main cause of resistance to therapy in acute myeloid leukemia (AML). Consequently, innovative therapeutic approaches are critical to target a wide spectrum of leukemic clones, regardless of their genetic and non-genetic complexity. In this report, we leverage the vulnerability of AML cells to CDK6 to identify a combination therapy capable of targeting common biological processes shared by all leukemic cells, while sparing non-transformed cells.
View Article and Find Full Text PDFPLoS Comput Biol
August 2025
Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina, United States of America.
Data from cell viability assays, which measure cumulative division and death events in a population and reflect substantial cellular heterogeneity, are widely available. However, interpreting such data with mechanistic computational models is hindered because direct model/data comparison is often muddled. We developed an algorithm that tracks simulated division and death events in mechanistically-detailed single-cell lineages to enable such a model/data comparison and suggest causes of cell-cell drug response variability.
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