HIGH-GRADE serous ovarian cancer (HGSOC) exhibits two distinct metabolic subtypes, with high oxidative phosphorylation (OXPHOS) tumours showing greater chemosensitivity and low OXPHOS tumours demonstrating glycolytic metabolism and drug resistance. Advanced imaging techniques can differentiate these subtypes and detect their varying responses to chemotherapy.
HGSOC is the most aggressive subtype of ovarian cancer, with limited treatment options for drug-resistant cases. Metabolic profiling offers a promising avenue for understanding tumour behaviour and tailoring therapies. This study investigated the metabolic characteristics of HGSOC subtypes using patient-derived organoids, xenograft models, and advanced imaging. High OXPHOS tumours, characterised by increased expression of electron transport chain components and oxygen consumption, were compared with low OXPHOS tumours, which exhibit higher lactate dehydrogenase activity and monocarboxylate transporter 4 expression, favouring glycolysis.
Patient-derived organoids were implanted subcutaneously into xenografts to assess metabolism through hyperpolarised 13C magnetic resonance spectroscopy (MRS) of [1-13C]pyruvate and positron emission tomography (PET) with [18F]FDG. Low OXPHOS tumours showed significantly elevated lactate labelling in 13C MRS, reflecting enhanced glycolytic activity, while PET imaging showed no difference in glucose uptake between subtypes. Carboplatin treatment elicited a marked metabolic response in high OXPHOS xenografts, with early metabolic changes detectable by both imaging modalities, whereas low OXPHOS xenografts displayed no significant metabolic or therapeutic response.
These findings suggest that hyperpolarised 13C MRS can clinically distinguish low OXPHOS from high OXPHOS tumours in HGSOC and identify their differential treatment responses. This has important implications for clinical practice, as the metabolic profile of HGSOC tumours may guide treatment decisions and improve patient outcomes. Developing non-invasive imaging biomarkers such as 13C MRS could enable real-time monitoring of therapy efficacy and aid in stratifying patients for tailored treatments. Future research should focus on validating these techniques in clinical settings and exploring potential metabolic vulnerabilities in drug-resistant low OXPHOS tumours to identify novel therapeutic targets.
Abigail Craig, EMJ
Reference
Chia ML et al. Metabolic imaging distinguishes ovarian cancer subtypes and detects their early and variable responses to treatment. Oncogene. 2024. DOI: 10.1038/s41388-024-03231-w.
