MRI-Based Imaging Predicts Chemotherapy Response in Ovarian Cancer Within 48 Hours
Key Insights
A novel MRI-based molecular imaging approach can differentiate ovarian cancer (search) subtypes and predict chemotherapy response rapidly.
Hyperpolarized carbon-13 imaging distinguishes between tumors receptive or resistant to Carboplatin in high-grade serous ovarian cancer (search) models.
The technique allows for personalized treatment decisions within days, potentially improving outcomes for ovarian cancer (search) patients.
A molecular imaging technique using magnetic resonance imaging (MRI) can distinguish between different types of ovarian cancer (search) and predict its response to chemotherapy within 48 hours, potentially enabling personalized treatment strategies. The method, detailed in a study published in Oncogene, utilizes hyperpolarized carbon-13 imaging to assess tumor metabolism and predict sensitivity to Carboplatin, a standard first-line chemotherapy drug.
Rapid Prediction of Treatment Response
The research demonstrates that hyperpolarized carbon-13 imaging can quickly determine whether a tumor is receptive or resistant to Carboplatin in cell models of high-grade serous ovarian cancer (search). This noninvasive imaging method could allow physicians to personalize treatment plans within days, a significant improvement over the current process that can take weeks or months.
According to senior researcher Kevin Brindle, PhD, a professor at the University of Cambridge, the technique allows for imaging a tumor before treatment to predict its likelihood of response and again immediately after treatment to confirm the response. This approach could help doctors select the most appropriate treatment for each patient and adjust it as necessary.
Metabolic Subtypes and Imaging
Ovarian cancer (search), a leading cause of cancer-related deaths in women, often presents as high-grade serous ovarian cancer with two metabolic subtypes: high OXPHOS and low OXPHOS. The high OXPHOS subtype exhibits increased expression of genes encoding electron transport chain components, increased oxygen consumption, and increased chemosensitivity. Conversely, the low OXPHOS subtype exhibits glycolytic metabolism and is more drug-resistant.
The study examined whether clinically applicable metabolic imaging methods could differentiate between gene copy number signatures and these metabolic subtypes. Researchers used patient-derived ovarian cancer (search) organoids and xenografts of high-grade serous ovarian cancer to detect early treatment response before changes in tumor volume occurred.
Hyperpolarized Carbon-13 Imaging vs. PET
The researchers found that patient-derived xenografts representative of different metabolic subtypes showed differences in glycolytic metabolism, detectable using hyperpolarized carbon-13 imaging. This technique involves injecting a labeled form of pyruvate and measuring its rate of metabolism into lactate. In contrast, positron emission tomography (PET) using fluorodeoxyglucose, a widely used clinical practice, did not show significant differences.
Amplification of the Myc (search) gene was identified as the likely mechanism driving increased lactate labeling in the low OXPHOS metabolic subtype. Both PET and hyperpolarized scans could detect response in a high OXPHOS tumor sensitive to Carboplatin and non-response in a low OXPHOS tumor resistant to the drug.
Clinical Implications and Future Trials
Brindle anticipates that hyperpolarized carbon-13 imaging will be trialed in ovarian cancer (search) within the next few years. The technique can assess the aggressiveness of an ovarian cancer tumor and evaluate multiple tumors in a patient, providing a more holistic assessment of disease prognosis and enabling the selection of the most appropriate treatment.
This imaging approach holds promise for improving treatment outcomes in ovarian cancer (search) by enabling rapid and personalized treatment decisions.