Exploring novel strategies for assessing response to treatment in patients with advanced ovarian cancer, in particular the role and potential of non-haemopoetic circulating cells and DECT imaging

Abstract

Ovarian cancer is the fifth most common female cancer worldwide with many patients presenting at an advanced stage. Patients typically undergo surgery and chemotherapy but despite an aggressive upfront approach, they relapse within a few years. More is needed to understand what is the best way to manage ovarian cancer including can we learn more about the treatment response and offer a more tailored approach to cancer care. Here we looked at different aspects of the ovarian cancer, including the use of dual energy CT imaging and liquid biopsies as potential tools for prognosis. Both methods offer the potential to gain a better insight into ovarian cancer, including its management. In patients with cancer, the current gold standard is to use computed tomography (CT) imaging to assess response to treatment. This involves measuring cancer lesions at baseline and post treatment and then calculating the percentage change in size. This is then categorised into complete/ partial response/ stable disease or progressive disease, as per RECIST criteria. The use of Dual Energy CT (DECT) allows us to use iodine concentration as a potential surrogate marker of vascularity. Here we explore the role of iodine concentration and how this changes in cancer lesions to assess whether this can be used to predict treatment response in patients with high-grade serous ovarian cancer (HGSOC). Our results showed that iodine concentration was better at predicting progression free survival in comparison to RECIST and more sensitive at predicting early disease relapse (1). This indicates that iodine concentration maybe a suitable method of assessing response to treatment. We also looked at the use of liquid biopsies and whether we can identify circulating tumour cells (CCs) from blood samples using ImageStream immunofluorescence techniques (including high definition fluorescent microscopy; ImageStream). By collecting bloods samples from ovarian cancer patients on treatment at regular intervals, we were able to use that information to correlate this with response to treatment. Factors such as high tumour burden, responders/ non-responders and cancer stage all had an impact on the number of CCs. Typically, high tumour burden and advanced stage of ovarian cancer was associated with higher number of CCs. The number of CCs at the start and end of treatment also had a negative impact on survival outcomes, with the higher the number of CCs, the shorter the overall survival/ progression free survival. This suggests that presence of CCs maybe associated with early relapse and a risk factor for development of metastatic disease. Further analysis using immunofluorescence was carried out to look at the presence of RAD51 foci and PD-L1 in ovarian cancer patients. More than fifty percent of patients with high-grade serous ovarian cancer harbour defects in the homologous recombination repair pathway. When DNA is damaged, RAD51 foci form and this plays a vital role in the repair of double stranded DNA breaks. Here we show that high levels of RAD51 foci are associated with poorer survival outcomes and treatment resistance. We also showed BRCA mutant/ HRD positive patients had low numbers of RAD51 foci. This highlights that RAD51 may have a role as a potential marker of HRD and maybe used to assess treatment response and predict survival outcomes. We also studied the role of PD-L1 positivity in ovarian cancer and how this compares to matched FFPE tissue and CCs. We demonstrated that approximately 50% of patients were PD-L1 positive and there was good concordance between matched tissue and CCs. It was noted that heterogeneity was present in OC tissue and PD-L1 status changed over the course of treatment in a few patients. More work is needed but the results so far have been promising in potentially using CCs to test for PD-L1 positivity.