GLOBAL NEWS: OVARIAN CANCER RESEARCH

Rare cancers, like ovarian cancer disproportionately contribute to cancer-related deaths. This is generally attributed to knowledge and funding deficits for these rare, and often very complex cancers.

Thanks to a significant donation of $10 million, Cabrini Health in collaboration with Monash University hopes to bring cutting-edge genomic testing to Victorian cancer patients without the lengthy waiting period and high costs to patients.

The data generated via this newly funded program could lead to more targeted therapies for certain ovarian cancer subtypes.

Low Grade Serous Ovarian Cancer (LGSOC) is a rare and difficult to treat ovarian cancer that doesn’t respond well to standard chemotherapy. This study screened over 3,400 drugs to find ones that specifically target LGSOC cells, and identified several promising drugs that could lead to more personalised and effective treatments for this rare cancer in the future.  

Low-Grade Serous Ovarian Carcinoma (LGSOC) is a rare type of ovarian cancer, making up about 5-8% of all epithelial ovarian cancers. LGSOC is typically diagnosed in younger women (median 47 years old compared to 63 years for High Grade Serous Ovarian Cancer (HGSOC)). Unfortunately, LGSOC is often resistant to chemotherapy, meaning standard cancer treatments don’t work as well, particularly when the cancer returns. 

The genetic makeup of LGSOC is unique, and unlike HGSOC which is driven by mutations in a gene called TP53, LGSOC is often driven by changes in the MAPK pathway—a critical communication system inside cells that controls growth and survival. However, LGSOC is a diverse disease with multiple genetic changes, many of which are unknown. Given that LGSOC is both rare and difficult to treat, new therapies that specifically target the unique characteristics of LGSOC are desperately needed.   

Lead author, Dr. Kathleen Pishas, OCRF-funded researcher, Dr. Dane Cheasley and their collaborators at the Peter MacCallum Cancer Centre and the University of Melbourne took a new approach to finding new and more effective therapies for LGSOC. 

The investigators completed the largest drug screens ever performed on LGSOC, which involved testing over 3,400 different compounds (potential treatments) on 12 different patient-derived cells, plus a normal ovarian cell control. Testing a large variety of drugs, including some that are already approved by the Food and Drug Administration (FDA) and others under investigation, the goal was to identify drugs that are more effective in targeting LGSOC cells specifically, without harming healthy cells. 

The researchers identified 60 drugs that showed an ability to kill LGSOC cancer cells, and 19 others that showed potential. Some of these drugs were already known to target pathways that are commonly altered in LGSOC, such as the mTOR/PI3K/AKT pathway (important for cell growth and survival). They also identified other drugs targeting the EGFR and MDM2-p53 pathways, that LGSOC cells were particularly vulnerable to. These pathways have not been widely explored in LGSOC treatment before, so they represent exciting new possibilities. 

This research is a step toward more personalised treatment for LGSOC patients. Instead of relying on drugs designed for other types of ovarian cancer, the hope is that future therapies can be developed to target the specific biology of LGSOC. The findings from this study also provide a valuable resource that other researchers can use to explore new treatment strategies for this rare cancer. Ultimately, this could lead to more effective treatments with fewer side effects, improving survival and quality of life for patients with LGSOC. 

This study validated the accuracy of the BOADICEA model in predicting 10-year ovarian cancer risk using a large dataset from the UK Biobank. By incorporating genetic information, family history, and lifestyle factors, the model effectively identified women at higher risk of developing ovarian cancer with 78% accuracy. These findings support the use of BOADICEA in clinical settings to guide preventive measures and improve diagnosis of ovarian cancer.

Over 75% of epithelial ovarian cancer (EOC) cases are diagnosed at an advanced stage. While there is currently no early detection test or population screening tool, preventive options like risk-reducing surgery can lower the risk of developing EOC, but is associated with adverse effects. Accurate ovarian cancer risk prediction models can therefore help identify women at a high risk who would benefit most from these preventive interventions. 

A new study out of the University of Cambridge assessed the effectiveness of a multifactorial Breast and Ovarian Analysis of Disease Incidence Algorithm (BOADICEA) model (implemented in the CanRisk Tool: https://www.canrisk.org/), in estimating the 10-year EOC risk in a large group of nearly 200,000 women from the UK Biobank who had no prior history of cancer. Unlike earlier versions of the tool, this study used the latest version of BOADICEA, which includes a comprehensive genetic risk score (polygenic risk score) and incorporated information on mutations in six key genes linked to ovarian cancer (BRCA1, BRCA2, RAD51C, RAD51D, BRIP1, and PALB2). It also considered other important factors like family cancer history, body mass index (BMI), use of oral contraceptives, history of endometriosis, and whether the woman had undergone tubal ligation (a permanent birth control procedure). 

Using this data, the BOADICEA model predicted each woman’s 10-year risk of developing EOC. Over a 10-year follow-up period, 733 women were diagnosed with EOC, and the researchers compared the predicted risk to the actual number of cancer cases to see how well the model worked. 

The study found that the full version of the BOADICEA model, which includes genetic information, family history, and lifestyle factors, correctly classified women into high- and low-risk groups 68% of the time. This is an improvement over earlier versions of the model. When the researchers focused specifically on women with genetic mutations known to increase EOC risk (called pathogenic variants or PVs), the model was 78% accurate at predicting EOC risk. 

Overall, the model found that 2.3% of women had an increased risk of developing EOC, which included women with specific genetic mutations or a strong family history of cancer. Importantly, 9.1% of all EOC cases occurred in these women, showing that the model can adequately identify those at the highest risk. 

This study is the first large-scale validation of the BOADICEA model for predicting ovarian cancer risk over a 10-year period. By accurately identifying women at higher risk of developing EOC, the model can help guide doctors and patients in making decisions about preventive measures, for example, risk-reducing surgery (such as salpingectomy – removal of the fallopian tubes). 

The BOADICEA model has been endorsed by health organisations like the UK’s National Institute for Health and Care Excellence (NICE) for managing ovarian cancer risk. This study provides further evidence that the model is a valuable tool for personalised cancer risk assessment, helping doctors and patients make informed choices about cancer prevention and management. 

Research out of the University of New South Wales have found that DNA extracted from ascites fluid in ovarian cancer patients provides the same valuable genetic information as traditional biopsies, making it a less invasive alternative for identifying biomarkers and guiding personalised treatment.

As new targeted therapies for ovarian cancers are being developed, it's also important to develop biomarkers that can guide treatment decisions for each individual patient, known as precision or personalised medicine. However, identifying these biomarkers can be difficult because it requires obtaining high-quality tumour DNA, which is often not easy to access. In some cases, performing a biopsy (removing a sample of tissue for testing) may not be possible or safe for the patient. For instance, certain biopsies may be too invasive or cause complications, making them unsuitable for some individuals. 

In advanced ovarian cancer, fluid buildup in the abdomen, known as ascites, is common. This fluid could provide a valuable source of tumour DNA without the need for invasive procedures like biopsies to identify precision medicine-guided biomarkers. In this study out of University of New South Wales, the researchers looked at DNA floating freely in the ascites fluid (cell-free DNA or cfDNA) as a potential alternative to tissue biopsies. They collected 26 samples of cfDNA from 15 patients with ovarian cancer and compared them to tumour DNA obtained from ascites-derived tumour cells versus traditional tissue biopsies preserved in paraffin wax (known as FFPE samples). 

The researchers found that the cfDNA from ascites was just as good as the DNA extracted from traditional biopsies when it came to tumour content and detecting genetic mutations and treatment biomarkers. They analysed large-scale genetic changes and the number of tumour mutations. They also noted that the genetic makeup of tumours changed between different ascites samples over time.

Overall, the analysis of cfDNA from ascites fluid provided clinically relevant information that matched well with traditional tissue biopsies, and will inform the discovery of precision medicine-guided biomarkers in the future. This study suggests that using ascites fluid for DNA analysis could be a practical and a less invasive alternative to performing biopsies, allowing for more personalised treatment strategies for ovarian cancer patients at multiple time junctions.