Finding the Best Treatment for Ovarian Cancer
The early detection and correct diagnosis of cancer is important to optimize treatment regimens, and to give patients the best chance of response and survival. Diagnosis of ovarian cancer is often difficult, as is correctly staging the disease, which can lead to patients not receiving the best treatment for their cancer type. A new test hopes to better identify the exact stage of ovarian cancer, and help each patient receive the best tailored care for their disease.
While breast cancer receives a lot or press and research support, it is actually ovarian cancer that is the most aggressive gynecological malignancy. Ovarian cancer ranks fifth in cancer deaths among women, and accounts for more deaths than any other cancer of the female reproductive system. In 2014 in the US, it is predicted that nearly 22,000 women will receive an ovarian cancer diagnosis, and over 14,000 women will die from the disease. Diagnosing ovarian cancer correctly and at an early stage is an important factor in choosing the correct treatment, and for patient survival. Women diagnosed in the early stages of the disease have a 90% chance of surviving for 5 years, but this falls to only 22% when advanced cancer is found. Diagnosing ovarian cancer is often quite tricky though, as symptoms such as bloating and abdominal pain are also symptoms of other much less serious illnesses. When an ovarian cancer diagnosis is made, often the tumor type and stage is not categorized correctly, and this can also result in patients receiving a treatment which is not optimal for their disease.
Currently, there is no test available to screen for ovarian cancer and to make a specific diagnosis of their disease type. Many researchers are now targeting this issue, and one team has recently published their findings in the BMJ. Their aim was to develop a model to test women with adnexal tumors (growths that form on the organs and connective tissues around the uterus in women, which are most often benign but can be cancerous) to work out if they have cancer, and also to figure out exactly what type they have to then find their best treatment option. The model would hopefully help to make a diagnosis easier, earlier, and quicker, and make sure women received the most appropriate treatment for their ovarian cancer type.
The study was a prospective cohort study of over 3,000 women with at least one adnexal mass and who needed surgery, looking at patients from 24 centers in 10 countries. The model looked at a combination of three clinical predictors (age, serum CA-125 level, and type of center the patient was treated at) combined with six ultrasound predictors based around the tumor type, dimensions, and pathology. Combining all of these factors, the team came up with a model which could accurately predict if the tumor was benign, borderline, or cancerous, and could also distinguish between stage I, stage II-IV, and secondary metastatic cancer. The ADNEX model was then validated on over 2,400 patients and shown to be successful in diagnosing all these stages of disease.
The study authors now hope that their model can be used to optimize diagnosis and treatment of women with adnexal tumors. Being able to correctly diagnose ovarian cancer at an early stage will help survival rates. Being able to spot the difference between borderline and more invasive tumors is then important as borderline tumors can be treated in a less aggressive fashion, which can help in the preservation of patient fertility. Similarly, stage I ovarian cancer can be managed in a much more moderate fashion than late stage disease. The new model can hopefully ensure that each patient receives the correct level of treatment for their specific disease.
Crown Bioscience is happy to see an advance in a disease which is difficult to diagnose and which there is no screening test for, and hope that this model can soon be used as a test for ovarian cancer patients. We support research into ovarian cancer through the use of our large collection of clinically relevant cell line derived xenograft and patient-derived xenograft (PDX) models available for drug discovery and translational sciences. We have the largest commercially available collection of over 1,100 patient-derived xenograft models (HuPrime®), which contains a selection of ovarian cancer patient-derived xenograft models at different disease stages. All HuPrime models are well-characterized and are easily searchable through our free, online database (HuBase™) which can be used to identify relevant models to interrogate biomarkers, pathways, and efficacy. Contact us at email@example.com to talk to our experts about how Crown Bioscience can meet your patient-derived xenograft research needs and how we can drive forward your ovarian cancer research today.