Cancer

Lead Researcher: Dr Cathrin Gudd

Supported by the Digestive Diseases Theme

Checkpoint inhibitors (CPIs) are a breakthrough in cancer treatment. These drugs help boost the immune system to better detect and attack cancer cells. However, while these therapies can be very effective in treating cancer, around two-thirds of patients experience side effects because the immune system becomes too active. These side effects can affect nearly any organ, causing issues ranging from skin rashes to severe illness or even death. One serious side effect is CPI-induced hepatitis (CPI-hepatitis), where the liver becomes inflamed due to the treatment. This condition can range from mild to life-threatening. If a patient develops CPI-hepatitis, they must stop their cancer treatment and take strong medications to suppress their immune system, which unfortunately can reduce the effectiveness of the cancer therapy. CPI-hepatitis is therefore a real concern for patients and oncologists.

In our earlier research, we found two types of immune cells that play a key role in causing liver inflammation during CPI treatment. In studies using mice, we discovered that these cells enter the liver and interact in ways that lead to damage. This new project focuses on studying the genes of these cells to better understand how they cause liver disease. We hope to find ways to block this harmful interaction, allowing patients to continue their cancer treatments with fewer risks.

Thus far, we have identified a cohort of patient and control samples accessible for genetic analysis. All samples were successfully retrieved, prepared and assessed for their genetic makeup. We are currently in the process of analysing the data and identifying key liver damage causing factors.

Lead Researcher: Dr Zoe Hall

Supported by the Digestive Diseases Theme

Liver cancer is one of the leading causes of cancer-related deaths worldwide, with more than a million cases expected by 2025. Hepatocellular carcinoma (HCC) is the most common form of liver cancer and is a very complex form of cancer which makes the development of new therapies is challenging. Drugs which target the immune system and get it to attack the cancer cells in HCC are often successful. At the same time patients with HCC can also have fatty liver disease, where fats accumulate in the liver and affect the liver’s ability to function properly. However, the immune targeting drugs have limited success in patients with HCC and who also have fatty liver disease.

The liver is made of many different cell types, including immune cells. The immune cells may be protective and “search” for and removing tumour cells, but they may also cause inflammation and increase cancer risk. When the liver starts to have problems metabolising fats it can contribute to the development and progression of HCC. Fats can interfere with the liver’s immune cells, and this can affect their ability to find and kill the HCC cells.

In the past decade, new methods and technologies have been developed that can quantify DNA, RNA, proteins and chemicals in biological samples. In this project, we will use a combination of these new methods to measure levels of chemicals across different parts of tissues and cells. We will explore the how different fats are found in the tumour and how they are connected to different tumour cells. Using these technologies, we can build a “chemical signature” across the tumour, and between tumours from different patients, to understand better the link between the immune system and metabolism. From this signature we will decide the best treatment for patients and lead to design of novel drugs for HCC.

Lead Researcher : Dr Laura Tookman

Supported by the Surgery & Cancer Theme

Ovarian cancer is a complex disease. To ensure that each individual patient receives the best treatment, doctors need more information about why the cancer developed. Cancer can be caused by genetic changes inherited from parents or due to changes within the cancer that drives the cancer to grow. The most commonly inherited gene abnormalities in ovarian cancer are in the BRCA1 and BRCA2 genes. Identifying harmful changes in genes is important for treatment decisions and managing future cancer risk for patients and their relatives.

Knowledge about genetic changes within the cancer itself can also help guide treatment.  Some ovarian cancers grow due to an inability to repair defective cells properly.  This process is known as homologous recombination deficiency or HRD. Identifying this defect is crucial because studies have shown that a new therapy called PARP inhibitors improves outcomes for patients with advanced ovarian cancer. The benefit is greatest in those with these harmful changes in the BRCA genes and those cancers that show HRD.

Genetic testing is vital for patients with ovarian cancer to help determine the best treatment.  However, a recent national survey of health record use by gynaecological cancer professionals found that finding these genetic records is challenging and time consuming. To improve this process, we wish to investigate new ways of evaluating results.

This project will set up a secure database so we can examine genetic test results from over 200 ovarian cancer patients. We will follow their progress to assess how accurately the test results predicted response to treatment. We will work with data scientists to develop new automated processes to interpret genetic results from patient notes to create accurate datasets. This will allow us and other researchers to perform high quality research, enhance efficiency and improve care for patients with ovarian cancer.