Source: Imperial College London
Summary: Patterns of genetic mutation in ovarian cancer are helping make sense of the disease, and could be used to personalize the treatment in future. The findings have found distinct patterns of DNA rearrangement that are linked to patient outcomes.
High-grade serous ovarian cancer, the most common type of ovarian cancer, is referred to as a ‘silent killer’ because early symptoms can be difficult to pick up. By the time the cancer is diagnosed, it is often at an advanced stage, and survival rates have not changed much over the last 20 years. But late diagnosis isn’t the only problem. Ovarian cancer genomes are particularly chaotic – they contain a scrambled mess of genetic code that has been chopped up, flipped over, incorrectly copied or deleted, or repeatedly copied over and over again. This makes it extremely difficult to understand what has caused a patient’s cancer and how that patient will respond to treatment. The findings, from scientists at the Cancer Research UK Cambridge Institute, University of Cambridge and Imperial College London have found distinct patterns of DNA rearrangement that are linked to patient outcomes. The study findings were published in the journal Nature Genetics.
Patterns of genetic mutation in ovarian cancer are helping make sense of the disease and could be used to personalize treatment in future. In this study, which involved ovarian cancer samples from over 500 women, the research team harnessed big data processing techniques to look for broad patterns in the genetic readouts from ovarian cancer cells. Rather than focusing on the detail of each individual mistake in the DNA, they designed powerful computer algorithms to scan the genetic data, finding seven distinct patterns. They showed that each pattern, or “signature“, represented a different mechanism of DNA mutation. Taken together, these signatures were able to make sense of the chaos seen in ovarian cancer genomes. Surprisingly, all patients studied showed more than one signature, suggesting that multiple mechanisms change ovarian cancer cells during the life of these cancers. This might explain why the disease is so hard to beat with therapies target just a single mechanism.
Prof. Iain McNeish said, “Ovarian cancer lags behind many other cancers because we haven’t been able to understand how its complex molecular changes relate to targeted therapies. Our new approach helps to decode the complexity and will improve outcomes and treatment choices for our patients.”
More information: Geoff Macintyre et al, “Copy number signatures and mutational processes in ovarian carcinoma”, Nature Genetics (2018). DOI: 10.1038/s41588-018-0179-8