Al Identifies Features of Tumor Cells in High-Risk Ovarian Cancer
Scientists have developed a new test that scans the shapes of tumor cells to select women with especially aggressive ovarian cancer. A team at The Institute of Cancer Research (ICR), London, created an artificial intelligence (AI) tool that looks for clusters of cells within tumors with misshapen nuclei. Findings from the study were published by Heindl et al in Nature Communications.
Women identified with these clusters of shapeshifting cells had extremely aggressive disease, with only 15% surviving for 5 years or more, compared with 53% for other patients with ovarian cancer. The researchers found that having misshapen nuclei was an indication that the DNA of cancer cells had become unstable and believe it could help to select the best treatment for each patient. The researchers also found that immune cells were not able to move into the clusters of cells with misshapen nuclei, which suggests that cancers with these clusters are better at evading the immune system.
Methods and Findings
Scientists at the ICR applied a new computer tool to automatically analyze tissue samples from 514 women with ovarian cancer, looking at nearly 150 million cells altogether. The study used AI to look at the shape and spatial distribution of ovarian cancer cells and their surroundings.
The researchers found that tumors containing clusters of cells whose nuclei varied highly in shape had lower levels of activity of key DNA repair genes, including BRCA1. The test could be used to pick out tumors with lower levels of activity of DNA repair genes, even in cases where the genetic code of the BRCA genes remained intact. These hidden DNA repair defects would be overlooked when only testing for faults in DNA repair genes.
The presence of clusters was associated with even worse prognosis than mutations in the BRCA genes. The researchers also found that the clusters had higher levels of a protein called galectin-3, which they believe may represent a potential target for new immunotherapies in ovarian cancer, although further research is needed.
Study Implications
Yinyin Yuan, PhD, team leader in computational pathology at the ICR, said, “We have developed a simple new computer test that can identify women with very aggressive ovarian cancer so treatment can be tailored for their needs. Using this new test gives us a way of detecting tumors with hidden weaknesses in their ability to repair DNA that wouldn’t be identified through genetic testing. It could be used alongside gene testing to identify women who could benefit from alternative treatment options that target DNA repair defects, such as PARP inhibitors.”
“Our test also revealed that ovarian tumors with these clusters of misshapen nuclei have evolved a new way of evading the immune system, and it might be possible to target this mechanism with new forms of immunotherapy,” she concluded.
Disclosure: The study authors’ full disclosures can be found at nature.com.
The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
