Researchers in the United Kingdom use artificial intelligence (AI) tools to detect tiny abnormal cell clusters in biopsy samples from ovarian cancer patients - the presence of these cells suggests that the disease is more aggressive.
The study, published in Nature Communications, used artificial intelligence to analyze ovarian cancer tissue samples from 514 women, and observed a total of nearly 150 million cell shapes.
Dr. Yinyin Yuan, head of the computer pathology team at the Cancer Institute and senior author of the paper, said: "We have developed a simple new computer test that identifies women with very aggressive ovarian cancer, so Their needs are tailored to the treatment plan."
Artificial intelligence tools scan the shape and content of tumor cells, especially the nucleus, the part of the cell that contains DNA. In most cells, the nucleus is a fuzzy circle or ellipse, but the researchers found small plaques with malformed nuclei in some ovarian cancer samples.
Women with these deformed cell clusters in tumors have very aggressive disease with a five-year survival rate of only 15%, while patients without these abnormal nuclei have a five-year survival rate of 53%.
Through in-depth research, they analyzed the plaques of these abnormal cells and found that they have lower levels of DNA repair genes, including BRCA1, one of the genes often defective in patients with hereditary breast and ovarian cancer.
Many of these defects can be identified in the DNA code by DNA sequencing, but in some cases there are other reasons for the low level of DNA repair genes, which may be missed by sequencing, but it is possible It is checked out by artificial intelligence test.
This new finding may also have an impact on the treatment of women with more aggressive ovarian cancer. The PARP inhibitor olaparib is currently approved by the FDA for BRCA mutations in breast cancer patients, but new artificial intelligence tests may be able to identify patients who have no mutations, but patients with lower BRCA levels may be able to get from this drug or other Benefit from similar treatments.
Yuan said: "The use of this new test provides us with a way to detect tumors. These tumors have defects in their ability to repair DNA, and these defects cannot be determined by genetic testing. It can be used simultaneously with genetic testing to identify Patients benefiting from alternative treatment options such as DNA repair defects, such as PARP inhibitors."
In addition to defects in DNA repair, the researchers also found that immune cells could not reach clusters of cells with abnormal nuclei, suggesting that perhaps escaping the immune system is the result of poor prognosis in patients with this ovarian cyst than in patients without malformed clusters. A lot of reasons.
Yuan said: "Our test also showed that ovarian tumors with these abnormal nuclear clusters have evolved a new way to evade the immune system, so it is possible to target this mechanism using new forms of immunotherapy for targeted therapy. ""
Further analysis of these clusters, the team found that they have a high level of protein galectin-3, which is known to cause T lymphocyte death, which is an important part of the immune system to control cancer, but more work is needed to figure out Whether this is the main factor in keeping these deformed cell populations "invisible" in front of the immune system.
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