new technique may help predict cancer patient survival
Last Updated : GMT 09:03:51
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Last Updated : GMT 09:03:51
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New technique may help predict cancer patient survival

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Almaghrib Today, almaghrib today New technique may help predict cancer patient survival

Washington - UPI
US researchers said Wednesday they have found a potential way to predict survival in ovarian cancer patients by counting the number of tumor-attacking immune cells that have migrated into the tumor in an effort to eradicate it. Researchers at Fred Hutchinson Cancer Research Center said that their method is able to count these cells known as tumor- infiltrating T lymphocytes, or TILs, "reliably, quickly and cheaply" in patients with early stage and advanced ovarian cancer. Such technology, a DNA-amplification technique, has the potential to predict treatment response, cancer recurrence and disease-free survival earlier and more effectively than any current method, the researchers reported in the U.S. journal Science Translational Medicine. "Our experiments demonstrate an association between higher TIL counts and improved survival among women with ovarian cancer, and are consistent with prior observations that the immune response against ovarian cancer is a meaningful and independent prognostic factor," lead researcher Jason Bielas, an associate member of the Human Biology and Public Health Sciences divisions at the center, said in a statement. The novel technique, called QuanTILfy, was tested on tumor samples from 30 ovarian cancer patients with known survival outcomes ranging from one to 122 months. The researchers looked at the levels of TILs in their tumors and compared those levels to the women's survival. They found that higher TIL numbers correlated with better survival. For example, the percentage of TILs was approximately three times higher on average for patients with a survival rate of more than five years as compared to patients with a survival rate of less than two years. "Now that we have the sensitivity and ability to reproducibly count TILs in tumors, we may be able to stratify and more effectively treat patients based on tumor TIL count," Bielas said.
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