Using computational tools, researchers from the Johns Hopkins Kimmel Cancer Center and the Johns Hopkins University School of Medicine have developed a method to assess which patients with metastatic triple-negative breast cancer could benefit from immunotherapy. The work by computational scientists and clinicians was published Oct. 28 in the Proceedings of the National Academy of Sciences .
Immunotherapy is used to try to boost the body's own immune system to attack cancer cells . However, only some patients respond to treatment , explains lead study author Theinmozhi Arulraj, Ph.D.
, a postdoctoral fellow at Johns Hopkins: "It's really important that we identify those patients for whom it will work, because the toxicity of these treatments is high." To tease this out, studies have tested whether the presence or absence of certain cells, or the expression of various molecules in the tumor, can indicate whether a particular patient will respond to immunotherapy . Such molecules are called predictive biomarkers and are useful in selecting the right treatment for patients, explains senior study author Aleksander Popel, Ph.
D., a professor of biomedical engineering and oncology at the Johns Hopkins University School of Medicine. "Unfortunately, existing predictive biomarkers have limited accuracy in identifying patients who will benefit from immunotherapy," Popel says.
"Moreover, a large-scale assessment of characteristics that predict treatment response would require the collecti.