A team of researchers from several health care systems and universities, including Emory University, has discovered a new artificial intelligence (AI)-derived biomarker that uses routine imaging scans to help predict which patients with lung cancer will respond to immunotherapy.
“The ability to predict response to immunotherapy merely from a baseline CT scan would be a game changer because if we find out which patients will and will not respond to therapy, we can offer different therapeutic modalities,” says Mohammadhadi Khorrami, PhD, first author on the study and postdoctoral fellow in the Wallace H. Coulter Department of Biomedical Engineering at Emory University School of Medicine and Georgia Institute of Technology College of Engineering. “Moreover, with the staggering costs of immunotherapy – around $200,000 a year per patient – the need to non-invasively determine this response before initiating therapy becomes crucial.”
The new biomarker, quantitative vessel tortuosity (QVT), examines features of blood vessels surrounding tumors, which can influence tumor behavior and therapeutic resistance.
Khorrami and his colleagues used AI tools to evaluate different aspects of QVT biomarkers in more than 500 cases of patients with non-small cell lung cancer before and after they were treated with immune checkpoint inhibitor (ICI) therapies, a type of immunotherapy.
The researchers discovered that the tumor vasculature of patients who do not respond to ICI therapies is more twisted compared to those who do respond. They hypothesize that blood vessel twistedness causes antitumor cells to accumulate at the tumor site but fail to efficiently infiltrate the tumor, diminishing the effectiveness of immunotherapy.
These findings are important because immunotherapy is often the first line of treatment for patients with non-small cell lung cancer, which represents 84% of all lung cancers, according to the American Cancer Society. However, most patients don’t achieve durable results from ICI therapies.
In future work, the researchers will seek to validate QVT biomarkers in prospective clinical trials.