There are currently very few available approaches to analyzing biologic data that can offer new information about immune responses and help guide appropriate interventions. However, investigators at Johns Hopkins University report in Cancer Immunology Research that they have developed what they call ImmunoMap, which can examine T-cell receptor repertoire relatedness.
“ImmunoMap was able to predict clinical outcome. Patients who were responding to therapy had more dominant T-cell receptor motifs,” said Jonathan Schneck, MD, PhD, who is a professor of pathology, medicine, and oncology at the Johns Hopkins University School of Medicine and a member of the Johns Hopkins Kimmel Cancer Center in Baltimore.
The ImmunoMap revealed unique trends in CD8 T-cell response to self-antigen (Kb-TRP2) or to a model foreign-antigen (Kb-SIY) in naive and tumor-bearing mice. The researchers also used this tool to analyze clinical trial data of tumor-infiltrating lymphocytes in patients treated with anti-PD-1 therapy.
The tool was developed through high-powered computing to create a mathematical model of genomic sequence data of receptors from human T cells that were exposed to a virus in the laboratory. Using an unsupervised learning algorithm, the team was able to convert the T-cell receptor sequencing data into numeric distances based on similarities in the receptor sequences. Once thousands of sequences were converted into the “distance” metrics, the computer system’s artificial intelligence algorithms looked for patterns among the receptors.
The researchers tested the map’s ability to correlate immune responses on receptor sequencing data from T cells in the tumors of 34 patients with cancer enrolled in a nationwide clinical trial of the immunotherapy drug nivolumab. Among the 34 patients, three melanoma patients responded to nivolumab, and the rest did not respond. In the responders, the scientists found more different T-cell receptor clusters (median of 15) compared with eight or nine in the nonresponders.
After 4 weeks of nivolumab, they also found that the diversity of T-cell receptors decreased among the responders by 10% to 15%. “T-cell and T-cell receptor analysis may become an important clinical tool for predicting clinical outcome even after just 4 weeks of therapy,” Schneck told Cancer Network.
Schneck said response to immunotherapy is commonly determined by whether T cells are able to infiltrate the tumor site. However, the current findings demonstrated that while infiltration is important, it is not enough to explain patients’ variable responses to immunotherapy. More research is warranted and currently the ImmunoMap cannot match T-cell receptors to specific antigens.
Ultimately, it is hoped this map can become a new tool for designing vaccines and engineered T cells for cancer treatment.