The immune system’s ability to detect and eliminate cancerous cells has long been of potential interest as a therapeutic avenue. In recent years, advances such as antigen-specific vaccines and T cell checkpoint inhibition have transformed how we treat cancers. In spite of this, these treatments are not universally successful: there is huge variability in effectiveness between people, and some types of cancer are more likely to elicit immune responses than others.
We use a mouse model system and human tumor samples to ask: what do T cells recognize in an effective anti-tumor immune response? How variable are the antigens from person to person? What makes an effective response different from an ineffective response? We find T cells of interest and then determine what antigens they recognize. We work to use this data to design more effective, broadly useful, antigen-specific treatments against cancer.
We are also applying these approaches to study infections with highly mutable viruses, such as HIV. We are interested in the what differences in immune targets and cross-reactivity distinguish effective immune responses from ineffective ones.