We have developed a tool, POLYSOLVER (Shukla, et al., Nature Biotechnology 2015), for genotyping HLA alleles and identifying somatic mutations in these genes in tumors. We used mutation data and HLA haplotypes to infer neoantigens across cancer, and predicted neoantigens were used as part of a vaccination trial in melanoma and GBM.
Together with Dr. Nir Hacohen, we recently reported clustering-based analysis of single cells in melanoma patients receiving immune checkpoint blockade that showed two distinct states of CD8+ T cells associated with patient tumor regression or progression (Sade-Feldman, Yizhak, et al., Cell 2018). In addition to delineating the epigenetic landscape and clonality of these T cell states, this study further identified a transcription factor in CD8+ T cells, TCF7, that predicted positive clinical outcome in checkpoint-treated patients. Overall, this study presented a more generalized strategy for identifying predictors, mechanisms, and targets for enhancing checkpoint immunotherapy. Analysis of a much larger cohort with bulk DNA and RNA sequencing showed that expression signatures that combines genes reflecting the differentiation state of the melanoma cells and genes reflecting the immune infiltrating cells can improve the prediction of who will respond to immune checkpoint blockade therapy (Freeman, Sade-Feldman, et al., Cell Reports Medicine 2022 )
Together with Drs. Steve Lipkin, Nir Hacohen, Zsofia Stadler, and Catherine Wu, we are using our understanding of MSI cancers to explore the use of vaccines to prevent or delay the development of tumors in patients that have a predisposition for tumors with MSI due to inherited defects in the mismatch repair pathway (Lynch syndrome).