IMMUNOGENOMIC ANALYTICAL APPROACHES FOR RESEARCH AND CLINICAL APPLICATIONS
One of the critical steps to developing curative and tumor-specific immunotherapies is the identification and selection of antigens with tumor-restricted expression in order to avoid undesirable immune responses against normal tissues. Proteins with tumor-specific mutations have the potential to be the most restricted of all tumor antigens. However, the comprehensive identification of such `neoantigens’ has only become feasible recently using next-generation massively parallel sequencing technologies, providing unprecedented genetic information about cancer cells. We have previously developed computational workflows to identify neoantigens arising from somatic missense mutations, insertions or deletions. The current project seeks to develop neoantigen prediction pipelines to discover cancer neoantigens deriving from transcriptome data, such as those arising from intra- or inter-chromosomal gene-fusions; or from splicing alterations, generated from mutation in cis-acting regulatory sequences, or from mutations in splicing factors themselves that can create multiple tumor-restricted transcripts. The current project also seeks to expand our previously developed toolkit for characterization of class I HLA genes to accommodate other immune-related polymorphic loci in the genome, particularly class II HLA genes, as well as a tool for inferring allele specific copy number variation in HLA genes. A new initiative in the Dr. Catherine Wu’s lab focuses on development of a novel experimental method for isolating paired CDR3-V? and -V? chain information from single T cells which would enable correspondence of specific TCRs that detect specific known peptide-HLA complexes of interest. As part of this project, we therefore propose creation of pipelines for deconvoluting single-cell T cell repertoire data. Finally, we propose to investigate the clonal evolutionary dynamics of tumor and immune components in chronic lymphocytic leukemia by developing single-cell sequencing workflows for studying transcriptional changes over time or in response to treatment.
Public Health Relevance
An emerging immunotherapy paradigm in cancer is to vaccinate patients and induce a strong immune response that eradicates the tumor, but most immunotherapies vaccinate with molecules that are present on both tumors and normal cells, making it likely that the immune response will also cause damage to normal tissues. Neoantigens – peptides deriving from somatic mutations in tumors – constitute an extremely promising class of cancer vaccines due their exclusive occurrence on tumor tissues, which is expected to make them safer and more effective. The advent of next-generation sequencing (NGS) technologies has made it possible to enumerate a patient’s neoantigens in an easy, quick and cost-effective manner. Here we propose to (i) develop novel methods for comprehensive identification of tumor neoantigens from NGS data; (ii) elucidate the genetic determinants of immune escape through analysis of bulk and single-cell tumor and immune cohorts; and (iii) develop informatics framework for the clinical targeting of personalized neoantigens. These aims will be pursued in the context of existing NCI funded research programs in Dr. Catherine Wu’s lab at Dana-Farber Cancer Institute.