Expanding the Antigen Landscape in High Grade Serous Ovarian Cancer

Project summary

Immune surveillance and killing of cancer cells relies on T cell recognition of short, cancer-specific protein sequences (antigens) on the surface of cancer cells. A major obstacle to immunotherapies in ovarian cancer — there are none approved — is the low number of antigens we are able to identify. Indeed, conventional antigen identification algorithms examine only small mutations in known genes; by this measure, ovarian cancer has few mutations relative to other cancers.

I propose to expand the antigen landscape in ovarian cancer by identifying non-canonical antigens, derived from 1) the large scale genomic structural variations (genomic rearrangements, deletions, amplifications, etc.) that define ovarian cancer and 2) non-canonical antigens made from previously unannotated proteins. I will use deep sequencing of the RNA and DNA of patient derived tumor organoids to identify genomic structural variants that may give rise to novel antigens. I will use ribosome profiling in these same organoids to identify potential non-canonical proteins and mass spectrometry to identify which of these non-canonical antigens are present on the surface of patient tumor-derived organoids. Finally, I will demonstrate that these non-canonical antigens are recognized by T cells from healthy donors and from ovarian cancer patients on a phase I cancer vaccine trial. This work will provide the basis for new vaccine and cellular immunotherapy targets.

This grant was made possible by generous donation from Li-An Yeh