The problem of optimal target selection represents a critical tension in the provision of targeted immunotherapy for many cancer types. Tumor-associated antigens (TAA) are widely shared and boast broad applicability for many patients; however, concerns abound over their efficacy and safety in cancer vaccine formulations since these targets are expressed in non-cancerous cells. Separately, the employment of preferred tumor-specific mutation-derived “neoantigens” in immunotherapy is burdened by a costly and time-intensive discovery process in which sequencing of patient samples reveals potentially actionable targets. As a result, there is a pressing need for cost-efficient methods to rapidly identify tumor-specific antigens that are widely shared among cancer types as molecular targets in the immunotherapy armamentarium. This proposal articulates one such method, leveraging insights derived from large-scale computational interrogation of cancer genomics data to explore the pan-cancer phenomenon of transposable element dysregulation.
AluOmics is developing a patent-pending, low-cost, rapid method by which a given tumor’s targetable neoantigen repertoire can be profiled without the need for costly and time-intensive sequencing. This technique aspires to uncouple the need for tumor-sequencing from vaccination, thus eliminating one of the largest logistical barriers to widespread implementation of this promising immunotherapeutic modality.