Search

ABSTRACTAntigen-encoding, lipoplex-formulated RNA (RNA-LPX) enables systemic delivery to lymphoid compartments and selective expression in resident antigen-presenting cells. We report here that the rejection of CT26 tumors, mediated by local radiotherapy (LRT), is further augmented in a CD8+T cell-dependent manner by an RNA-LPX vaccine that encodes CD4+T cell-recognized neoantigens (CD4 neoantigen vaccine). Whereas CD8+T cells induced by LRT alone were primarily directed against the immunodominant gp70 antigen, mice treated with LRT plus the CD4 neoantigen vaccine rejected gp70-negative tumors and were protected from rechallenge with these tumors, indicating a potent poly-antigenic CD8+T cell response and T cell memory. In the spleens of CD4 neoantigen-vaccinated mice, we found a high number of activated, poly-functional, Th1-like CD4+T cells against ME1, the immunodominant CD4 neoantigen within the poly-neoantigen vaccine. LRT itself strongly increased CD8+T cell numbers and clonal expansion. However, tumor infiltrates of mice treated with CD4 neoantigen vaccine/LRT, as compared to LRT alone, displayed a higher fraction of activated gp70-specific CD8+T cells, lower PD-1/LAG-3 expression and contained ME1-specific IFNγ+CD4+T cells capable of providing cognate help. CD4 neoantigen vaccine/LRT treatment followed by anti-CTLA-4 antibody therapy further enhanced the efficacy with complete remission of gp70-negative CT26 tumors and survival of all mice. Our data highlight the power of combining synergistic modes of action and warrants further exploration of the presented treatment schema.

ABSTRACTHPV16 infections are associated with a variety of cancers and there is compelling evidence that the transforming activity of HPV16 critically depends on the expression of the viral oncoproteins E6 and E7. Therapeutic cancer vaccines capable of generating durable and specific immunity against these HPV16 antigens hold great promise to achieve long-term disease control. Here we show in mice that HPV16 E7 RNA-LPX, an intravenously administered cancer vaccine based on immuno-pharmacologically optimized antigen-encoding mRNA, efficiently primes and expands antigen-specific effector and memory CD8+T cells. HPV-positive TC-1 and C3 tumors of immunized mice are heavily infiltrated with activated immune cells and HPV16-specific T cells and are polarized towards a proinflammatory, cytotoxic and less immune-suppressive contexture. E7 RNA-LPX immunization mediates complete and durable remission of progressing tumors. Circulating memory T cells are highly cytotoxic and protect from tumor rechallenge. Moreover, E7 RNA-LPX immunization sensitizes anti-PD-L1 refractory tumors to checkpoint blockade. In conclusion, our data highlight the potential of HPV16 RNA-LPX for the treatment of HPV-driven cancers.

Cancer cell lines are a tremendous resource for cancer biology and therapy development. These multipurpose tools are commonly used to examine the genetic origin of cancers, to identify potential novel tumor targets, such as tumor antigens for vaccine devel­opment, and utilized to screen potential therapies in preclinical studies. Mutations, gene expression, and drug sensitivity have been determined for many cell lines using next-generation sequencing (NGS). However, the human leukocyte antigen (HLA) type and HLA expression of tumor cell lines, characterizations necessary for the development of cancer vaccines, have remained largely incomplete and, such information, when available, has been distributed in many publications. Here, we determine the 4-digit HLA type and HLA expression of 167 cancer and 10 non-cancer cell lines from publically available RNA-Seq data. We use standard NGS RNA-Seq short reads from “whole transcriptome” sequencing, map reads to known HLA types, and statistically determine HLA type, heterozygosity, and expression. First, we present previously unreported HLA Class I and II genotypes. Second, we determine HLA expression levels in each cancer cell line, providing insights into HLA downregulation and loss in cancer. Third, using these results, we provide a fundamental cell line “barcode” to track samples and prevent sample annotation swaps and contamination. Fourth, we integrate the cancer cell-line specific HLA types and HLA expression with available cell-line specific mutation information and existing HLA binding prediction algorithms to make a catalog of predicted antigenic mutations in each cell line. The compilation of our results are a fundamental resource for all researchers selecting specific cancer cell lines based on the HLA type and HLA expression, as well as for the development of immunotherapeutic tools for novel cancer treatment modalities.