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Combining STING-based neoantigen-targeted vaccine with checkpoint modulators enhances antitumor immunity in murine pancreatic cancer
Heather L. Kinkead, … , Elizabeth M. Jaffee, Neeha Zaidi
Heather L. Kinkead, … , Elizabeth M. Jaffee, Neeha Zaidi
Published October 18, 2018
Citation Information: JCI Insight. 2018;3(20):e122857. https://doi.org/10.1172/jci.insight.122857.
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Research Article Oncology

Combining STING-based neoantigen-targeted vaccine with checkpoint modulators enhances antitumor immunity in murine pancreatic cancer

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Abstract

Tumor neoantigens arising from somatic mutations in the cancer genome are less likely to be subject to central immune tolerance and are therefore attractive targets for vaccine immunotherapy. We utilized whole-exome sequencing, RNA sequencing (RNASeq), and an in silico immunogenicity prediction algorithm, NetMHC, to generate a neoantigen-targeted vaccine, PancVAX, which was administered together with the STING adjuvant ADU-V16 to mice bearing pancreatic adenocarcinoma (Panc02) cells. PancVAX activated a neoepitope-specific T cell repertoire within the tumor and caused transient tumor regression. When given in combination with two checkpoint modulators, namely anti–PD-1 and agonist OX40 antibodies, PancVAX resulted in enhanced and more durable tumor regression and a survival benefit. The addition of OX40 to vaccine reduced the coexpression of T cell exhaustion markers, Lag3 and PD-1, and resulted in rejection of tumors upon contralateral rechallenge, suggesting the induction of T cell memory. Together, these data provide the framework for testing personalized neoantigen-based combinatorial vaccine strategies in patients with pancreatic and other nonimmunogenic cancers.

Authors

Heather L. Kinkead, Alexander Hopkins, Eric Lutz, Annie A. Wu, Mark Yarchoan, Kayla Cruz, Skylar Woolman, Teena Vithayathil, Laura H. Glickman, Chudi O. Ndubaku, Sarah M. McWhirter, Thomas W. Dubensky Jr., Todd D. Armstrong, Elizabeth M. Jaffee, Neeha Zaidi

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Figure 1

Neoantigen prediction pipeline and estimation of immunogenicity.

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Neoantigen prediction pipeline and estimation of immunogenicity.
(A) Tum...
(A) Tumor neoepitope identification pipeline from whole-exome sequencing (WES) to in vivo verification. (B) C57BL6J mice were immunized with 20-mer peptides corresponding to mutant Panc02 peptides identified in Supplemental Table 4. Isolated CD8+ T cells were stimulated with T2-Db or Kb APCs pulsed with cognate peptides on an IFN-γ capture plate and resulting spots were counted (ELISPOT assay, see Methods). (C) Mice were immunized with pooled 20-mer peptides, and isolated CD8+ cells were tested for reactivity to minimal epitopes that were predicted from NetMHC algorithm (Supplemental Table 3). Altered peptide ligands (APLs) are indicated in the graph. The peptide number is followed by the MHC-restricted allele (Db or Kb) on the x axis. Symbols represent a single mouse together with mean ± SEM (n = 3 mice per group). Negative controls were VSV and LCMV peptides (see Methods). (D) Mice were immunized with pooled 20-mer peptides corresponding to the mutant neoepitopes and APLs, and isolated CD8+ T cells were analyzed for cross-reactivity to the wild-type 20-mer.

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