Tumor neoantigen heterogeneity impacts bystander immune inhibition of pancreatic cancer growth

Abstract

The immunogenic clonal-fraction threshold in heterogeneous solid-tumor required to induce effective bystander-killing of non-immunogenic subclones is unknown. Pancreatic cancer poses crucial challenges for immune therapeutic interventions due to low mutational-burden and consequent lack of neoantigens. Here, we designed a model to incorporate artificial-neoantigens into genes-of -interest in cancer-cells and to test their potential to actuate bystander-killing. By precisely controlling a neoantigen's abundance in the tumor, we studied the impact of neoantigen frequency on immune-response and immune-escape. Our results showed single, strong, widely-expressed neoantigen could lead to robust antitumor response when over 80% of cancer cells express the neoantigen. Further, immunological assays demonstrated T-cell responses against non-target self-antigen on KRAS-oncoprotein, when we inoculated animals with a high frequency of tumor-cells expressing test-neoantigen. Using nanoparticle-based gene-therapy, we successfully altered tumor-microenvironment by perturbing interleukin-12 and interleukin-10 gene-expression. The subsequent microenvironment-remodeling reduced the neoantigen frequency threshold at which bioluminescent signal intensity for tumor-burden decreased 1.5-log-fold, marking robust tumor-growth inhibition, from 83% to 29%. Our results thus suggest bystander killing is inefficient in immunologically-cold tumors like pancreatic-cancer and requires high neoantigen abundance. However, bystander killing mediated antitumor response can be rescued by adjuvant-immune therapy.

Fig. 1

In silico prediction of neoantigens derivable from single point mutations on KRAS, a) Scheme of insertion of neoantigens via gene editing, b) Representative sequences from a library of mouse KRAS (UniProt P32883–2) sequences with single amino acid variations, c) Alignment of predicted mutation-derived neoantigens against conserved KRAS functional domains, d) Predicted changes in sequence scoring upon single point mutation, from weak binding level (WB) to strong binding level (SB), via NetMHC 4.0 Server, Technical University of Denmark, http://www.cbs.dtu.dk/services/NetMHC/, e) Predicted changes in sequence scoring upon single point mutation, via Immune Epitope Database and Analysis Resource, http://tools.iedb.org/main/tcell/

Fig. 2

Designing plasmids encoding mutant KRAS and determining functionality of mutant KRAS, a) Workflow for designing plasmids encoding KRAS with mutations predicted to generate neoantigens, mutations were incorporated into DNA inserts via PCR overlap extension, b) Sanger sequencing results confirm incorporation of the D153S mutation- the mutation predicted to have highest binding to MHC-I alleles for C57BL/6 mice, sharing genetic background with KPC, c) Sanger sequencing results confirm incorporation of the D153S mutation in plasmids with pcDNA3.1 backbone, d) Western blot analysis of lysates from in vitro cell cultures transfected with KRAS ORF plasmids for 48 h, using Lipofectamine 2000 transfection reagent, analyzing for p44/42 MAPK, downstream of RAS (n = 2–3). Data show mean ± SEM. * p < .05.

Fig. 3

Engineering monoclonal cell lines expressing mutant KRAS and measuring change in antitumor response with variation in epitope frequency, a) Sanger sequencing results confirm expression of the D153S mutation alongside WT allele – in a monoclonal cell line to be referred as 3F11, b) Effect of mutation on orthotopic pancreatic tumor growth via bioluminescence imaging (n = 4–10). Day 10 post tumor inoculation, KPCF1 is a KPC cell line with KRAS^G12D mutation, 3F11 is a KPC cell line with KRAS^G12D/D153S mutation, c) Imaging protocol for panels b and e. BLI stands for Bioluminescence imaging, and D stands for Day, d) Sanger sequencing results confirm expression of the D153M mutation alongside WT allele – in a monoclonal cell line to be referred as 4E1, e) Effect of mutation on orthotopic pancreatic tumor growth via bioluminescence imaging (n = 4–5). Day 10 post tumor inoculation, KPCF1 is a KPC cell line with KRAS^G12D mutation, 4E1 is a KPC cell line with KRAS^G12D/D153M mutation. Data show mean ± SEM. * p < .05, ** p < .01, *** p < .001, **** p < .0001.

Fig. 4

Antitumor response with variation in epitope frequency under local Interleukin 10 blockade, a) Effect of mutation on orthotopic pancreatic tumor growth via bioluminescence imaging (n = 4–10). Day 10 post tumor inoculation, KPCF1 is a KPC cell line with KRAS^G12D mutation, 3F11 is a KPC cell line with KRAS^G12D/D153S mutation. Animals received either phosphate buffered saline (denoted as PBS) or 50 μg of IL-10 trap plasmid DNA (denoted as IL-10 t) administered via lipid-protamine-DNA (LPD) nanoparticles intravenously on Day 7 and 9 post orthotopic tumor cell inoculation, b) Treatment regimen for panel a. pDNA stands for plasmid DNA and BLI stands for bioluminescence imaging, c) Animals were sacrificed on Day 10 post orthotopic tumor inoculation, tumors were harvested, and mRNA Gene expression were quantified by qPCR (n = 16–18), d) Animals were sacrificed on Day 10 post orthotopic tumor inoculation, tumors were harvested, and immune cells were characterized and quantified by flow cytometry (n = 3). Data show mean ± SEM. * p < .05, ** p < .01, *** p < .001, **** p < .0001.

Fig. 5

Antitumor response with variation in epitope frequency under local Interleukin 12 gene expression, a) Effect of mutation on orthotopic pancreatic tumor growth via bioluminescence imaging (n = 4–10). Day 10 post tumor inoculation, KPCF1 is a KPC cell line with KRAS^G12D mutation, 3F11 is a KPC cell line with KRAS^G12D/D153S mutation. Animals received either phosphate buffered saline (denoted as PBS) or 50 μg of IL-12 plasmid DNA (denoted as IL12) administered via lipid-protamine-DNA (LPD) nanoparticles intravenously on Day 7 and 9 post orthotopic tumor cell inoculation, b) Treatment regimen for Fig. 5a. pDNA stands for plasmid DNA and BLI stands for bioluminescence imaging, c) Animals were sacrificed on Day 10 post orthotopic tumor inoculation, tumors were harvested, and mRNA Gene expression were quantified by qPCR (n = 16–18), d) Animals were sacrificed on Day 10 post orthotopic tumor inoculation, tumors were harvested, and immune cells were characterized and quantified by flow cytometry (n = 3) . Data show mean ± SEM. * p < .05, ** p < .01, *** p < .001, **** p < .0001.

Fig. 6

Effective immune adjuvant therapy reduces the threshold of neoantigen frequency required to obtain tumor regression benefit, Effect of mutation and immune intervention on orthotopic pancreatic tumor growth via bioluminescence imaging (n = 4–10). Mice were imaged and tumor signals were quantified on Day 10 post tumor inoculation, KPCF1 is a KPC cell line with KRAS^G12D mutation, 3F11 is a KPC cell line with KRAS^G12D/D153S mutation. Animals received either phosphate buffered saline (denoted as PBS), 50 μg of IL-12 plasmid DNA (denoted as IL12), or 50 μg of IL-10 trap plasmid DNA (denoted as IL-10 t), administered via lipid-protamine-DNA (LPD) nanoparticles intravenously on Day 7 and 9 post orthotopic tumor cell inoculation. The log normalized bioluminescence signal representing tumor burden was plotted on y-axis, and the percentage of cells with D153S mutation in the mixed inoculates were plotted on the x axis. Data fitted using third order polynomial (cubic) interpolation via GraphPad Prism 8.1.0. Horizontal line defines the threshold at which signal intensity for tumor burden reduces 1.5-logfold relative to untreated WT tumor. The numbers on the graph indicate the estimate of neoantigen carrying cells required to reduce the tumor burden by 32-fold or 1.5-logfold in terms of bioluminescence intensity- PBS (89%), IL-10 t (68%), and IL-12 (29%). Data show mean ± SEM.