Novel neoantigen peptides and tumor regression in the MC38 colorectal cancer model.

Authors

null

Jamie Mong

Institute of Bioengineering and Bioimaging, Singapore, Singapore

Jamie Mong , Sasidharan Swarnalatha Lucky , Meusia Neo , Hao Chen , Norhidayah Binte Mohammad Mazian , Min-Han Tan , Joe Poh Sheng Yeong , Chwee Ming Lim

Organizations

Institute of Bioengineering and Bioimaging, Singapore, Singapore, Lucence Diagnostics Pte. Ltd., Singapore, Singapore, Singapore General Hospital, Singapore, Singapore

Research Funding

Other
Accelerate Technologies Gap-funded project ACCL/19-GAP058-R20H, Agency for Science Technology and Research (A*STAR), Biomedical research council (BMRC), A*STAR

Background: Neoantigen vaccine is an emerging modality to treat cancer by unleashing cytotoxic T cells against tumor-specific mutant antigens. Neoantigens are de-novo changes in tumor cells and are hence more immunogenic and less susceptible to off-target toxicities. In building our own pipeline for neoantigen discovery, we used the mouse colon adenocarcinoma cell line MC38 as a validation model. Methods: We sequenced MC38 cells by whole exome and RNA sequencing to shortlist variants. Candidates were confirmed by sanger sequencing, then analyzed for binding affinity to MHC class I H2-Kb and H2-Db. We selected top 10 epitopes for facile modification to maximize immunogenicity by taking into account peptide characteristics, such as hydrophobicity. In-vivo immunogenicity was tested by subcutaneous injections of pooled peptides in C57BL/6J mice. Amongst the 10 peptides tested, we picked five that elicited greatest IFNγ secretion in re-stimulated splenocytes. Predicted binding affinity did not correlate with in-vivo immunogenicity. We inoculated MC38 cells into the left flank of C57BL/6J mice and started treatment four days later. Mice were injected twice weekly with PBS (group 1), CpG only (group 2), anti-PDL1 only (group 3), Peptide pool + CpG (group 4) and Peptide pool + CpG + anti-PDL1 (group 5) (n=8 per group). CpG ODN 1826 is a TLR9 agonist and acts as an adjuvant, while anti-PDL1 is an immune checkpoint inhibitor. We monitored tumor size, animal weights and food intake every 2-3 days. Results: In control group 1, tumor size exponentially increased by 36 folds on the 18th day of treatment. Groups 2, 3, 4 and 5 saw 16, 13, 8 and 5-fold increases in tumor size respectively, 21 days post-treatment. No tumors were found in 3/7 mice in group 5 upon sacrifice, suggesting tumor regression. Tumor control in groups 4 and 5 corroborated with significant IFNγ secretion from neoantigen re-stimulated splenocytes. We observed 38-45 fold expansion in the number of CD8+ KLRG1+ short-lived effector cells and significant increase in PD-1+ TIM3+ exhausted T cells in group 4 and 5 relative to control. Reps1 and Adpgk neoantigen peptides are widely reported and used in MC38 syngenic model. However, they were not included because both were undetected by sequencing. Cell line authentication by STR profiling confirmed that our cells matched that of MC38 from Kerafast. Conclusions: Using an in-house pipeline, we derived a set of novel neoantigen peptides that robustly controlled tumor growth in the MC38 tumor challenge model. In-silico binding predictions did not correlate with in-vivo patterns of IFNγ secretion. In-vivo tests for IFNγ induction after peptide vaccination is a better measure for potential in tumor control. Upregulation of T-cell exhaustion markers after peptide vaccination explains the improved response with anti-PDL1. Reps1 and Adpgk mutations were absent in our cells, which calls caution to researchers conducting similar research.

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Abstract Details

Meeting

2023 ASCO Breakthrough

Session Type

Poster Session

Session Title

Poster Session A

Track

Breast Cancer,Central Nervous System Tumors,Developmental Therapeutics,Genitourinary Cancer,Hematologic Malignancies,Thoracic Cancers,Other Malignancies or Topics

Sub Track

Vaccines

Citation

JCO Global Oncology 9, 2023 (suppl 1; abstr 28)

DOI

10.1200/GO.2023.9.Supplement_1.28

Abstract #

28

Poster Bd #

C10

Abstract Disclosures

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