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This content will become publicly available on August 19, 2025

Title: Predicting Neoantigens for Cancer Using Next-Generation IEDB & CEDAR Tools
Cancer is a group of diseases characterized by uncontrolled growth and spread of abnormal cells. The underlying cause of cancer relates to the cell cycle, during which DNA is replicated. Cancer cells accumulate DNA mutations that help them acquire cancerous features, such as evading cell death and indefinite growth [1]. If these DNA mutations are in coding regions, they are translated to mutated proteins. The epitopes that contain these mutations are called neoantigens. Neoantigens are highly tumor-specific and can be targeted with immunotherapies [2]. During cell division, tumor suppressor genes play a role in the case of DNA damage or replication errors. The p53 protein is a tumor suppressor gene product that prevents tumor formation by activating processes that block cell division when DNA damage has occurred [3]. Mutant p53 does not effectively bind DNA or activate the production of proteins necessary for the stop signal. This project explored a hypothesis that a set of distinct p53 protein mutations can be selected to serve as potential targets for cancer immunotherapy and vaccines by using immunoinformatics predictive analysis tools. By comparing these potential targets with experimental results, we can predict epitopes that may serve as neoantigen targets for immunotherapy. We identified candidate immunogenic epitopes using the NCI’s TP53 Database (NCI DB - tp53.isb-cgc.org), Cancer Epitope Database and Analysis Resource (CEDAR - cedar.iedb.org), and a powerful new bioinformatics tool (nextgen-tools.iedb.org/) [4] hosted by Immune Epitope Database (IEDB - iedb.org) and CEDAR.  Comparing predicted epitopes to highly mutable regions of p53 in tumor variants from NCI DB revealed areas of overlap that may be priority candidate epitopes for immunotherapy.  Experimental data from CEDAR tested the immunogenicity of normal and mutated protein versions to help avoid harmful cross-reactions. These results help predict cancer epitope amino acid sequences relevant to understanding the immune system's role in cancer progression, prevention, and treatment. These studies also set the stage for important subsequent undergraduate research projects to further characterize predicted cancer neoantigens.  more » « less
Award ID(s):
2055036
NSF-PAR ID:
10537891
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ; ; ;
Publisher / Repository:
Zenodo
Date Published:
Journal Name:
Journal of advanced technological education
ISSN:
2832-9627
Subject(s) / Keyword(s):
p53 mutations neoantigens cancer CEDAR bioinfomatics immunotherapeutic Open Access Resources
Format(s):
Medium: X
Right(s):
Creative Commons Attribution 4.0 International
Sponsoring Org:
National Science Foundation
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  1. Abstract

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  5. Abstract BACKGROUND

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    METHODS

    We used both COLD-PCR and conventional PCR (for comparison) to amplify serially diluted mutation-containing cell-line DNA diluted into wild-type DNA, as well as DNA from lung adenocarcinoma and colorectal cancer samples. After amplification of TP53 (tumor protein p53), KRAS (v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog), IDH1 [isocitrate dehydrogenase 1 (NADP+), soluble], and EGFR (epidermal growth factor receptor) gene regions, PCR products were pooled for library preparation, bar-coded, and sequenced on the Illumina HiSeq 2000.

    RESULTS

    In agreement with recent findings, sequencing errors by conventional targeted-amplicon approaches dictated a mutation-detection limit of approximately 1%–2%. Conversely, COLD-PCR amplicons enriched mutations above the error-related noise, enabling reliable identification of mutation abundances of approximately 0.04%. Sequencing depth was not a large factor in the identification of COLD-PCR–enriched mutations. For the clinical samples, several missense mutations were not called with conventional amplicons, yet they were clearly detectable with COLD-PCR amplicons. Tumor heterogeneity for the TP53 gene was apparent.

    CONCLUSIONS

    As cancer care shifts toward personalized intervention based on each patient's unique genetic abnormalities and tumor genome, we anticipate that COLD-PCR combined with NGS will elucidate the role of mutations in tumor progression, enabling NGS-based analysis of diverse clinical specimens within clinical practice.

     
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