A New Machine-Learning-Based Vaccine Design Program Called Auto Pep Vax: Use in a Pan-Cancer Vaccine Targeting EGFR Missense Mutations

Abstract

More complex in silico techniques are required to identify immunologically relevant epitopes since the existing epitope
selection methods for peptide vaccines only use one-peptope binding affinity estimates.In order to speed up and enhance the in silico
epitope selection process for peptide vaccine creation, we created AutoPepVax.A new tool called AutoPepVax uses a variety of
epitope properties to automatically identify non-toxic and non-allergic epitopes that may trigger lymphocytes that infiltrate tumours.
AutoPepVax uses machine learning models based on random forest classification and linear regression that are trained using tumour
sample datasets.AutoPepVax and its installation instructions are publicly accessible on GitHub.We utilised AutoPepVax to create a
pan-cancer peptide vaccine that targets missense mutations in the epidermal growth factor receptor (EGFR), which are often seen in
head and neck squamous cell carcinoma (HNSCC), lung adenocarcinoma (LUAD), colonrecta adenocarcinoma (CRAD), and
glioblastoma multiforme (GBM).Clinical studies for EGFR-specific peptide vaccines have already addressed these mutations in GBM
and LUAD; although they show promise, they have not yet showed clinical effectiveness. Our investigation of 96 EGFR mutations
using Auto Pep Vax revealed 430 possible MHC-I-restricted depitope–HLA couples from 168,669 candidates and 368 potential MHC-
I-restricted pairs from 49,113 candidates. Interestingly, 19 mutations showed MHC I and II restriction epitopes that were viable.We
used our algorithm, PCOptim , to curate a basic list of epitopes with optimum population coverage in order to assess the possible effect
of a pan-cancer vaccine made up of these epitopes. For MHC Class II and Class I epitopes, our list's global population coverage varied
from 81.8% to 98.5%, respectively. We created 3D epitope–MHC models for six MHC-I-restricted and four MHC-II-restricted
depitopes based on our list of epitopes, showcasing their interaction with T-cell receptors and potential for epitope binding. The
thorough method of in silico epitope selection used by Auto Pep Vax tackles vaccine effectiveness, safety, and wide application. Future
research will use mouse tumour models that include the mutations under study to verify the Auto Pep Vax-designed vaccinations.