An in silico reverse vaccinology approach to design a novel multiepitope peptide vaccine for non-small cell lung cancers

Abstract

Non-small cell lung cancer (NSCLC) is the most prevalent and fatal lung cancer. The multiepitope vaccine is one of the immunotherapies successfully applied to treat NSCLC. We designed a multiepitope vaccine with MHC-I, MHC-II, CTL, and linear B cell epitopes of MAGE-A3, EGF, and MUC-1 oncoproteins employing in silico immunoinformatics approach. The structural assessment of the vaccine showed it as a well-stable protein (Z score of −7.53). The molecular docking between the vaccine and human receptors (TLR-2, TLR-4, MHC-I and MHC-II alleles) implied a high affinity of the vaccine to the receptors. The codon optimization and in silico cloning of the vaccine into the pET-28a (+) plasmid of the E. coli K12 strain revealed its potentiality upon expression (CAI value of 0.9607). Furthermore, immune simulation of the vaccine depicted its ability to stimulate immune responses (B cell, T cell, antibody, and cytokines) against NSCLC. Almost all developed NSCLC vaccines cannot treat or prevent NSCLC satisfactorily, and there is still no multiepitope vaccine available that contains all three significant oncoproteins; therefore, our designed vaccine could be a significant weapon against NSCLC. This novel multiepitope vaccine could be developed upon considering its safety, efficacy, and adverse effects on humans through further studies.

Keywords

• Non-small cell lung cancer
• Reverse vaccinology
• Multiepitope vaccine
• MAGE-A3
• EGF
• MUC-1