• Computational Design of an MUC1-Targeted mRNA Vaccine for Colorectal Cancer: Population-Specific Optimization for Iranian HLA Alleles
  • sara farahbakhsh,1,* Zarrin Minuchehr,2 Raha Mahdavi karimi,3 Hanita Kouzegar,4 Atrin Tofighi,5 Amitis Masumian,6
    1. Ph.D. Graduate in Biotechnology, Bu-Ali Sina University, Hamadan, Iran
    2. PhD, Head of Department of National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran
    3. Ministry of Education, Tehran, Iran
    4. Ministry of Education, Tehran, Iran
    5. Ministry of Education, Tehran, Iran
    6. Ministry of Education, Tehran, Iran


  • Introduction: Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, with significant mortality and morbidity rates. Traditional treatments like chemotherapy and radiation often cause severe side effects and face challenges such as drug resistance. Recent advances in immunotherapy, particularly mRNA vaccines, offer a promising alternative by eliciting targeted immune responses against tumor-specific antigens. The MUC1 gene, overexpressed in CRC, encodes a mucin protein that plays a critical role in tumor progression and immune evasion, making it an ideal target for vaccine design. This study aimed to computationally design an mRNA vaccine targeting MUC1, leveraging bioinformatics tools to predict high-affinity epitopes and evaluate their immunogenic potential. By focusing on the Iranian population, we sought to ensure broad coverage and efficacy, addressing a critical gap in personalized cancer therapeutics.
  • Methods: The study began with the selection of the MUC1 protein sequence (UniProt ID: P15941) as the target antigen. High-frequency MHC alleles in the Iranian population were identified using the Allele Frequency Database (AFD), prioritizing five MHC class I (e.g., HLA-A*01:01, HLA-A*02:01) and three MHC class II alleles (e.g., DRB1*01:01). Epitope prediction was performed using the Immune Epitope Database (IEDB) tools, focusing on 9-mer peptides for MHC class I and 15–18-mer peptides for MHC class II binding. Key parameters included binding affinity (IC50 < 500 nM), proteasomal processing efficiency (score > 0.5), and TAP transportability. The epitopes' immunogenicity was further validated using VaxiJen (threshold > 0.5) and the IEDB Immunome Browser to assess clinical immune response data. The final vaccine construct was designed in SnapGene 8.0, incorporating optimized codons, 5′/3′ UTRs, a leader sequence, and a poly-A tail. RNAfold analyzed the vaccine’s secondary structure and thermodynamic stability, with metrics like free energy (ΔG) and ensemble diversity.
  • Results: Two epitopes, SVSDVPFPF and TPASKSTPF, exhibited strong MHC class I binding (IC50 = 23 nM and 15 nM, respectively) and high proteasomal/TAP scores (>0.9). SVSDVPFPF also bound MHC class II (rank < 2%), demonstrating its dual potential to activate CD8+ and CD4+ T cells. VaxiJen scores (0.69 and 0.51) confirmed their antigenicity, while the Immunome Browser showed a 100% positive response rate for SVSDVPFPF in existing assays. Population coverage analysis revealed 100% efficacy for the selected epitopes in the Iranian cohort. The designed mRNA vaccine demonstrated high stability, with a free energy of -52.78 kcal/mol and an MFE structure frequency of 0.3%. The centroid structure’s energy (-29.60 kcal/mol) and ensemble diversity (62.19%) indicated structural flexibility, which may enhance immune recognition.
  • Conclusion: This study successfully designed a stable and immunogenic mRNA vaccine targeting MUC1 for colorectal cancer, with SVSDVPFPF as the lead epitope. Computational tools enabled efficient epitope screening and vaccine optimization, highlighting the potential of in silico approaches in accelerating cancer vaccine development. The vaccine’s high population coverage and thermodynamic stability support its feasibility for further preclinical testing. Future work should validate these findings in vitro and in vivo, with potential applications in personalized oncology. This research underscores the transformative role of mRNA vaccines in cancer immunotherapy, offering a precise and adaptable therapeutic strategy.
  • Keywords: mRNA vaccine, colorectal cancer, MUC1, epitope prediction, in silico