Desain Imunoinformatika Vaksin Terapeutik Kanker Mulut Rahim Berbasis Onkoprotein E6 dan E7 HPV-52 Terintegrasi Neoantigen

Abstract

Kanker mulut rahim menempati urutan kedua sebagai kanker dengan kasus tertinggi di Indonesia akibat infeksi Human Papilloma Virus (HPV), khususnya melalui onkoprotein E6 dan E7. Keterbatasan vaksin profilaksis dan rendahnya cakupan vaksinasi mendorong pengembangan vaksin terapeutik. Penelitian ini bertujuan mendesain vaksin multi-epitop berbasis imunoinformatika dengan mengintegrasikan onkoprotein HPV-52 (E6 dan E7) dan neoantigen PIK3CA (E545K). Metode meliputi eksplorasi mutasi, prediksi epitop sel T dan B, seleksi berdasarkan imunogenisitas hingga toksisitas, serta konstruksi vaksin dengan adjuvan dan linker. Karakterisasi dilakukan melalui analisis fisikokimia, pemoodelan struktur 3D, molecular docking terhadap TLR3 dan TLR4, dan simulasi imun. Hasil menunjukkan cakupan populasi 93,8% di Indonesia. Struktur memiliki kualitas nilai Ramachandran favored 98,2%. Hasil docking menunjukkan interaksi kuat, dengan TLR3 dan TLR4. Simulasi imun menunjukkan peningkatan antibodi hingga 650.000/mL, aktivasi sel T helper hingga 11.000 sel/mm³, serta dominasi IFN-a hingga 425.000 ng/mL.

Cervical cancer ranks as the second most prevalent cancer in Indonesia and is primarily caused by infection with Human Papilloma Virus (HPV), particularly through the actions of the E6 and E7 oncoproteins. The limitations of prophylactic vaccines and low vaccination coverage necessitate the development of therapeutic vaccines. This study aimed to design a multi-epitope vaccine using an immunoinformatics approach by integrating HPV-52 E6 and E7 oncoproteins with the PIK3CA neoantigen (E545K). Methods included epitope prediction and selection based on immunological properties, vaccine construction, vaccine characterization, 3D structure modeling, molecular docking with TLR3 and TLR4, and immune simulation. The results showed 93.8% population coverage in Indonesia. Structural analysis indicated high quality with 98.2% Ramachandran favored regions. Molecular docking demonstrated strong interactions with TLR3 and TLR4. Immune simulation revealed increased antibody levels up to 650,000/mL, T helper cell activation up to 11,000 cells/mm³, and dominant IFN-a production reaching 425,000 ng/mL