Abstract C075: Systems-level computational engineering of a multi-epitope mRNA vaccine for glioblastoma by targeting CD204 positive tumor associated macrophage

Abstract Glioblastoma (GBM) is the most common malignant brain tumor; its five-year survival rate is just 6.9%, underscoring the need for novel therapeutic interventions beyond supportive care. There is currently no cure for GBM, further emphasizing the need for the development of novel treatments. Vaccine design has emerged as a promising method for GBM prevention and treatment. A long-standing issue with vaccine development for GBM is the lack of widely expressed genetic targets across individuals; there are few distinct markers of GBM presence across the affected population. One target that has been identified as significant in GBM pathogenesis is CD204. Literature shows that CD204 is an indicator of tumor associated macrophages (TAMs) in both gliomas and aggressive cancers at-large; furthermore, CD204 positive TAMs suppress the anti-tumor immune response, downregulating T-cell activation and creating a pro-tumorigenic environment. Independently, CD204’s direct correlation with poor GBM prognosis indicates that it plays a crucial role in malignant progression. This study uses immunoinformatic tools to design a safe, efficacious, soluble, and non-toxic multivalent mRNA GBM vaccine by assembling antigenic, immunogenic, and non-allergenic B- and T-cell (CTL and HTL) epitopes specifically targeting CD204. 9 CTL, 3 HTL, and 19 B-cell epitopes were successfully identified and conjugated. We ordered the epitopes with 5′ cap, 5′ UTR, Kozak sequence, signal peptide (tPA), stop codon, 3′ UTR, and a 120-nucleotide long poly(A) tail at the C-terminal with linker sequences (AAY, GGGGS, KK). The computational findings (physicochemical, structural (secondary and tertiary), 3D refinement analyses, MD simulations, and docking analyses) corroborated the stability, high quality, and hydrophilicity of the proposed construct. Molecular docking and immune simulation revealed a high binding affinity (below -600 kcal/mol) of the in silico vaccine with artificial toll-like-receptors (TLR2, TLR3, and TLR4). Immune simulations showed a robust immune response. A slow but consistent increase in immunoglobulins and cytokines was observed. This immunoinformatic study presents a viable GBM vaccine candidate, suggesting that this mRNA construct can now be validated experimentally and be compared to other vaccine candidates to assess its possible impact in human health. At the same time, this study’s methods have the potential to democratize access to therapeutic tools for understudied dangerous cancers worldwide. Citation Format: Ridhi Gutta, Sreelasya Polavarapu, Suhani Garg. Systems-level computational engineering of a multi-epitope mRNA vaccine for glioblastoma by targeting CD204 positive tumor associated macrophage [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr C075.

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Journal
Cancer Immunology Research
Published
2026-02-18
DOI
https://doi.org/10.1158/2326-6074.io2026-c075
Primary Topic
vaccines and immunoinformatics approaches
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article
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article

Abstract C075: Systems-level computational engineering of a multi-epitope mRNA vaccine for glioblastoma by targeting CD204 positive tumor associated macrophage

Suhani Garg, Ridhi Gutta, Sreelasya Polavarapu
Cancer Immunology Research
vaccines and immunoinformatics approaches
article

Abstract C075: Systems-level computational engineering of a multi-epitope mRNA vaccine for glioblastoma by targeting CD204 positive tumor associated macrophage

Suhani Garg, Ridhi Gutta, Sreelasya Polavarapu
article en

Abstract

Abstract Glioblastoma (GBM) is the most common malignant brain tumor; its five-year survival rate is just 6.9%, underscoring the need for novel therapeutic interventions beyond supportive care. There is currently no cure for GBM, further emphasizing the need for the development of novel treatments. Vaccine design has emerged as a promising method for GBM prevention and treatment. A long-standing issue with vaccine development for GBM is the lack of widely expressed genetic targets across individuals; there are few distinct markers of GBM presence across the affected population. One target that has been identified as significant in GBM pathogenesis is CD204. Literature shows that CD204 is an indicator of tumor associated macrophages (TAMs) in both gliomas and aggressive cancers at-large; furthermore, CD204 positive TAMs suppress the anti-tumor immune response, downregulating T-cell activation and creating a pro-tumorigenic environment. Independently, CD204’s direct correlation with poor GBM prognosis indicates that it plays a crucial role in malignant progression. This study uses immunoinformatic tools to design a safe, efficacious, soluble, and non-toxic multivalent mRNA GBM vaccine by assembling antigenic, immunogenic, and non-allergenic B- and T-cell (CTL and HTL) epitopes specifically targeting CD204. 9 CTL, 3 HTL, and 19 B-cell epitopes were successfully identified and conjugated. We ordered the epitopes with 5′ cap, 5′ UTR, Kozak sequence, signal peptide (tPA), stop codon, 3′ UTR, and a 120-nucleotide long poly(A) tail at the C-terminal with linker sequences (AAY, GGGGS, KK). The computational findings (physicochemical, structural (secondary and tertiary), 3D refinement analyses, MD simulations, and docking analyses) corroborated the stability, high quality, and hydrophilicity of the proposed construct. Molecular docking and immune simulation revealed a high binding affinity (below -600 kcal/mol) of the in silico vaccine with artificial toll-like-receptors (TLR2, TLR3, and TLR4). Immune simulations showed a robust immune response. A slow but consistent increase in immunoglobulins and cytokines was observed. This immunoinformatic study presents a viable GBM vaccine candidate, suggesting that this mRNA construct can now be validated experimentally and be compared to other vaccine candidates to assess its possible impact in human health. At the same time, this study’s methods have the potential to democratize access to therapeutic tools for understudied dangerous cancers worldwide. Citation Format: Ridhi Gutta, Sreelasya Polavarapu, Suhani Garg. Systems-level computational engineering of a multi-epitope mRNA vaccine for glioblastoma by targeting CD204 positive tumor associated macrophage [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr C075.

Cancer Immunology ResearchVol. 14(2_Supplement)
George Washington University Virginia Campus (US)
No poverty
Openalex Percentile: Top 51%
vaccines and immunoinformatics approaches
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