Rationally guided discovery platform for monoclonal antibodies against carbohydrate antigens using virus-like particle conjugate immunization and high throughput selection
Rationally guided discovery platform for monoclonal antibodies against carbohydrate antigens using virus-like particle conjugate immunization and high throughput selection
批准号:
10574738
负责人:
Daniel Ray Woldring
金额:
$22.76万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-10 至 2025-06-30
关键词:
AddressAffinityAntibodiesAntibody Binding SitesAntigensBindingBiological MarkersBreastCancer PatientCarbohydratesCarrier ProteinsCell SeparationCell surfaceCellsClinicalComplement-Dependent CytotoxicityCytometryDiagnosticDirected Molecular EvolutionDiseaseDisease OutcomeEngineeringEnsureEnzymesEpitope MappingEpitopesGenomicsGlycopeptidesGlycoproteinsHumanImaging DeviceImmune responseImmune systemImmunizationImmunoglobulin Somatic HypermutationIndividualLibrariesLightMalignant NeoplasmsMalignant neoplasm of ovaryMalignant neoplasm of pancreasMethodologyMethodsMolecularMonoclonal AntibodiesMusOvarianPancreasPatient-Focused OutcomesPatternPerformancePhylogenetic AnalysisPhylogenyPolysaccharidesProtein EngineeringSensitivity and SpecificitySpecificityTechnologyTherapeuticTherapeutic Monoclonal AntibodiesTimeTransgenic MiceTumor Cell LineTumor-Associated Carbohydrate AntigensVaccinesVirus-like particleYeastsbiomarker discoverycancer biomarkerscancer diagnosisclinical diagnosisdesigndiagnostic tooldiagnostic valueempowermentglycosylationguided inquiryimprovedin vivointerestlead candidatelead optimizationmalignant breast neoplasmmolecular diagnosticsmolecular imagingneoplastic cellnoveloverexpressionreconstructionspecific biomarkerstumortumorigenesistumorigenicvaccine development
中文摘要
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英文摘要
This project will establish a protein engineering platform for evolving monoclonal antibody binding affinity and
specificity to solve the notorious challenge of developing clinical mAbs against tumor associated carbohydrate
antigens (TACAs). Our central hypothesis is that the merger of Qβ carrier protein-elicited mAb discovery and
rationally-guided directed evolution will outpace existing methodologies for discovering powerful antibodies
against challenging TACA glycosylated biomarkers.
TACAs are unique biomarkers to multiple tumor types, yet they have been underutilized for molecular imaging
and diagnostics because of challenges in developing selective, potent binders. Distinct glycosylation patterns
of tumor cell surfaces are hallmark features that arise during oncogenesis through changes in expression
levels of glyco-processing enzymes. Problematically, these aberrant tumorigenic features are usually
undetected by the immune system and rarely identified as non-self. Even when recognized as an antigen,
weak binding against monovalent glycans leads to an insufficient immune response.
To address this need, we will apply our directed evolution methodology to develop lead candidate mAbs
against TACAs selective to cancer with in vivo binding of KD<10nM and specificity >100-fold binding above
control cells. This will be accomplished by first generating a diverse panel of TACA-specific antibodies via
immunization of transgenic mice with multivalent Qβ vaccines. Dominant antibodies will be isolated and
characterized for paratope diversity and the ability to selectively bind the glyco-targets. Next, we use rationally-
guided directed evolution to achieve mAb binding affinity and specificity. Multiple TACA-specific mAbs obtained
through immunization will undergo high-throughput yeast display directed evolution with site-wise
diversification based on structural, stabilizing, and phylogenetic factors to overcome the routinely low affinity of
anti-carbohydrate binders. Specificity and affinity will be evaluated against multiple human tumor cell lines.
This project will: 1) establish a platform that drastically reduces initial discovery time for translatable molecular
imaging and diagnostic tools against carbohydrate antigens; 2) significantly advance understanding of
tumorigenic cell glycosylation patterns; and 3) mark a major step towards improving sensitivity and specificity
of biomarker-based diagnosis of cancers including ovarian, breast, and pancreatic cancers.
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