ECI3 Antibody

How do antibody responses differ between mild and severe viral infections?

Antibody responses show distinct patterns depending on infection severity. In mild viral infections, antibodies predominantly bind to epitopes in the S2 subunit within fusion peptide (FP) and heptad-repeat regions. In contrast, individuals with severe disease develop antibodies that additionally bind to epitopes in the N- and C-terminal domains of the S1 subunit - a pattern also observed in vaccinated individuals .

This differential binding pattern suggests that disease severity correlates with a broader antibody response. Interestingly, antibodies from non-hospitalized infected individuals display significantly higher binding to the fusion peptide (FP) epitope than samples from hospitalized or vaccinated individuals, while antibodies from both hospitalized infected and vaccinated individuals have significantly higher binding to the NTD, CTD, and SH-H regions compared to non-hospitalized infected individuals .

What factors affect the binding patterns of antibodies after vaccination?

Several factors can influence antibody binding patterns following vaccination:

• Time since vaccination: Epitope binding changes over time after vaccination. For samples in the Moderna Trial Cohort, there was significantly decreased binding to the CTD epitope and SH-H epitope at the later timepoint post first dose (day 119) compared to the earlier timepoint (day 36) .

• Vaccine dosage: Interestingly, vaccine dosage (comparing 100 μg and 250 μg mRNA-1273 groups) did not significantly affect binding to the four major epitope regions (NTD, CTD, FP, or SH-H) .

• Escape pathways: For antibodies targeting specific epitopes (like the NTD and CTD-N), the pathways of escape tend to drift over time and were different at 119 days post vaccination compared to 36 days post vaccination .

These findings highlight the temporal dynamics of antibody responses following vaccination and have implications for understanding long-term immunity.

How do bispecific antibodies enable targeted immunotherapy approaches?

Bispecific antibodies represent a powerful approach for targeted immunotherapy by simultaneously binding to two different antigens, often redirecting immune effector cells to target cells. For example, T-cell engaging bispecific antibodies commonly target CD3 on T-cells and a tumor-associated antigen.

The DLL3/CD3 IgG-like T-cell engaging bispecific antibody (ITE) demonstrates this principle by redirecting T-cells to specifically lyse small cell lung cancer (SCLC) cells expressing Delta-like ligand 3 (DLL3). This bispecific antibody selectively binds to DLL3-positive tumor cells and T-cells, inducing formation of an immunological synapse that results in tumor cell lysis and T-cell activation .

In preclinical models, this approach leads to:

• Increased infiltration of T-cells into tumor tissue

• Apoptosis of tumor cells

• Tumor regression

• Upregulation of immune checkpoint molecules (PD-1, PD-L1, and LAG-3)

This mechanism demonstrates how bispecific antibodies can recruit T-cells into non-inflamed tumor tissues, potentially overcoming limitations of traditional immunotherapies.

What strategies can improve the specificity and safety of bispecific antibodies?

A key challenge with bispecific antibodies is managing on-target, off-tumor toxicity. Several innovative strategies are being developed to enhance specificity and safety:

Conditional Active Biologics (CABs): These bispecific antibodies are engineered to have pH-dependent binding properties. They show reduced binding under normal physiological conditions (≥pH7.4) while maintaining good binding under tumor microenvironment (TME) conditions (pH5.8–6.7) .

For example, EpCAM × CD3 bispecific CABs are designed with:

• IgG1-N297Q backbone (non-glycosylated IgG1 without effector functions) for the tumor-targeting arm

• Anti-CD3 single chain variable fragment (anti-CD3-scFv) antibody fused to the C-terminus of each light chain

• Resulting in homodimers (~200 kDa) with two binding domains for EpCAM and two for CD3

This conditional activation in the acidic tumor microenvironment potentially reduces peripheral toxicity while maintaining anti-tumor efficacy in the target environment.

How can researchers efficiently screen large antibody libraries?

Modern antibody discovery requires screening vast numbers of candidates. "Deep screening" represents a breakthrough method that leverages the Illumina HiSeq platform to screen approximately 10^8 antibody-antigen interactions within just 3 days .

The methodology involves:

• Clustering and sequencing of antibody libraries

• Converting DNA clusters into complementary RNA clusters covalently linked to the instrument's flow-cell surface

• In situ translation of the clusters into antibodies tethered via ribosome display

• Screening via fluorescently labeled antigens

This approach has successfully discovered:

• Low-nanomolar nanobodies to model antigens using 4 × 10^6 unique variants from yeast-display-enriched libraries

• High-picomolar single-chain antibody fragment leads for human interleukin-7 directly from unselected synthetic repertoires

Additionally, deep screening can be integrated with machine learning approaches. For example, researchers used deep screening of a library of 2.4 × 10^5 sequences of the third complementarity-determining region of the heavy chain (CDR-H3) of an anti-HER2 antibody as input for a large language model that generated new single-chain antibody fragment sequences with higher affinity for HER2 than those in the original library .

How can proteomic methods enhance antibody discovery and characterization?

Proteomics offers powerful tools for antibody discovery through data mining of antibody sequences. Novel approaches include:

• Leveraging next-generation sequencing (NGS): Using NGS output for antibody sequencing to construct novel antibody peptide databases, expanding the search space of proteomics database searches while keeping it at a manageable level .

• Discovering novel antibody peptides: This approach enables identification of previously undiscovered antibody peptides in blood plasma samples, with over 5% new antibody peptides detected .

• Mapping to functional regions: Identified peptides can be mapped back to critical regions like CDR-H3, which significantly influence antibody binding and specificity .

• Disease-specific applications: CDR-H3 peptides specific to certain conditions (e.g., COVID) hold potential for disease diagnostics, with methodologies potentially applicable across various diseases .

These proteomic approaches are particularly valuable when the presence of specific antibodies correlates with disease state, allowing for both diagnostic applications and enhanced understanding of immune responses.

How do allotypic variations in antibodies impact their functional properties?

Allotypic variations - naturally occurring genetic variants of antibodies - can significantly impact antibody structure and function. IgG3 allotypic variations demonstrate this principle clearly:

Structural consequences:

• Variations in hinge region length (from 32 to 62 amino acids) depending on G3m alleles

• Altered conformational flexibility

• Modified spatial arrangements in the immunological synapse

Functional impacts:

What methodological approaches can optimize antibody effector functions?

Optimizing antibody effector functions requires understanding and manipulating key structural elements:

• Hinge region engineering: Modifying the length and composition of the hinge region can enhance ADCC. Shorter hinges may increase ADCC against certain targets but potentially reduce phagocytosis, affecting the balance of inflammatory properties .

• CH3 domain modifications: Alterations in the CH3 domain affect CH3-CH3 interdomain interactions with consequences for complement activation and aggregation dynamics .

• FcRn binding optimization: Amino acid modifications at position 435 (switching from arginine to histidine) can extend half-life by improving FcRn-mediated transport. Additionally, modifications remote from the FcRn binding site can also affect IgG binding to FcRn .

• Conditional activation engineering: Creating pH-sensitive antibodies that are preferentially active in specific microenvironments (like the acidic tumor microenvironment) through mutations in CDR loops .

• T-cell engaging optimization: For bispecific antibodies, optimizing the spatial arrangement between effector and target cells through structural modifications can enhance cytotoxic activity .

How do T-cell engaging antibodies differ in mechanism from traditional immunotoxins?

T-cell engaging antibodies and immunotoxins represent two distinct approaches to targeting diseased cells, particularly in cancer therapy:

T-cell engaging antibodies:

• Function by redirecting endogenous T-cells to target cells

• Create an immunological synapse between T-cells and target cells

• Harness the natural cytotoxic machinery of T-cells

• Potentially induce immunological memory

• Examples include the DLL3/CD3 IgG-like T-cell engaging bispecific antibody for SCLC

Immunotoxins (like CD3e-sZAP):

• Consist of an antibody component linked to a toxin

• Directly deliver cytotoxic payloads to target cells

• Function through internalization and intracellular toxin release

• Generally do not require immune cell engagement

• May have more immediate cytotoxic effects but lack memory induction

Both approaches have distinct advantages in different contexts, with T-cell engagers potentially offering more durable responses through immune activation, while immunotoxins may provide more consistent cytotoxicity independent of the immune microenvironment.

What factors contribute to the uniformity or variability of antibody escape profiles?

Understanding antibody escape - how pathogens evade antibody-mediated immunity - is crucial for therapeutic development. Research shows that escape profiles can be either relatively uniform or highly variable:

• Vaccination-induced uniformity: Vaccination induces a relatively uniform escape profile across individuals for some epitopes. This suggests that vaccine-induced antibodies target similar antigenic sites in a consistent manner .

• Infection-induced variability: There is much more variation in escape pathways in mildly infected individuals. This indicates that natural infection leads to more diverse antibody responses with variable targeting .

• Epitope-specific patterns: For antibodies targeting certain regions (like the fusion peptide), the escape profile after infection is not altered by subsequent vaccination. This suggests some epitope-specific escape mechanisms are consistent regardless of how immunity was acquired .

• Temporal dynamics: Escape profiles can change over time after vaccination, as demonstrated by differences in escape pathways at 119 days post-vaccination compared to 36 days post-vaccination .

These findings have important implications for understanding antibody-mediated protection and designing therapeutics that can overcome or prevent escape mutations.