TIGIT Human

What is TIGIT and what are its structural components?

TIGIT is an inhibitory receptor expressed on lymphocytes that plays a critical role in modulating immune responses. Structurally, TIGIT encompasses three major domains: an extracellular IgV domain, a transmembrane domain, and a cytoplasmic domain containing an immunoreceptor tyrosine-based inhibitory motif (ITIM) and an immunoglobulin tyrosine tail (ITT)-like motif . The extracellular IgV domain is particularly important for ligand binding, while the cytoplasmic domain mediates inhibitory signaling. When designing experimental approaches targeting TIGIT, researchers should consider these distinct structural elements as they serve different functions in the protein's inhibitory activity.

Which cell populations express TIGIT and how does expression vary with activation?

TIGIT is primarily expressed on T cells, NK cells, and regulatory T cells (Tregs). Expression patterns vary significantly depending on activation state. Flow cytometry analysis reveals that only a small proportion of resting NK cells express TIGIT under basal conditions, but the entire NK cell population becomes TIGIT-positive following IL-2 stimulation . Similarly, a small proportion of T cells express TIGIT at rest, with expression increasing substantially following cytokine stimulation . This differential expression pattern is important when designing experiments to study TIGIT function, as researchers must consider the activation state of target cells when interpreting results.

What are TIGIT's primary ligands and their distribution?

TIGIT primarily binds to two ligands: CD155 (PVR) and CD112 (PVRL2, nectin-2), which are expressed by tumor cells and antigen-presenting cells in the tumor microenvironment . Additionally, TIGIT can function as a receptor for NECTIN4 to inhibit NK cell cytotoxicity . The interaction between TIGIT and its ligands is central to its inhibitory function, as binding initiates phosphorylation of the cytoplasmic tail by Src family tyrosine kinases such as FYN or LCK, allowing subsequent binding to adapter GRB2 and SHIP1/INPP5D . When designing competitive binding studies, researchers should account for all three ligands to fully understand TIGIT's regulatory network.

How does TIGIT signaling mechanistically inhibit immune responses?

TIGIT mediates immune inhibition through multiple mechanisms. Upon binding to its ligands, TIGIT's cytoplasmic tail becomes phosphorylated by Src family tyrosine kinases, enabling recruitment of adapter GRB2 and phosphatase SHIP1/INPP5D . This inhibits PI3K and MAPK signaling cascades crucial for T cell activation. Additionally, TIGIT associates with beta-arrestin-2/ARRB2 to recruit SHIP1/INPP5D, which suppresses autoubiquitination of TRAF6 and subsequently inhibits the NF-kappa-B signaling pathway . TIGIT also functions by competing with the activating receptor DNAM-1 for binding to CD155, as demonstrated by experiments showing that blocking DNAM-1 inhibits CIK-mediated lysis of CD155-expressing tumor cells . Understanding these mechanistic details is essential for designing targeted interventions that modulate TIGIT activity.

What is the scientific rationale for combining TIGIT blockade with other checkpoint inhibitors?

Dual PD-1/TIGIT blockade potently increases tumor antigen-specific CD8+ T cell expansion and function in vitro and promotes tumor rejection in mouse tumor models . This synergistic effect occurs because TIGIT and PD-1 utilize distinct but complementary inhibitory mechanisms. While PD-1 primarily affects TCR and CD28 signaling pathways, TIGIT functions through SHIP1-mediated inhibition and competition with DNAM-1. When designing combination therapy studies, researchers should examine pathway-specific markers to determine mechanistic independence versus overlap, and consider sequential versus simultaneous blockade protocols to optimize anti-tumor effects.

How does Fc engineering affect anti-TIGIT antibody efficacy?

Engineering of Fc variants of anti-TIGIT antibodies with enhanced Fc-mediated effector functions yields further improvements in antitumor efficacy beyond simple TIGIT blockade . Research demonstrates that anti-TIGIT antibodies exert antitumor effects through multiple immunological impacts, including CD8+ T cell responses and Fc-mediated effector functions through NK cells that significantly reduce intratumoral regulatory T cells . This Treg reduction activates additional antitumor CD8+ T cell responses targeting tumor-shared antigens normally suppressed by Tregs, conferring cross-tumor immune memory. When developing therapeutic anti-TIGIT antibodies, researchers should carefully consider Fc domain engineering as a critical design parameter.

What is the relationship between TIGIT and autoimmune disorders?

Studies in murine models of experimental autoimmune encephalomyelitis (EAE) have demonstrated that loss of TIGIT expression results in hyperproliferative T cell responses and increased susceptibility to autoimmune disease . Agonistic anti-TIGIT monoclonal antibodies directly inhibit T cell responses even in the absence of antigen-presenting cells, demonstrating a T cell-intrinsic inhibitory effect . This suggests TIGIT plays a protective role against autoimmunity, in contrast to its potentially detrimental role in cancer immunity. Researchers studying autoimmune conditions should incorporate TIGIT functional assessment in their experimental designs, particularly when exploring tolerance mechanisms.

What are effective methods for generating TIGIT knockout models?

TIGIT knockout models can be efficiently generated using CRISPR-Cas9 genome editing. A validated approach involves designing a sgRNA targeting the TIGIT gene's IgV domain (e.g., 5′-TTCAGTCTTCAGTGATCGGG-3' followed by 5'-TGG-3' PAM sequence) . The sgRNA recruits Cas9 endonuclease to introduce a double-strand break resulting in deletion mutations. For verification, researchers should construct primer pairs with forward primers on intron 1 and reverse primers on intron 2 to detect the deletion in exon 2 . Additionally, functional validation through flow cytometry using anti-TIGIT antibodies against isolated immune populations (NK cells, T cells, CD4+ and CD8+ T cells) is essential to confirm successful knockout .

What techniques are most suitable for quantifying TIGIT expression and functional activity?

Multiple complementary approaches can quantify TIGIT expression and function:

• Flow cytometry with anti-TIGIT antibodies combined with lineage markers (CD3, Ncr1, CD4, CD8) provides cellular resolution of expression patterns .

• ELISA kits enable quantitative measurement of TIGIT protein in cell culture extracts with high sensitivity and reproducibility, as shown in the following performance data:

• Functional assays measuring cytokine production (IFN-γ, IL-6, TNF-α) following TIGIT engagement or blockade provide insights into its inhibitory activity .

• Cytotoxicity assays comparing TIGIT-blocked versus unblocked effector cells against target cells expressing CD155 directly assess functional consequences of TIGIT manipulation .

How should researchers design experiments to assess TIGIT and DNAM-1 competitive interactions?

To properly evaluate the competitive relationship between inhibitory TIGIT and activating DNAM-1 receptors for CD155 binding, researchers should implement a multi-arm experimental design. First, measure baseline cytotoxicity or cytokine production of effector cells against CD155-expressing targets. Then, systematically block: (1) TIGIT alone, (2) DNAM-1 alone, (3) CD155 alone, and (4) combinations of these molecules . Critical controls include using CD155-negative targets and isotype control antibodies. In published models, blocking DNAM-1 inhibited CIK-mediated lysis of CD155-expressing A375 cells but had no effect on lysis of CD155-negative K562 cells, demonstrating the specificity of the TIGIT/DNAM-1/CD155 axis . Using recombinant proteins with quantifiable binding affinities can further elucidate competitive binding dynamics.

What are best practices for developing anti-TIGIT blocking antibodies?

Development of effective anti-TIGIT blocking antibodies requires targeting the segment connecting F and G strands of TIGIT's extracellular IgV domain, as this region is critical for ligand interaction . When evaluating candidate antibodies, researchers should assess: (1) binding affinity to TIGIT; (2) blockade of TIGIT-CD155 interaction; (3) enhancement of effector cell functions (proliferation, cytokine production); (4) Fc-dependent effector functions; and (5) cross-species reactivity if translational studies are planned . Importantly, evidence suggests that antibodies with enhanced Fc-mediated functions show superior anti-tumor efficacy, so Fc engineering should be considered during development .

How do TIGIT expression patterns differ between healthy individuals and cancer patients?

Recent research shows distinct patterns of TIGIT expression between healthy individuals and cancer patients, with higher expression observed on tumor-infiltrating lymphocytes compared to peripheral blood lymphocytes. Research protocols investigating these differences should include paired samples of peripheral blood and tumor tissue, age-matched healthy controls, and multiparameter flow cytometry to distinguish TIGIT expression across diverse immune cell subsets. Understanding these differential expression patterns may reveal opportunities for targeting TIGIT in specific patient populations or disease contexts.

What biomarkers predict response to TIGIT blockade therapies?

Identifying biomarkers that predict response to TIGIT blockade represents a critical research direction. Investigators should examine correlations between treatment outcomes and: (1) baseline TIGIT expression levels on different immune populations; (2) CD155/CD112 expression levels in tumor microenvironment; (3) TIGIT/DNAM-1 expression ratio; and (4) comprehensive immune profiling of pre-treatment samples. Single-cell analyses of tumor-infiltrating lymphocytes before and after TIGIT blockade can provide insights into changes in T cell states and clonal expansion patterns that correlate with therapeutic response.

How does TIGIT function differ across various human tumor types?

TIGIT's inhibitory function may vary across tumor types based on the immune contexture and ligand availability. Research approaches should include comparative analyses of TIGIT expression, signaling, and function across multiple tumor models with diverse immune infiltration patterns. Experiments should examine whether TIGIT's primary mechanism of action (direct inhibitory signaling versus DNAM-1 competition) differs between tumor contexts, which would inform tumor-specific therapeutic strategies. Meta-analyses of TIGIT expression across multiple cancer types can guide prioritization of indications for clinical development.

What is the impact of TIGIT polymorphisms on immune function and disease susceptibility?

Genetic variations in TIGIT may influence its expression, binding affinity to ligands, or downstream signaling capacity. Research investigating these variations should employ genotyping of TIGIT loci in diverse populations, paired with functional assessment of variant TIGIT proteins. Studies examining associations between TIGIT polymorphisms and autoimmune disease or cancer susceptibility could reveal important insights into personalized approaches to TIGIT-targeted therapies.