LGALS9 Antibody

What is LGALS9 and what are its major functions in immune regulation?

LGALS9 (Galectin-9) is an immune checkpoint molecule that plays diverse roles in immune regulation. It consists of an N-terminal carbohydrate recognition domain (N-CRD) and a C-terminal carbohydrate recognition domain (C-CRD) connected by a linker region. In normal physiology, LGALS9 helps maintain immune homeostasis, but in cancer settings, it often contributes to immunosuppression.

LGALS9 exerts its immunoregulatory functions by binding to receptors like TIM-3 on immune cells, which can induce T-cell death and suppress immune responses. This immune checkpoint activity makes it particularly relevant in cancer biology, where it can protect tumor cells from immune surveillance . Expression studies have shown that LGALS9 is highly upregulated in multiple cancer types compared to normal tissues, including glioblastoma, pancreatic cancer, and acute myeloid leukemia .

How can LGALS9 expression be detected in experimental settings?

LGALS9 expression can be detected through multiple complementary methods. Immunohistochemistry (IHC) allows visualization of LGALS9 in formalin-fixed paraffin-embedded tissues, revealing both localization patterns and expression levels. Flow cytometry enables quantitative analysis of LGALS9 expression in cell populations, including intracellular staining for detailed examination .

In research models like the KC mice (K-rasLSL.G12D/+;Pdx-1-Cre) with pancreatic intraepithelial neoplasia (PanIN), LGALS9 shows distinct expression patterns. Immunofluorescence staining can detect LGALS9 in both regulatory T cells (Tregs) and conventional T cells (Tconv). Western blotting may also be employed, though some antibody clones, like those described in the literature, may not efficiently detect denatured LGALS9 .

What is the relationship between LGALS9 expression and cancer progression?

LGALS9 expression significantly increases in pancreatic tissues during cancer progression. Studies in transgenic KC mouse models have demonstrated that LGALS9 is weakly expressed or absent in healthy pancreatic tissue (WT mice) but shows strong expression in PanIN lesions of all stages. LGALS9 staining appears strongly at the apex and in the nucleus of cancer cells, with diffuse cytoplasmic expression .

Flow cytometric analysis confirms a significant increase in LGALS9 expression in pancreatic tissue of KC mice (RFI: 3.03) compared to WT mice (RFI: 1.63). This elevated expression is observed across different age groups and particularly in CD45- pancreatic cells, suggesting that tumor cells themselves are a major source of LGALS9 . The expression correlation with disease stage makes LGALS9 both a potential biomarker and therapeutic target.

What are the prognostic implications of LGALS9 in different cancer types?

The prognostic value of LGALS9 varies significantly across cancer types. While LGALS9 expression is associated with favorable outcomes in some cancers, it correlates with poor prognosis in difficult-to-treat cancers including brain tumors, pancreatic cancer, and acute myeloid leukemia .

Elevated LGALS9 levels in tumor tissues and plasma have been shown to correlate with poor patient survival rates and aggressive disease in multiple tumor types. In glioblastoma multiforme, LGALS9 is highly upregulated compared to normal brain tissues and lower-grade gliomas, and this high expression correlates with poor patient survival. Similarly, LGALS9 is highly expressed in both tumor cells and immune cells of patients with pancreatic ductal adenocarcinoma . These findings suggest that therapeutic targeting of LGALS9 might be particularly beneficial in these cancer types.

What are the key considerations when designing anti-LGALS9 antibody experiments?

When designing experiments with anti-LGALS9 antibodies, researchers should first determine which domain of LGALS9 they need to target. Evidence suggests that antibodies targeting the N-CRD of LGALS9 can effectively block its interaction with TIM-3 and prevent T-cell death . This domain specificity is crucial for designing functional neutralizing antibodies.

Cross-reactivity testing is essential, as demonstrated in studies where human LGALS9 antibodies were tested against mouse LGALS9. While some antibodies developed against human LGALS9 can cross-react with mouse LGALS9 due to sequence homology (such as the 1G3 clone targeting the TPAIPPMPHP amino acid sequence in human LGALS9 and the TPGIPPVYPTP sequence in mouse LGALS9, which share 69% homology), many antibodies are species-specific . Additionally, researchers should test for cross-reactivity with other galectin family members, such as Galectin-1 and Galectin-8, to ensure specificity .

How can researchers validate the neutralizing capacity of anti-LGALS9 antibodies?

Validation of anti-LGALS9 neutralizing antibodies requires multiple functional assays. The gold standard is T-cell protection assays, where human T cells expanded from peripheral blood mononuclear cells (PBMCs) are incubated with LGALS9 in the presence or absence of the antibody, with cell survival measured by MTS or similar viability assays .

For more precise quantification, researchers can use annexin V/propidium iodide staining to measure apoptosis or Cell Counting Kit-8 (CCK-8) assays to assess cell viability. These methods help determine the antibody's potency in preventing LGALS9-induced cell death. Binding affinity should be assessed by ELISA, allowing comparison between different antibody clones. Functional validation can also include plate-based binding assays to confirm that the antibody blocks the interaction between LGALS9 (particularly the N-CRD) and its receptors like TIM-3 .

What mechanisms underlie the therapeutic effects of anti-LGALS9 antibodies in cancer models?

Anti-LGALS9 antibodies exert therapeutic effects through multiple mechanisms. Primarily, they neutralize LGALS9's immunosuppressive functions by preventing its interaction with receptors like TIM-3, thereby protecting T cells from LGALS9-induced death and restoring anti-tumor immune responses .

In pancreatic cancer mouse models (KC mice), anti-LGALS9 treatment demonstrates multiple effects: (1) reduction of LGALS9 expression in pancreatic cancer cells, (2) decreased regulatory T cell (Treg) infiltration, and (3) inhibition of pancreatic intraepithelial neoplasia (PanIN) progression and grade . The antibody appears to function by targeting both endogenous LGALS9 produced by tumor cells and exogenous LGALS9 produced by Tregs.

Mechanistically, anti-LGALS9 antibodies can inhibit Treg suppressive activity, as demonstrated in mixed lymphocyte reaction assays where the addition of anti-LGALS9 partially restored T cell proliferation (83±2.3%) that was suppressed by Tregs (43±3.6% reduction) . This suggests that targeting LGALS9 affects both the tumor cells directly and the immunosuppressive microenvironment.

How does LGALS9 expression in regulatory T cells impact cancer immunosuppression?

LGALS9 expression in regulatory T cells (Tregs) represents a critical mechanism of cancer immunosuppression. Studies have demonstrated that Tregs express LGALS9 intracellularly, and this expression contributes to their immunosuppressive functions . Flow cytometry and immunofluorescence analyses confirm LGALS9 expression in both Tregs and conventional T cells (Tconv).

In pancreatic cancer models, significant increases in both circulating and pancreas-infiltrating Tregs are observed in KC mice compared to WT controls. This Treg infiltration occurs early and is sustained throughout cancer development, correlating with increased LGALS9 expression . The immunosuppressive effect of Tregs is partly mediated by LGALS9, as demonstrated by suppression assays where anti-LGALS9 antibodies partially restored the proliferation of T cells co-cultured with Tregs (increasing from 43±3.6% to 83±2.3%) . This finding highlights the therapeutic potential of targeting LGALS9 to neutralize Treg-mediated immunosuppression in the tumor microenvironment.

What technical challenges exist in developing effective anti-LGALS9 antibodies?

Developing effective anti-LGALS9 antibodies presents several technical challenges. First, antibodies must exhibit high binding specificity to LGALS9 without cross-reactivity to other galectin family members. Studies have shown that carefully developed antibodies can achieve this specificity, with no significant cross-reactivity to Galectin-1 or Galectin-8 .

Domain-specific targeting represents another challenge. Most effective neutralizing antibodies target the N-CRD of LGALS9, which mediates binding to receptors like TIM-3 . Antibodies must be tested for their ability to block specific protein-protein interactions rather than merely binding to LGALS9.

Application-specific validation is essential, as some antibodies may work well in certain applications but not others. For example, some antibodies effectively stain intracellular LGALS9 in flow cytometry and immunocytochemistry but fail to detect denatured LGALS9 in Western blotting . Finally, ensuring cross-species reactivity (or intentional species-specificity) requires detailed epitope mapping and validation across different experimental systems. Researchers have successfully addressed this challenge by identifying homologous sequences between human and mouse LGALS9 that can be targeted for cross-species recognition .

How can researchers interpret contradictory findings regarding LGALS9 function across different cancer models?

Interpreting contradictory findings regarding LGALS9 function requires careful consideration of context-dependent factors. The dual role of LGALS9 as both a favorable and unfavorable prognostic marker across different cancer types illustrates this complexity . Researchers should evaluate:

• Cancer type specificity: LGALS9's role varies substantially between cancer types. While it correlates with poor prognosis in glioblastoma and pancreatic cancer, it may have different implications in other cancers .

• Cellular source: LGALS9 is expressed by both tumor cells and immune cells, including Tregs. Distinguishing between these sources is crucial for understanding its function in a specific context .

• Receptor interaction: The presence and abundance of LGALS9 receptors (like TIM-3) in the experimental system significantly influences observed effects. Researchers should characterize receptor expression alongside LGALS9 levels .

• Experimental system differences: Results from in vitro systems, mouse models, and human samples may vary. For example, anti-LGALS9 antibodies might show different efficacy in cell lines versus complex tumor microenvironments .

When contradictory findings emerge, researchers should systematically investigate these factors to determine whether they represent genuine biological differences or technical variations in experimental approaches.

What are the optimal methods for validating anti-LGALS9 antibody specificity?

Validating anti-LGALS9 antibody specificity requires a multi-faceted approach. The gold standard involves testing antibodies in LGALS9 knockout systems. Researchers have validated antibody specificity using CRISPR-Cas9-generated LGALS9 knockout Jurkat T cells, where strong staining was observed in wild-type cells but none in knockout cells, confirming high binding specificity .

Cross-reactivity testing is essential and should examine binding to:

• Other galectin family members (particularly Galectin-1 and Galectin-8)

• LGALS9 from different species (human versus mouse)

• Individual domains of LGALS9 (N-CRD versus C-CRD)

ELISA assays can quantify binding affinity and specificity by coating plates with recombinant LGALS9, other galectins, or domain-specific constructs. Antibody clones like 292-13 and 292-18A have demonstrated higher binding affinity to LGALS9 compared to commercially available alternatives, highlighting the importance of comparative validation .

What in vivo models are most appropriate for testing anti-LGALS9 immunotherapies?

The selection of appropriate in vivo models for testing anti-LGALS9 immunotherapies depends on the cancer type and research questions. For pancreatic cancer, the K-rasLSL.G12D/+;Pdx-1-Cre (KC) transgenic mouse model has proven valuable as it recapitulates the progressive development of pancreatic intraepithelial neoplasia (PanIN) that precedes pancreatic ductal adenocarcinoma (PDAC) .

This model demonstrates increased LGALS9 expression in pancreatic tissue compared to wild-type controls, along with elevated Treg infiltration, making it suitable for evaluating anti-LGALS9 immunotherapy . Treatment protocols typically involve regular antibody administration (e.g., one injection per week for 8 weeks), starting at early disease stages when LGALS9 expression and Treg infiltration begin to increase .

For other cancer types, appropriate models should reflect the relevant LGALS9 biology. Humanized mouse models have also been used for evaluating anti-LGALS9 antibodies in nasopharyngeal carcinoma, demonstrating that neutralizing human LGALS9 can induce strong anti-tumor immune responses . The choice of model should align with the antibody's species specificity, the cancer's LGALS9 expression pattern, and the presence of relevant immune cell populations.

How can researchers quantitatively assess the functional effects of anti-LGALS9 antibodies?

Quantitative assessment of anti-LGALS9 antibody functional effects should employ multiple complementary approaches:

• T-cell protection assays: Measure the ability of antibodies to protect T cells from LGALS9-induced death. This can be quantified using:

  • MTS viability assays (showing percentage of viable cells)

  • Annexin V/propidium iodide staining (to distinguish early and late apoptotic cells)

  • Cell Counting Kit-8 (CCK-8) assays for cell viability

• Proliferation assays: Assess how anti-LGALS9 antibodies restore T-cell proliferation inhibited by recombinant LGALS9. For example, studies have shown that rLGALS9 inhibits T-cell proliferation by 47±1.5%, while addition of anti-LGALS9 restores proliferation to 92±1.8% .

• Treg suppression assays: Evaluate the antibody's ability to neutralize Treg suppressive function in mixed lymphocyte reaction (MLR) assays. Quantification can reveal what percentage of Tconv proliferation is restored when anti-LGALS9 is added to Tconv-Treg co-cultures .

• In vivo efficacy metrics: For animal models, researchers should quantify PanIN progression and grade using validated software (like FIJI) with pathologist verification, measure changes in LGALS9 expression by flow cytometry (reporting relative fluorescence intensity values), and analyze Treg infiltration in both circulation and tumor tissue .

What complementary markers should be analyzed alongside LGALS9 in immunophenotyping studies?

Comprehensive immunophenotyping alongside LGALS9 analysis should include several complementary markers to understand the broader immunological context:

• T-cell populations: CD4 (for conventional T cells), CD25 and FOXP3 (for regulatory T cells), CD8 (for cytotoxic T cells), and CD3 (for pan-T cells) .

• T-cell functional status: TIM-3 (a key LGALS9 receptor), PD-1, CTLA-4, and LAG-3 (other immune checkpoints often co-expressed). Studies have shown that most T cells used in LGALS9-induced death experiments express TIM-3, highlighting the importance of assessing this receptor .

• Myeloid populations: CD45 (to distinguish immune from non-immune cells), markers for M2 macrophages (which have been implicated in LGALS9-mediated immunosuppression in PDAC), and markers for myeloid-derived suppressor cells .

• Activation/exhaustion markers: Ki-67 (proliferation), IFN-γ, TNF-α, IL-2 (T-cell function), and markers of T-cell exhaustion to assess the functional consequences of LGALS9 blockade.

When analyzing tissue samples, researchers should distinguish between tumor cells and infiltrating immune cells, as both can express LGALS9. Flow cytometry gating strategies should include clear discrimination between CD45+ and CD45- populations to enable separate analysis of LGALS9 expression in tumor versus immune cells .

How does LGALS9 compare to other immune checkpoint molecules in therapeutic potential?

LGALS9 represents a promising immune checkpoint target with distinct features compared to established targets like PD-1/PD-L1 and CTLA-4. In pancreatic cancer, LGALS9 expression levels have been found to be significantly higher than those of PD-L1, suggesting it may be a more abundant target in this notoriously immunotherapy-resistant cancer type .

Unlike PD-1/PD-L1 which primarily acts by inhibiting T-cell activation, LGALS9 can directly induce T-cell death through its interaction with TIM-3 and other receptors. This more profound immunosuppressive mechanism may explain why LGALS9 blocking could potentially be effective in cancers that don't respond to current checkpoint inhibitors .

LGALS9 also exhibits broader immunomodulatory effects, influencing multiple immune cell types including regulatory T cells and myeloid cells. This multi-faceted activity suggests that anti-LGALS9 therapies might address several immunosuppressive mechanisms simultaneously, potentially offering advantages over more narrowly targeted checkpoint inhibitors .

What combination strategies might enhance the efficacy of anti-LGALS9 immunotherapy?

Several combination strategies show promise for enhancing anti-LGALS9 immunotherapy efficacy:

• Combining with other checkpoint inhibitors: As LGALS9 represents just one immune checkpoint pathway, combining anti-LGALS9 with anti-PD-1/PD-L1 or anti-CTLA-4 antibodies might produce synergistic effects by blocking multiple immunosuppressive pathways simultaneously.

• Chemotherapy combinations: In pancreatic cancer, combining anti-LGALS9 with standard chemotherapy regimens like FOLFIRINOX or gemcitabine plus nab-paclitaxel might enhance treatment efficacy. The current standard of care for metastatic PDAC offers limited survival benefits (11-15 months OS), suggesting room for improvement through combination approaches .

• Targeting the tumor microenvironment: Since LGALS9 interacts with the immunosuppressive tumor microenvironment, particularly through Tregs and M2 macrophages in PDAC, combining anti-LGALS9 with agents that target these cellular components might enhance efficacy .

• Early intervention strategies: Research in the KC mouse model suggests that LGALS9 expression and Treg infiltration occur early in pancreatic neoplasia. This finding supports exploring anti-LGALS9 therapy in early disease stages or even in prevention settings for high-risk individuals .

Research should systematically evaluate these combinations through properly designed preclinical studies before advancing to clinical trials.

What are the potential biomarkers for predicting response to anti-LGALS9 immunotherapy?

Several potential biomarkers may predict response to anti-LGALS9 immunotherapy:

• LGALS9 expression levels: Baseline LGALS9 expression in tumor tissue may predict which patients are most likely to benefit from anti-LGALS9 therapy. Quantitative assessment by immunohistochemistry or flow cytometry could establish expression thresholds for patient selection .

• TIM-3 expression: As a primary receptor for LGALS9, TIM-3 expression on tumor-infiltrating lymphocytes might indicate patients whose T cells are susceptible to LGALS9-mediated suppression. Studies have confirmed TIM-3 expression on most T cells used in experimental systems .

• Regulatory T cell infiltration: Given the role of LGALS9 in Treg-mediated suppression, the density and distribution of FOXP3+ Tregs in tumor tissue might predict which tumors have LGALS9-dependent immunosuppression. Studies in KC mice showed significantly elevated Treg levels in both circulation and pancreatic tissue compared to controls .

• Immune contexture analysis: Comprehensive immune profiling of the tumor microenvironment, including the balance between effector and suppressive immune cells, may help identify tumors with an immunological profile amenable to anti-LGALS9 intervention.

Future research should validate these potential biomarkers in preclinical models and eventually in clinical trials to develop companion diagnostics for anti-LGALS9 immunotherapies.