Involvement of Actin Filaments in the Cytotoxic Effect of GD2-Specific Antibodies

Therapeutic efficacy of antibody-drug conjugates targeting GD2-positive tumors

Background

Both ganglioside GD2-targeted immunotherapy and antibody-drug conjugates (ADCs) have demonstrated clinical success as solid tumor therapies in recent years, yet no research has been carried out to develop anti-GD2 ADCs against solid tumors. This is the first study to analyze cytotoxic activity of clinically relevant anti-GD2 ADCs in a wide panel of cell lines with varying GD2 expression and their effects in mouse models of GD2-positive solid cancer.

Methods

Anti-GD2 ADCs were generated based on the GD2-specific antibody ch14.18 approved for the treatment of neuroblastoma and commonly used drugs monomethyl auristatin E (MMAE) or F (MMAF), conjugated via a cleavable linker by thiol-maleimide chemistry. The antibody was produced in a mammalian expression system, and its specific binding to GD2 was analyzed. Antigen-binding properties and biodistribution of the ADCs in mice were studied in comparison with the parent antibody. Cytotoxic effects of the ADCs were evaluated in a wide panel of GD2-positive and GD2-negative tumor cell lines of neuroblastoma, glioma, sarcoma, melanoma, and breast cancer. Their antitumor effects were studied in the B78-D14 melanoma and EL-4 lymphoma syngeneic mouse models.

Results

The ch14.18-MMAE and ch14.18-MMAF ADCs retained antigen-binding properties of the parent antibody. Direct dependence of the cytotoxic effect on the level of GD2 expression was observed in cell lines of different origin for both ADCs, with IC50 below 1 nM for the cells with high GD2 expression and no cytotoxic effect for GD2-negative cells. Within the analyzed cell lines, ch14.18-MMAF was more effective in the cells overexpressing GD2, while ch14.18-MMAE had more prominent activity in the cells expressing low GD2 levels. The ADCs had a similar biodistribution profile in the B78-D14 melanoma model compared with the parent antibody, reaching 7.7% ID/g in the tumor at 48 hours postinjection. The average tumor size in groups treated with ch14.18-MMAE or ch14.18-MMAF was 2.6 times and 3.8 times smaller, respectively, compared with the control group. Antitumor effects of the anti-GD2 ADCs were also confirmed in the EL-4 lymphoma model.

Conclusion

These findings validate the potential of ADCs targeting ganglioside GD2 in treating multiple GD2-expressing solid tumors.

Gangliosides as Signaling Regulators in Cancer

At the plasma membrane, gangliosides, a group of glycosphingolipids, are expressed along with glycosphingolipids, phospholipids, and cholesterol in so-called lipid rafts that interact with signaling receptors and related molecules. Most cancers present abnormalities in the intracellular signal transduction system involved in tumor growth, invasion, and metastasis. To date, the roles of gangliosides as regulators of signal transduction have been reported in several cancer types. Gangliosides can be expressed by the exogenous ganglioside addition, with their endogenous expression regulated at the enzymatic level by targeting specific glycosyltransferases. Accordingly, the relationship between changes in the composition of cell surface gangliosides and signal transduction has been investigated by controlling ganglioside expression. In cancer cells, several types of signaling molecules are positively or negatively regulated by ganglioside expression levels, promoting malignant properties. Moreover, antibodies against gangliosides have been shown to possess cytotoxic effects on ganglioside-expressing cancer cells. In the present review, we highlight the involvement of gangliosides in the regulation of cancer cell signaling, and we explore possible therapies targeting ganglioside-expressing cancer.

RNA Sequencing-Based Identification of Ganglioside GD2-Positive Cancer Phenotype

The tumor-associated ganglioside GD2 represents an attractive target for cancer immunotherapy. GD2-positive tumors are more responsive to such targeted therapy, and new methods are needed for the screening of GD2 molecular tumor phenotypes. In this work, we built a gene expression-based binary classifier predicting the GD2-positive tumor phenotypes. To this end, we compared RNA sequencing data from human tumor biopsy material from experimental samples and public databases as well as from GD2-positive and GD2-negative cancer cell lines, for expression levels of genes encoding enzymes involved in ganglioside biosynthesis. We identified a 2-gene expression signature combining ganglioside synthase genes ST8SIA1 and B4GALNT1 that serves as a more efficient predictor of GD2-positive phenotype (Matthews Correlation Coefficient (MCC) 0.32, 0.88, and 0.98 in three independent comparisons) compared to the individual ganglioside biosynthesis genes (MCC 0.02-0.32, 0.1-0.75, and 0.04-1 for the same independent comparisons). No individual gene showed a higher MCC score than the expression signature MCC score in two or more comparisons. Our diagnostic approach can hopefully be applied for pan-cancer prediction of GD2 phenotypes using gene expression data.