Recognition of Dimeric Lewis X by Anti-Dimeric Lex Antibody SH2

The carbohydrate antigen dimeric Lewis X (DimLe^x), which accumulates in colonic and liver adenocarcinomas, is a valuable target to develop anti-cancer therapeutics. Using the native DimLe^x antigen as a vaccine would elicit an autoimmune response against the Le^x antigen found on normal, healthy cells. Thus, we aim to study the immunogenic potential of DimLe^x and search internal epitopes displayed by DimLe^x that remain to be recognized by anti-DimLe^x monoclonal antibodies (mAbs) but no longer possess epitopes recognized by anti-Le^x mAbs. In this context, we attempted to map the epitope recognized by anti-DimLe^x mAb SH2 by titrations and competitive inhibition experiments using oligosaccharide fragments of DimLe^x as well as Le^x analogues. We compare our results with that reported for anti-Le^x mAb SH1 and anti-polymeric Le^x mAbs 1G5F6 and 291-2G3-A. While SH1 recognizes an epitope localized to the non-reducing end Le^x trisaccharide, SH2, 1G5F6, and 291-2G3-A have greater affinity for DimLe^x conjugates than for Le^x conjugates. We show, however, that the Le^x trisaccharide is still an important recognition element for SH2, which (like 1G5F6 and 291-2G3-A) makes contacts with all three sugar units of Le^x. In contrast to mAb SH1, anti-polymeric Le^x mAbs make contact with the GlcNAc acetamido group, suggesting that epitopes extend further from the non-reducing end Le^x. Results with SH2 show that this epitope is only recognized when DimLe^x is presented by glycoconjugates. We have reported that DimLe^x adopts two conformations around the β-d-GlcNAc-(1→3)-d-Gal bond connecting the Le^x trisaccharides. We propose that only one of these conformations is recognized by SH2 and that this conformation is favored when the hexasaccharide is presented as part of a glycoconjugate such as DimLe^x-bovine serum albumin (DimLe^x-BSA). Proper presentation of the oligosaccharide candidate via conjugation to a protein or lipid is essential for the design of an anti-cancer vaccine or immunotherapeutic based on DimLe^x.

Kinetic and Structural Characterization of Sialidases (Kdnases) from Ascomycete Fungal Pathogens

Sialidases catalyze the release of sialic acid from the terminus of glycan chains. We previously characterized the sialidase from the opportunistic fungal pathogen, Aspergillus fumigatus, and showed that it is a Kdnase. That is, this enzyme prefers 3-deoxy-d-glycero-d-galacto-non-2-ulosonates (Kdn glycosides) as the substrate compared to N-acetylneuraminides (Neu5Ac). Here, we report characterization and crystal structures of putative sialidases from two other ascomycete fungal pathogens, Aspergillus terreus (AtS) and Trichophyton rubrum (TrS). Unlike A. fumigatus Kdnase (AfS), hydrolysis with the Neu5Ac substrates was negligible for TrS and AtS; thus, TrS and AtS are selective Kdnases. The second-order rate constant for hydrolysis of aryl Kdn glycosides by AtS is similar to that by AfS but 30-fold higher by TrS. The structures of these glycoside hydrolase family 33 (GH33) enzymes in complex with a range of ligands for both AtS and TrS show subtle changes in ring conformation that mimic the Michaelis complex, transition state, and covalent intermediate formed during catalysis. In addition, they can aid identification of important residues for distinguishing between Kdn and Neu5Ac substrates. When A. fumigatus, A. terreus, and T. rubrum were grown in chemically defined media, Kdn was detected in mycelial extracts, but Neu5Ac was only observed in A. terreus or T. rubrum extracts. The C8 monosaccharide 3-deoxy-d-manno-oct-2-ulosonic acid (Kdo) was also identified in A. fumigatus and T. rubrum samples. A fluorescent Kdn probe was synthesized and revealed the localization of AfS in vesicles at the cell surface.

Structurally homologous sialidases exhibit a commonality in reactivity: Glycoside hydrolase-catalyzed hydrolysis of Kdn-thioglycosides

Aspergillus fumigatus is one of the main causative agents of invasive aspergillosis, an often-lethal fungal disease that affects immunocompromised individuals. A. fumigatus produces a sialidase that cleaves the nine-carbon carbohydrate Kdn from glycoconjugates. This enzyme plays a critical role in A. fumigatus pathogenicity, and is thus a target for the development of new therapeutics. In order to understand the reactivity of this Kdnase, and to develop a sensitive and selective assay for its catalytic activity we determined whether, like its close structural homolog the excreted sialidase produced by Micromonospora viridifaciens, this enzyme can efficiently hydrolyze thioglycoside substrates. We synthesized a panel of seven aryl 2-thio-d-glycero-α-d-galacto-non-2-ulopyranosonides and measured the activity of the A. fumigatus Kdnase towards these substrates. Four of these substrates were hydrolyzed by the A. fumigatus enzyme, although M. viridifaciens sialidase-catalyzed the hydrolysis of these Kdn thioglycosides with higher catalytic efficiencies (k_cat/K_m). We also tested an enzyme that was evolved from MvNA to improve its activity against Kdn glycosides (Glycobiology 2020, 30, 325). All three enzymes catalyzed the hydrolysis of the four most reactive Kdn thioglycosides and their second-order rate constants (k_cat/K_m) display a concave downwards Brønsted plot. The kinetic data, for each enzyme, is consistent with a change in rate-limiting step from CS bond cleavage for thioglycosides in which the pK_a of the corresponding aryl thiol is >3.6, to a non-chemical step, which is likely a conformational change, that occurs prior to CS bond cleavage for the 2,3,4,5,6-pentafluorothiophenyl glycoside.

A self-immolative Kdn-glycoside substrate enables high-throughput screening for inhibitors of Kdnases

Aspergillus fumigatus, a filamentous fungus, is an opportunistic pathogen and the major causative agent of the often-fatal disease, invasive aspergillosis (IA). Current treatments for IA are limited due to their high toxicity and/or the emergence of drug resistance; therefore, a need exists for the development of new therapeutics to treat IA. The Kdnase produced by A. fumigatus plays a vital role in maintaining cell wall integrity. As there are no known Kdnases in humans, developing inhibitors of Kdnase from this fungal pathogen is a promising therapeutic approach. The rapid testing of enzymatic activity in a high-throughput screen of large chemical libraries can be an efficient way to find new small molecule lead compounds. Herein we show that a Kdn glycoside with a self-immolative cleavable aglycon is a practical and efficient substrate for a high throughput assay to identify Kdnase inhibitors. We optimized the activity assay and screened over 27,000 compounds from two bioactive chemical libraries as potential inhibitors, and we compared the hit compounds' potency towards Aspergillus terreus and Trichophyton rubrum Kdnases, two other fungal Kdnases. We validated a number of hits and these small molecules are potential leads for the development of novel therapeutics to treat invasive aspergillosis.

Selective inhibitors of the TrkC.T1 receptor reduce retinal inflammation and delay neuronal death in a model of retinitis pigmentosa

The heterogeneity of receptor isoforms can cause an apparent paradox where each isoform can promote different or even opposite biological pathways. One example is the neurotrophin receptor TrkC. The trkC mRNA translates a full-length receptor tyrosine kinase (TrkC-FL) whose activation by the growth factor NT3 promotes neuronal survival. In some diseases, the trkC mRNA is spliced to a kinase-truncated isoform (TrkC.T1) whose activation by NT3 up-regulates tumor necrosis factor alpha (TNF-α) causing neurotoxicity. Since TrkC.T1 expression is significantly increased at the onset of neurodegeneration, we hypothesized that in disease TrkC.T1-mediated toxicity prevails over TrkC-FL-mediated survival. To study this, we developed small molecules that selectively antagonize NT3-driven TrkC.T1 neurotoxicity without compromising TrkC-FL survival. In a genetic mouse model of retinitis pigmentosa, therapeutic administration of TrkC.T1 antagonists prevents elevation of TNF-α and reduces photoreceptor neuronal death. This work demonstrates the importance of accounting for functional and structural heterogeneity in receptor-ligand interactions, illustrates chemical biology strategies to develop isoform-selective agents, validates TrkC.T1 as a druggable target, and expands the therapeutic concept of reducing neurotoxicity as a strategy to achieve neuroprotection.

The cancer glycocode as a family of diagnostic biomarkers, exemplified by tumor-associated gangliosides

One unexploited family of cancer biomarkers comprise glycoproteins, carbohydrates, and glycolipids (the Tumor Glycocode).A class of glycolipid cancer biomarkers, the tumor-marker gangliosides (TMGs) are presented here as potential diagnostics for detecting cancer, especially at early stages, as the biological function of TMGs makes them etiological. We propose that a quantitative matrix of the Cancer Biomarker Glycocode and artificial intelligence-driven algorithms will expand the menu of validated cancer biomarkers as a step to resolve some of the challenges in cancer diagnosis, and yield a combination that can identify a specific cancer, in a tissue-agnostic manner especially at early stages, to enable early intervention. Diagnosis is critical to reducing cancer mortality but many cancers lack efficient and effective diagnostic tests, especially for early stage disease. Ideal diagnostic biomarkers are etiological, samples are preferably obtained via non-invasive methods (e.g. liquid biopsy of blood or urine), and are quantitated using assays that yield high diagnostic sensitivity and specificity for efficient diagnosis, prognosis, or predicting response to therapy. Validated biomarkers with these features are rare. While the advent of proteomics and genomics has led to the identification of a multitude of proteins and nucleic acid sequences as cancer biomarkers, relatively few have been approved for clinical use. The use of multiplex arrays and artificial intelligence-driven algorithms offer the option of combining data of known biomarkers; however, for most, the sensitivity and the specificity are below acceptable criteria, and clinical validation has proven difficult. One strategic solution to this problem is to expand the biomarker families beyond those currently exploited. One unexploited family of cancer biomarkers comprise glycoproteins, carbohydrates, and glycolipids (the Tumor Glycocode). Here, we focus on a family of glycolipid cancer biomarkers, the tumor-marker gangliosides (TMGs). We discuss the diagnostic potential of TMGs for detecting cancer, especially at early stages. We include prior studies from the literature to summarize findings for ganglioside quantification, expression, detection, and biological function and its role in various cancers. We highlight the examples of TMGs exhibiting ideal properties of cancer diagnostic biomarkers, and the application of GD2 and GD3 for diagnosis of early stage cancers with high sensitivity and specificity. We propose that a quantitative matrix of the Cancer Biomarker Glycocode and artificial intelligence-driven algorithms will expand the menu of validated cancer biomarkers as a step to resolve some of the challenges in cancer diagnosis, and yield a combination that can identify a specific cancer, in a tissue-agnostic manner especially at early stages, to enable early intervention.

GD2 and GD3 gangliosides as diagnostic biomarkers for all stages and subtypes of epithelial ovarian cancer

Background

Ovarian cancer (OC) is the deadliest gynecological cancer, often diagnosed at advanced stages. A fast and accurate diagnostic method for early-stage OC is needed. The tumor marker gangliosides, GD2 and GD3, exhibit properties that make them ideal potential diagnostic biomarkers, but they have never before been quantified in OC. We investigated the diagnostic utility of GD2 and GD3 for diagnosis of all subtypes and stages of OC.

Methods

This retrospective study evaluated GD2 and GD3 expression in biobanked tissue and serum samples from patients with invasive epithelial OC, healthy donors, non-malignant gynecological conditions, and other cancers. GD2 and GD3 levels were evaluated in tissue samples by immunohistochemistry (n=299) and in two cohorts of serum samples by quantitative ELISA. A discovery cohort (n=379) showed feasibility of GD2 and GD3 quantitative ELISA for diagnosing OC, and a subsequent model cohort (n=200) was used to train and cross-validate a diagnostic model.

Results

GD2 and GD3 were expressed in tissues of all OC subtypes and FIGO stages but not in surrounding healthy tissue or other controls. In serum, GD2 and GD3 were elevated in patients with OC. A diagnostic model that included serum levels of GD2+GD3+age was superior to the standard of care (CA125, p<0.001) in diagnosing OC and early-stage (I/II) OC.

Conclusion

GD2 and GD3 expression was associated with high rates of selectivity and specificity for OC. A diagnostic model combining GD2 and GD3 quantification in serum had diagnostic power for all subtypes and all stages of OC, including early stage. Further research exploring the utility of GD2 and GD3 for diagnosis of OC is warranted.