Glycoproteins are an underexploited drug target for cancer therapeutics. In this work, we integrated computational methods in network pharmacology and in silico docking approaches to identify phytochemical compounds that could potentially interact with several cancer-associated glycoproteins. We first created a database of phytochemicals from selected plant species, Manilkara zapota (sapodilla/chico), Mangifera indica (mango), Annona muricata (soursop/guyabano), Artocarpus heterophyllus (jackfruit/langka), Lansium domesticum (langsat/lanzones), and Antidesma bunius (bignay), and performed pharmacokinetic analysis to determine their drug-likeness properties. We then constructed a phytochemical-glycoprotein interaction network and characterized the degree of interactions between the phytochemical compounds and with cancer-associated glycoproteins and other glycosylation-related proteins. We found a high degree of interactions from α-pinene (Mangifera indica), cyanomaclurin (Artocarpus heterophyllus), genistein (Annona muricata), kaempferol (Annona muricata and Antidesma bunius), norartocarpetin (Artocarpus heterophyllus), quercetin (Annona muricata, Antidesma bunius, Manilkara zapota, Mangifera indica), rutin (Annona muricata, Antidesma bunius, Lansium domesticum), and ellagic acid (Antidesma bunius and Mangifera indica). Subsequent docking analysis confirmed that these compounds could potentially bind to EGFR, AKT1, KDR, MMP2, MMP9, ERBB2, IGF1R, MTOR, and HRAS proteins, which are known cancer biomarkers. In vitro cytotoxicity assays of the plant extracts showed that the n-hexane, ethyl acetate, and methanol leaf extracts from A. muricata, L. domesticum and M. indica gave the highest growth inhibitory activity against A549 lung cancer cells. These may help further explain the reported cytotoxic activities of select compounds from these plant species.

A multi-glycomic method for characterizing the glycocalyx was employed to identify the difference between 2-dimensional (2D) and 3-dimensional (3D) culture models with two human colorectal cancer cell lines, HCT116 and HT29. 3D cell cultures are considered more representative of cancer due to their ability to mimic the microenvironment found in tumors. For this reason, they have become an important tool in cancer research. Cell-cell interactions increase in 3D models compared to 2D, indeed significant glycomic changes were observed for each cell line. Analyses included the N-glycome, O-glycome, glycolipidome, glycoproteome, and proteome providing the most extensive characterization of the glycocalyx between 3D and 2D thus far. The different glycoconjugates were affected in different ways. In the N-glycome, the 3D cells increased in high-mannose glycosylation and in core fucosylation. Glycolipids increased in sialylation. Specific glycoproteins were found to increase in the 3D cell, elucidating the pathways that are affected between the two models. The results show large structural and biological changes between the 2 models suggesting that the 2 are indeed very different potentially affecting individual outcomes in the study of diseases.

Cancer progression is linked to aberrant protein glycosylation due to the overexpression of several glycosylation enzymes. These enzymes are underexploited as potential anticancer drug targets and the development of rapid-screening methods and identification of glycosylation inhibitors are highly sought. An integrated bioinformatics and mass spectrometry-based glycomics-driven glycoproteomics analysis pipeline was performed to identify an N-glycan inhibitor against lung cancer cells. Combined network pharmacology and in silico screening approaches were used to identify a potential inhibitor, pictilisib, against several glycosylation-related proteins, such as Alpha1-6FucT, GlcNAcT-V, and Alpha2,6-ST-I. A glycomics assay of lung cancer cells treated with pictilisib showed a significant reduction in the fucosylation and sialylation of N-glycans, with an increase in high mannose-type glycans. Proteomics analysis and in vitro assays also showed significant upregulation of the proteins involved in apoptosis and cell adhesion, and the downregulation of proteins involved in cell cycle regulation, mRNA processing, and protein translation. Site-specific glycoproteomics analysis further showed that glycoproteins with reduced fucosylation and sialylation were involved in apoptosis, cell adhesion, DNA damage repair, and chemical response processes. To determine how the alterations in N-glycosylation impact glycoprotein dynamics, modeling of changes in glycan interactions of the ITGA5-ITGB1 (Integrin alpha 5-Integrin beta-1) complex revealed specific glycosites at the interface of these proteins that, when highly fucosylated and sialylated, such as in untreated A549 cells, form greater hydrogen bonding interactions compared to the high mannose-types in pictilisib-treated A549 cells. This study highlights the use of mass spectrometry to identify a potential glycosylation inhibitor and assessment of its impact on cell surface glycoprotein abundance and protein-protein interaction.

Aberrant glycosylation has been extensively reported in cancer, with fundamental changes in the glycosylation patterns of cell-surface and secreted proteins largely occurring during cancer progression. As such, serum glycan and glycopeptide biomarkers have been discovered using mass spectrometry and proposed for cancer detection. Here, we report for the first time potential serum N-glycan and glycopeptide biomarkers for Philippine lung cancer patients. The N-glycan and glycoprotein profiles of a cohort (n = 26 patients, n = 22 age- and gender-matched) of lung cancer patients were analyzed and compared to identify potential N-glycan and glycopeptide serum biomarkers using nano-QToF-MS/MS and ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry dynamic multiple monitoring methods, respectively. Statistical analyses identified differential N-glycan and glycopeptide abundances. The N-glycans were mostly sialylated and sialofucosylated branched structures. The glycopeptides involved proteins in complement and coagulation cascades (p _adj = 6.418 × 10^-4), innate immunity (p _adj = 6.094 × 10^-3), acute inflammatory response (p _adj = 6.404 × 10^-5), defense response (p _adj = 2.082 × 10^-4), complement activation pathways (p _adj = 1.895 × 10^-2), and immunoglobulin-mediated immune response pathways (p _adj = 4.818 × 10^-2). Biomarker models were constructed using serum N-glycans [area under the curve (AUC) = 0.775; 95% CI: 0.617-0.931] and glycopeptides (AUC = 0.959; 95% CI: 0.85-1.0), with glycopeptides having higher accuracies than N-glycans. The results suggest that in the Philippine lung cancer patient sera, specific N-glycans and site-specific glycans are differentially expressed between cases and controls. This report represents the first serum glycan and glycopeptide biomarkers of Philippine lung cancer patients, further demonstrating the utility of mass spectrometry-based glycomic and glycoproteomic methods.

Lung cancer is the leading cause of cancer death and non-small cell lung carcinoma (NSCLC) accounting for majority of lung cancers. Thus, it is important to find potential biomarkers, such as glycans and glycoproteins, which can be used as diagnostic tools against NSCLC. Here, the N-glycome, proteome, and N-glycosylation distribution maps of tumor and peritumoral tissues of Filipino lung cancer patients (n = 5) were characterized. We present several case studies with varying stages of cancer development (I-III), mutation status (EGFR, ALK), and biomarker expression based on a three-gene panel (CD133, KRT19, and MUC1). Although the profiles of each patient were unique, specific trends arose that correlated with the role of aberrant glycosylation in cancer progression. Specifically, we observed a general increase in the relative abundance of high-mannose and sialofucosylated N-glycans in tumor samples. Analysis of the glycan distribution per glycosite revealed that these sialofucosylated N-glycans were specifically attached to glycoproteins involved in key cellular processes, including metabolism, cell adhesion, and regulatory pathways. Protein expression profiles showed significant enrichment of dysregulated proteins involved in metabolism, adhesion, cell-ECM interactions, and N-linked glycosylation, supporting the protein glycosylation results. The present case series study provides the first demonstration of a multi-platform mass-spectrometric analysis specifically for Filipino lung cancer patients.

Annona muricata L. (Guyabano) leaves are reported to exhibit anticancer activity against cancer cells. In this study, the ethyl acetate extract from guyabano leaves was purified through column chromatography, and the cytotoxic effects of the semi-purified fractions were evaluated against A549 lung cancer cells using in vitro MTS cytotoxicity and scratch/wound healing assays. Fractions F15-16C and F15-16D exhibited the highest anticancer activity in the MTS assay, with % cytotoxicity values of 99.6% and 99.4%, respectively. The bioactivity of the fractions was also consistent with the results of the scratch/wound healing assay. Moreover, untargeted metabolomics was employed on the semi-purified fractions to determine the putative compounds responsible for the bioactivity. The active fractions were processed using LC-MS/MS analysis with the integration of the following metabolomic tools: MS-DIAL (for data processing), MetaboAnalyst (for data analysis), GNPS (for metabolite annotation), and Cytoscape (for network visualization). Results revealed that the putative compounds with a significant difference between active and inactive fractions in PCA and OPLS-DA models were pheophorbide A and diphenylcyclopropenone.