Glycomic, Glycoproteomic, and Proteomic Profiling of Philippine Lung Cancer and Peritumoral Tissues: Case Series Study of Patients Stages I-III.

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.

Multi-glycomic analysis of spheroid glycocalyx differentiates 2- and 3-dimensional cell models.

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.

Metabolomics based inferences to unravel phenolic compound diversity in cereals and its implications for human gut health.

Background: Whole grain cereals are a good source of nutrients. Several cutting-edge metabolomic platforms have been deployed to identify various phenolic compounds and enhance cereal bioactive bioavailability. A diet rich in cereal phenolics may modify the microbial composition, support gut homeostasis, and increase gut health, thereby lowering the risk of non-communicable illness. Scope and approach: In this work, we reviewed current metabolomic breakthroughs in cereal phenolic profiling and their effects on human health via gut microbiota modulation. We argue that the information presented in this paper will assist in the development of nutritionally superior cereal breeds and functional foods. Key findings and conclusion: Most cereal grains contain ferulic acid derivatives, caffeoyl glycerides, and feruloyl and coumaroyl esters. While there has been significant progress in discovering novel phenolic compounds in cereals, quantifying these molecules, and translating their therapeutic effects from animal model systems to humans remains a challenge. To this end, metabolomics, and other high-throughput-omics-based platforms must be integrated to further examine the structure and functionality of phenolic metabolites to breed nutritionally rich cereals as well as map their influence on human health benefits. Rare alleles must be introduced to improve bioactive content in cereal grains while maintaining yield. Following that, these exceptional varieties must be effectively processed to maximize phenolic bioavailability.

Biological Assay-Guided Fractionation and Mass Spectrometry-Based Metabolite Profiling of Annona muricata L. Cytotoxic Compounds against Lung Cancer A549 Cell Line.

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.