Prediction of gastric cancer by machine learning integrated with mass spectrometry-based N-glycomics.

Early and accurate diagnosis of gastric cancer is vital for effective and targeted treatment. It is known that glycosylation profiles differ in the cancer tissue development process. This study aimed to profile the N-glycans in gastric cancer tissues to predict gastric cancer using machine learning algorithms. The (glyco-) proteins of formalin-fixed parafilm embedded (FFPE) gastric cancer and adjacent control tissues were extracted by chloroform/methanol extraction after the conventional deparaffinization step. The N-glycans were released and labeled with a 2-amino benzoic (2-AA) tag. The MALDI-MS analysis of the 2-AA labeled N-glycans was performed in negative ionization mode, and fifty-nine N-glycan structures were determined. The relative and analyte areas of the detected N-glycans were extracted from the obtained data. Statistical analyses identified significant expression levels of 14 different N-glycans in gastric cancer tissues. The data were separated based on the physical characteristics of N-glycans and used to test in machine-learning models. It was determined that the multilayer perceptron (MLP) was the most appropriate model with the highest sensitivity, specificity, accuracy, Matthews correlation coefficient, and f1 scores for each dataset. The highest accuracy score (96.0 ± 1.3) was obtained from the whole N-glycans relative area dataset, and the AUC value was determined as 0.98. It was concluded that gastric cancer tissues could be distinguished from adjacent control tissues with high accuracy using mass spectrometry-based N-glycomic data.

Stability Evaluation of the Biosimilar Monoclonal Antibody Using Analytical Techniques.

Objectives: Determination of the drug substance (DS) and drug product (DP) stability is especially important for biosimilar monoclonal antibodies since it can affect the quality, efficacy, and safety of the drugs. The main objective of this study was to determine the stability of the biosimilar candidate (TUR01) using state-of-the-art (current) analytical techniques. Materials and Methods: Analytical techniques used in this study were isoelectric focusing on capillary electrophoresis, capillary electrophoresis-sodium dodecyl sulfate, size exclusion chromatography-ultra-high performance liquid chromatography, binding affinity, and physicochemical and microbiological tests. DS was kept in polyethylene terephthalate copolyester, glycol modified (PETG) bottles at ≤-65.0°C and 5.0 ± 3.0°C for 18 months, where the pre-filled syringe stability study was conducted at 5.0 ± 3.0°C for 24 months and 25.0 ± 2.0°C/60% ± 5 relative humidity (RH) for 6 months. The accelerated condition for DS was accepted as 5.0 ± 3.0°C, while it was 25.0 ± 2.0°C for the DP. Results: The results indicated that TUR01 DS was stable when it was stored under long-term storage conditions at ≤-65°C and at 5 ± 3°C at least 18 months. Also, TUR01 DP was stable at 5 ± 3°C for 24 months and at 25 ± 2°C with 60.5% RH for 2 months without any significant changes. Conclusion: State-of-the-art analytical techniques proved to be invaluable tools for evaluate the stability of the TUR01 DS and drug product.

Utilizing linkage-specific ethyl-esterification approach to perform in-depth analysis of sialylated N-glycans present on milk whey glycoproteins.

Glycosylation of milk whey proteins, specifically the presence of sialic acid-containing glycan residues, causes functional changes in these proteins. This study aimed to analyze the N-glycome of milk whey glycoproteins from various milk sources using a linkage-specific ethyl esterification approach with MALDI-MS (matrix-assisted laser desorption/ionization-mass spectrometry). The results showed that the N-glycan profiles of bovine and buffalo whey mostly overlapped. Acetylated N-glycans were only detected in donkey milk whey at a rate of 16.06%. a2,6-linked N-Acetylneuraminic acid (a2,6-linked NeuAc, E) was found to be the predominant sialylation type in human milk whey (65.16%). The amount of a2,6-linked NeuAc in bovine, buffalo, goat, and donkey whey glycoproteomes was 42.33%, 44.16%, 39.00%, and 34.86%, respectively. The relative abundances of a2,6-linked N-Glycolylneuraminic acid (a2,6-linked NeuGc, Ge) in bovine, buffalo, goat, and donkey whey were 7.52%, 5.41%, 28.24%, and 17.31%, respectively. Goat whey exhibited the highest amount of a2,3-linked N-Glycolylneuraminic acid (a2,3-linked NeuGc, Gl, 8.62%), while bovine and donkey whey contained only 2.14% and 1.11%, respectively.

Comparative systeomics to elucidate physiological differences between CHO and SP2/0 cell lines.

Omics-based tools were coupled with bioinformatics for a systeomics analysis of two biopharma cell types: Chinese hamster ovary (M-CHO and CHO-K1) and SP2/0. Exponential and stationary phase samples revealed more than 10,000 transcripts and 6000 proteins across these two manufacturing cell lines. A statistical comparison of transcriptomics and proteomics data identified downregulated genes involved in protein folding, protein synthesis and protein metabolism, including PPIA-cyclophilin A, HSPD1, and EIF3K, in M-CHO compared to SP2/0 while cell cycle and actin cytoskeleton genes were reduced in SP2/0. KEGG pathway comparisons revealed glycerolipids, glycosphingolipids, ABC transporters, calcium signaling, cell adhesion, and secretion pathways depleted in M-CHO while retinol metabolism was upregulated. KEGG and IPA also indicated apoptosis, RNA degradation, and proteosomes enriched in CHO stationary phase. Alternatively, gene ontology analysis revealed an underrepresentation in ion and potassium channel activities, membrane proteins, and secretory granules including Stxbpt2, Syt1, Syt9, and Cma1 proteins in M-CHO. Additional enrichment strategies involving ultracentrifugation, biotinylation, and hydrazide chemistry identified over 4000 potential CHO membrane and secretory proteins, yet many secretory and membrane proteins were still depleted. This systeomics pipeline has revealed bottlenecks and potential opportunities for cell line engineering in CHO and SP2/0 to improve their production capabilities.