Spectral library-based glycopeptide analysis-detection of circulating galectin-3 binding protein in pancreatic cancer

Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape

The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.

Galectin-3's Complex Interactions in Pancreatic Ductal Adenocarcinoma: From Cellular Signaling to Therapeutic Potential

Galectin-3 (Gal-3) plays a multifaceted role in the development, progression, and prognosis of pancreatic ductal adenocarcinoma (PDAC). This review offers a comprehensive examination of its expression in PDAC, its interaction with various immune cells, signaling pathways, effects on apoptosis, and therapeutic resistance. Additionally, the prognostic significance of serum levels of Gal-3 is discussed, providing insights into its potential utilization as a biomarker. Critical analysis is also extended to the inhibitors of Gal-3 and their potential therapeutic applications in PDAC, offering new avenues for targeted treatments. The intricate nature of Gal-3's role in PDAC reveals a complex landscape that demands a nuanced understanding for potential therapeutic interventions and monitoring.

LC-MS/MS: A sensitive and selective analytical technique to detect COVID-19 protein biomarkers in the early disease stage

INTRODUCTION

The COVID-19 outbreak has put enormous pressure on the scientific community to detect infection rapidly, identify the status of disease severity, and provide an immediate vaccine/drug for the treatment. Relying on immunoassay and a real-time reverse transcription polymerase chain reaction (rRT-PCR) led to many false-negative and false-positive reports. Therefore, detecting biomarkers is an alternative and reliable approach for determining the infection, its severity, and disease progression. Recent advances in liquid chromatography and mass spectrometry (LC-MS/MS) enable the protein biomarkers even at low concentrations, thus facilitating clinicians to monitor the treatment in hospitals.

AREAS COVERED

This review highlights the role of LC-MS/MS in identifying protein biomarkers and discusses the clinically significant protein biomarkers such as Serum amyloid A, Interleukin-6, C-Reactive Protein, Lactate dehydrogenase, D-dimer, cardiac troponin, ferritin, Alanine transaminase, Aspartate transaminase, gelsolin and galectin-3-binding protein in COVID-19, and their analysis by LC-MS/MS in the early stage.

EXPERT OPINION

Clinical doctors monitor significant biomarkers to understand, stratify, and treat patients according to disease severity. Knowledge of clinically significant COVID-19 protein biomarkers is critical not only for COVID-19 caused by the coronavirus but also to prepare us for future pandemics of other diseases in detecting by LC-MS/MS at the early stages.

The next "sweet" spot for pancreatic ductal adenocarcinoma: Glycoprotein for early detection

Pancreatic ductal adenocarcinoma (PDAC) is the most common neoplastic disease of the pancreas, accounting for more than 90% of all pancreatic malignancies. As a highly lethal malignancy, PDAC is the fourth leading cause of cancer-related deaths worldwide with a 5-year overall survival of less than 8%. The efficacy and outcome of PDAC treatment largely depend on the stage of disease at the time of diagnosis. Surgical resection followed by adjuvant chemotherapy remains the only possibly curative therapy, yet 80%-90% of PDAC patients present with nonresectable PDAC stages at the time of clinical presentation. Despite our advancing knowledge of PDAC, the prognosis remains strikingly poor, which is primarily due to the difficulty of diagnosing PDAC at the early stages. Recent advances in glycoproteomics and glycomics based on mass spectrometry have shown that aberrations in protein glycosylation plays a critical role in carcinogenesis, tumor progression, metastasis, chemoresistance, and immuno-response of PDAC and other types of cancers. A growing interest has thus been placed upon protein glycosylation as a potential early detection biomarker for PDAC. We herein take stock of the advancements in the early detection of PDAC that were carried out with mass spectrometry, with special focus on protein glycosylation.

Data-independent acquisition proteomics methods for analyzing post-translational modifications

Protein post-translational modifications (PTMs) increase the functional diversity of the cellular proteome. Accurate and high throughput identification and quantification of protein PTMs is a key task in proteomics research. Recent advancements in data-independent acquisition (DIA) mass spectrometry (MS) technology have achieved deep coverage and accurate quantification of proteins and PTMs. This review provides an overview of DIA data processing methods that cover three aspects of PTMs analysis, i.e., detection of PTMs, site localization, and characterization of complex modification moieties, such as glycosylation. In addition, a survey of deep learning methods that boost DIA-based PTMs analysis is presented, including in silico spectral library generation, as well as feature scoring and error rate control. The limitations and future directions of DIA methods for PTMs analysis are also discussed. Novel data analysis methods will take advantage of advanced MS instrumentation techniques to empower DIA MS for in-depth and accurate PTMs measurements. This article is protected by copyright. All rights reserved.

An Integrated Proteomic and Glycoproteomic Investigation Reveals Alterations in the N-Glycoproteomic Network Induced by 2-Deoxy-D-Glucose in Colorectal Cancer Cells

As a well-known glycolysis inhibitor for anticancer treatment, 2-Deoxy-D-glucose (2DG) inhibits the growth and survival of cancer cells by interfering with the ATP produced by the metabolism of D-glucose. In addition, 2DG inhibits protein glycosylation in vivo by competing with D-mannose, leading to endoplasmic reticulum (ER) stress and unfolded protein responses in cancer cells. However, the molecular details underlying the impact of 2DG on protein glycosylation remain largely elusive. With an integrated approach to glycoproteomics and proteomics, we characterized the 2DG-induced alterations in N-glycosylation, as well as the cascading impacts on the whole proteome using the HT29 colorectal cancer cell line as a model system. More than 1700 site-specific glycoforms, represented by unique intact glycopeptides (IGPs), were identified. The treatment of 2DG had a broad effect on the N-glycoproteome, especially the high-mannose types. The glycosite occupancy of the high-mannose N-glycans decreased the most compared with the sialic acid and fucose-containing N-glycans. Many of the proteins with down-regulated high-mannose were implicated in functional networks related to response to topologically incorrect protein, integrin-mediated signaling, lysosomal transport, protein hydroxylation, vacuole, and protein N-glycosylation. The treatment of 2DG also functionally disrupted the global cellular proteome, evidenced by significant up-regulation of the proteins implicated in protein folding, endoplasmic reticulum, mitochondrial function, cellular respiration, oxidative phosphorylation, and translational termination. Taken together, these findings reveal the complex changes in protein glycosylation and expression underlying the various effects of 2DG on cancer cells, and may provide insightful clues to inform therapeutic development targeting protein glycosylation.

Transforming growth factor-β challenge alters the N-, O-, and glycosphingolipid glycomes in PaTu-S pancreatic adenocarcinoma cells

Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognosis and high mortality. Transforming growth factor-β (TGF-β) plays a key role in PDAC tumor progression, which is often associated with aberrant glycosylation. However, how PDAC cells respond to TGF-β and the role of glycosylation therein is not well known. Here, we investigated the TGF-β-mediated response and glycosylation changes in the PaTu-8955S (PaTu-S) cell line deficient in SMA-related and MAD-related protein 4 (SMAD4), a signal transducer of the TGF-β signaling. PaTu-S cells responded to TGF-β by upregulating SMAD2 phosphorylation and target gene expression. We found that TGF-β induced expression of the mesenchymal marker N-cadherin but did not significantly affect epithelial marker E-cadherin expression. We also examined differences in N-glycans, O-glycans, and glycosphingolipid-linked glycans in PaTu-S cells upon TGF-β stimulation. TGF-β treatment primarily induced N-glycome aberrations involving elevated levels of branching, core fucosylation, and sialylation in PaTu-S cells, in agreement with TGF-β-induced changes in the expression of glycosylation-associated genes. In addition, we observed differences in O glycosylation and glycosphingolipid glycosylation profiles after TGF-β treatment, including lower levels of sialylated Tn antigen and neoexpression of globosides. Furthermore, the expression of transcription factor sex-determining region Y-related high-mobility group box 4 was upregulated upon TGF-β stimulation, and its depletion blocked TGF-β-induced N-glycomic changes. Thus, TGF-β-induced N-glycosylation changes can occur in a sex-determining region Y-related high-mobility group box 4–dependent and SMAD4-independent manner in the pancreatic PaTu-S cancer cell line. Our results open up avenues to study the relevance of glycosylation in TGF-β signaling in SMAD4-inactivated PDAC.

Role of galectin 3 binding protein in cancer progression: a potential novel therapeutic target

The lectin galactoside-binding soluble 3 binding protein (LGALS3BP) is a secreted, hyperglycosylated protein expressed by the majority of human cells. It was first identified as cancer and metastasis associated protein, while its role in innate immune response upon viral infection remains still to be clarified. Since its discovery dated in early 90 s, a large body of literature has been accumulating highlighting both a prognostic and functional role for LGALS3BP in cancer. Moreover, data from our group and other have strongly suggested that this protein is enriched in cancer-associated extracellular vesicles and may be considered a promising candidate for a targeted therapy in LGALS3BP positive cancers. Here, we extensively reviewed the literature relative to LGALS3BP role in cancer and its potential value as a therapeutic target.

Recent Advances in Mass Spectrometry-Based Glycomic and Glycoproteomic Studies of Pancreatic Diseases

Modification of proteins by glycans plays a crucial role in mediating biological functions in both healthy and diseased states. Mass spectrometry (MS) has emerged as the most powerful tool for glycomic and glycoproteomic analyses advancing knowledge of many diseases. Such diseases include those of the pancreas which affect millions of people each year. In this review, recent advances in pancreatic disease research facilitated by MS-based glycomic and glycoproteomic studies will be examined with a focus on diabetes and pancreatic cancer. The last decade, and especially the last five years, has witnessed developments in both discovering new glycan or glycoprotein biomarkers and analyzing the links between glycans and disease pathology through MS-based studies. The strength of MS lies in the specificity and sensitivity of liquid chromatography-electrospray ionization MS for measuring a wide range of biomolecules from limited sample amounts from many sample types, greatly enhancing and accelerating the biomarker discovery process. Furthermore, imaging MS of glycans enabled by matrix-assisted laser desorption/ionization has proven useful in complementing histology and immunohistochemistry to monitor pancreatic disease progression. Advances in biological understanding and analytical techniques, as well as challenges and future directions for the field, will be discussed.

Metaproteomics-An Advantageous Option in Studies of Host-Microbiota Interaction

Gut microbiome contributes to host health by maintaining homeostasis, increasing digestive efficiency, and facilitating the development of the immune system. Manipulating gut microbiota is being recognized as a therapeutic target to manage various chronic diseases. The therapeutic manipulation of the intestinal microbiome is achieved through diet modification, the administration of prebiotics, probiotics, or antibiotics, and more recently, fecal microbiome transplantation (FMT). In this opinion paper, we give a perspective on the current status of application of multi-omics technologies in the analysis of host-microbiota interactions. The aim of this paper was to highlight the strengths of metaproteomics, which integrates with and often relies on other approaches.

Clinical Perspective on Proteomic and Glycomic Biomarkers for Diagnosis, Prognosis, and Prediction of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is known as a highly aggressive malignant disease. Prognosis for patients is notoriously poor, despite improvements in surgical techniques and new (neo)adjuvant chemotherapy regimens. Early detection of PDAC may increase the overall survival. It is furthermore foreseen that precision medicine will provide improved prognostic stratification and prediction of therapeutic response. In this review, omics-based discovery efforts are presented that aim for novel diagnostic and prognostic biomarkers of PDAC. For this purpose, we systematically evaluated the literature published between 1999 and 2020 with a focus on protein- and protein-glycosylation biomarkers in pancreatic cancer patients. Besides genomic and transcriptomic approaches, mass spectrometry (MS)-based proteomics and glycomics of blood- and tissue-derived samples from PDAC patients have yielded new candidates with biomarker potential. However, for reasons discussed in this review, the validation and clinical translation of these candidate markers has not been successful. Consequently, there has been a change of mindset from initial efforts to identify new unimarkers into the current hypothesis that a combination of biomarkers better suits a diagnostic or prognostic panel. With continuing development of current research methods and available techniques combined with careful study designs, new biomarkers could contribute to improved detection, prognosis, and prediction of pancreatic cancer.

90K predicts the prognosis of glioma patients and enhances tumor lysate-pulsed DC vaccine for immunotherapy of GBM in vitro

OBJECTIVES

This study aimed to investigate the relationship between 90K expression with glioma malignancy and prognosis. Additionally, the enhancement effect of 90K in the Dendritic cell (DC) vaccine for Immunotherapy of glioblastoma (GBM) was evaluated in vitro.

METHODS

The expression of 90K protein in glioma tissues was detected by western blot. The relationship between the 90K expression and the tumor grade as well as the prognosis of patients was further analyzed by mining TCGA and CGGA database. The concentration of IL-12p70 and IL-10 was detected by ELISA. T lymphocyte proliferation and lethal effect of cytotoxic T cell (CTL) were detected by CCK-8.

RESULTS

The expression of 90K was significantly higher in glioma than normal tissue and increased with tumor grade (P< 0.05). Higher 90K expression was observed in IDH wildtype glioma than IDH mutant and predicted worse overall survival for glioma patients. The concentration of IL-12p70 and IFN-γ was the highest in the Apoptosis U251-90K-DC group, in which group the ability to kill U251 cells by CTL was also the strongest.

CONCLUSION

90K was a useful biomarker for glioma malignancy and patient prognosis. The appearance of 90K enhanced the effect of Apoptosis U251-DC vaccine for immunotherapy of GBM.

The Role of Data-Independent Acquisition for Glycoproteomics

Data-independent acquisition (DIA) is now an emerging method in bottom–up proteomics and capable of achieving deep proteome coverage and accurate label-free quantification. However, for post-translational modifications, such as glycosylation, DIA methodology is still in the early stage of development. The full characterization of glycoproteins requires site-specific glycan identification as well as subsequent quantification of glycan structures at each site. The tremendous complexity of glycosylation represents a significant analytical challenge in glycoproteomics. This review focuses on the development and perspectives of DIA methodology for N- and O-linked glycoproteomics and posits that DIA-based glycoproteomics could be a method of choice to address some of the challenging aspects of glycoproteomics. First, the current challenges in glycoproteomics and the basic principles of DIA are briefly introduced. DIA-based glycoproteomics is then summarized and described into four aspects based on the actual samples. Finally, we discussed the important challenges and future perspectives in the field. We believe that DIA can significantly facilitate glycoproteomic studies and contribute to the development of future advanced tools and approaches in the field of glycoproteomics.

•

Protein glycosylation and challenges in glycoproteomics.

•

Data-independent acquisition for deglycosylated and intact N-linked glycopeptides.

•

Unbiased screening of oxonium ions from all glycopeptide precursors.

•

Glyco–data-independent acquisition on mucin-type O-glycopeptides.

Proteome alterations in pancreatic ductal adenocarcinoma

Proteins are the essential functional biomolecules profoundly implicated in all aspects of pancreatic tumorigenesis and its progression. While common genomic factors, such as KRAS, TP53, SMAD4, and CDKN2A have been well recognized in association of pancreatic ductal adenocarcinoma (PDAC), our understanding of functional changes at the proteome level merits further investigation. Malignance associated proteome alterations can be attributed to the convoluted outcomes from genetic, epigenetic and environmental factors in initiating and progressing PDAC, and may reflect on changes in protein expressional level, structure, localization, as well as post-translational modifications (PTMs) status. The study of localized or systemic proteome alterations in PDAC, as well as its precursor lesions, such as pancreatic intraepithelial neoplasia (PanIN) and mucinous pancreatic cystic neoplasm, would provide unique perspectives in elucidating functional molecular events underlying PDAC. While efforts have been made, challenges still exist to comprehensively integrate much of the proteomic discovery to the perspectives gained from genomic studies in the context of biomarker discovery. Novel approaches and data from well-defined longitudinal clinical studies and experimental models are needed to facilitate the study of PDAC and precursor lesions for early detection and intervention.

Surfaceome profiling enables isolation of cancer-specific exosomal cargo in liquid biopsies from pancreatic cancer patients

Background

Detection of circulating tumor DNA can be limited due to their relative scarcity in circulation, particularly while patients are actively undergoing therapy. Exosomes provide a vehicle through which cancer-specific material can be enriched from the compendium of circulating non-neoplastic tissue-derived nucleic acids. We carried out a comprehensive profiling of the pancreatic ductal adenocarcinoma (PDAC) exosomal 'surfaceome' in order to identify surface proteins that will render liquid biopsies amenable to cancer-derived exosome enrichment for downstream molecular profiling.

Patients and methods

Surface exosomal proteins were profiled in 13 human PDAC and 2 non-neoplastic cell lines by liquid chromatography-mass spectrometry. A total of 173 prospectively collected blood samples from 103 PDAC patients underwent exosome isolation. Droplet digital PCR was used on 74 patients (136 total exosome samples) to determine baseline KRAS mutation call rates while patients were on therapy. PDAC-specific exosome capture was then carried out on additional 29 patients (37 samples) using an antibody cocktail directed against selected proteins, followed by droplet digital PCR analysis. Exosomal DNA in a PDAC patient resistant to therapy were profiled using a molecular barcoded, targeted sequencing panel to determine the utility of enriched nucleic acid material for comprehensive molecular analysis.

Results

Proteomic analysis of the exosome 'surfaceome' revealed multiple PDAC-specific biomarker candidates: CLDN4, EPCAM, CD151, LGALS3BP, HIST2H2BE, and HIST2H2BF. KRAS mutations in total exosomes were detected in 44.1% of patients undergoing active therapy compared with 73.0% following exosome capture using the selected biomarkers. Enrichment of exosomal cargo was amenable to molecular profiling, elucidating a putative mechanism of resistance to PARP inhibitor therapy in a patient harboring a BRCA2 mutation.

Conclusion

Exosomes provide unique opportunities in the context of liquid biopsies for enrichment of tumor-specific material in circulation. We present a comprehensive surfaceome characterization of PDAC exosomes which allows for capture and molecular profiling of tumor-derived DNA.

Metaproteomics Study of the Gut Microbiome

Proteomics is a widely used method for defining the protein composition of a complex sample. As this approach allows for identification and quantification of proteins across a broad dynamic range as well as detection of post-translational modifications, proteomics is an ideal platform to investigate the gut microbiome at a functional level. The gut microbiome is a dynamic environment which is crucial for overall health and fitness. Imbalances in the gut microbiome can influence nutrient absorption, pathogen resistance, inflammation, and various human diseases. Metaproteomic analysis of the gut microbiome is currently being performed on bacteria isolated from (1) fecal samples (2) colonic lavage, or (3) colon biopsies. Investigation of the gut microbiome has demonstrated that within the colon, there are distinct communities based on spatial location, and separable from the gut microbiomes isolated from stool. In addition to expanding our understanding of host-bacterial interactions for human health and disease, gut microbiome analysis is being utilized for biomarker development to discriminate normal individuals and diseased (i.e., inflammatory bowel disease or colon cancer) patients as well as to monitor disease activity and prognosis.