Longitudinal changes of serum protein N-Glycan levels for earlier detection of pancreatic cancer in high-risk individuals

Glycoproteomics of Gastrointestinal Cancers and Its Use in Clinical Diagnostics

Cancer is a leading cause of death worldwide, resulting in substantial economic costs. Because cancer is a complex, heterogeneous group of diseases affecting a variety of cells, its detection may sometimes be difficult. Herein we review a large group of the gastrointestinal cancers (oral, esophageal, stomach, pancreatic, liver, and bowel cancers) and the possibility of using glycans conjugated to protein backbones for less-invasive diagnoses than the commonly used endoscopic approaches. The reality of bacterial N-glycosylation and the effect of epithelial mucosa on gut microbiota are discussed. Current advantages, barriers, and advantages in the prospective use of selected glycomic approaches in clinical practice are also detailed.

The exposome and pancreatic cancer, lifestyle and environmental risk factors for PDAC

Pancreatic cancer (PC), particularly pancreatic ductal adenocarcinoma (PDAC), is a significant global health issue with high mortality rates. PDAC, though only 3 % of cancer diagnoses, causes 7 % of cancer deaths due to its severity and asymptomatic early stages. Risk factors include lifestyle choices, environmental exposures, and genetic predispositions. Conditions like new-onset type 2 diabetes and chronic pancreatitis also contribute significantly. Modifiable risk factors include smoking, alcohol consumption, non-alcoholic fatty pancreatic disease (NAFPD), and obesity. Smoking and heavy alcohol consumption increase PC risk, while NAFPD and obesity, particularly central adiposity, contribute through chronic inflammation and insulin resistance. Refined sugar and sugar-sweetened beverages (SSBs) are also linked to increased PC risk, especially among younger individuals. Hormonal treatments and medications like statins, aspirin, and metformin have mixed results on PC risk, with some showing protective effects. The gut microbiome influences PC through the gut-pancreas axis, with disruptions leading to inflammation and carcinogenesis. Exposure to toxic substances, including heavy metals and chemicals, is associated with increased PC risk. Glycome changes, such as abnormal glycosylation patterns, are significant in PDAC development and offer potential for early diagnosis. Interactions between environmental and genetic factors are crucial in PDAC susceptibility. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) linked to PDAC, but gene-environment interactions remain largely unexplored. Future research should focus on polygenic risk scores (PRS) and large-scale studies to better understand these interactions and their impact on PDAC risk.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Pancreatic cancer surveillance: Risk stratification of individuals with a germline CDKN2A pathogenic variant

BACKGROUND

Individuals carrying a germline CDKN2A pathogenic variant (PV) are at a high risk of developing pancreatic ductal adenocarcinoma. Risk stratification could allow tailored surveillance.

OBJECTIVE

To develop a Fine-Gray prediction model for the risk of PDAC in carriers of a CDKN2A PV.

METHODS

Data from two large Dutch pancreatic cancer surveillance programs were used. A limited set of predictor variables were selected bsased on previous literature and the clinical expertise of the study group.

RESULTS

A total of 506 CDKN2A PV carriers were included, among whom we showed a substantial lifetime risk of PDAC (23%). The model identifies having a first-degree relative with PDAC (B = 0.7256) and a history of smoking (B = 0.4776) as significant risk factors. However, the model shows limited discrimination (c-statistic 0.64) and calibration.

CONCLUSION

Our study highlights the high lifetime risk of PDAC in carriers of a CDKN2A PV. While identifying significant risk factors such as family history of PDAC and smoking, our prediction model shows limited precision, highlighting the need for additional factors such as biomarkers to improve its clinical utility for tailored surveillance of high-risk individuals.

Pancreatic cancer screening is effective in individuals at risk with predisposing germline gene variants, but not in gene variant-negative familial pancreatic cancer families

OBJECTIVE

To evaluate the diagnostic yield of pancreatic cancer screening in individuals at risk (IAR) from familial pancreatic cancer (FPC) families with respect to the presence or absence of pathogenic germline variants predisposing to pancreatic adenocarcinoma (PDAC).

DESIGN

In a 20 years period, IAR from FPC families were enrolled in a prospective screening program of the national case collection for FPC of Germany, including magnet resonance imaging (MRI) and endoscopic ultrasound (EUS). The diagnostic yield was analyzed regarding significant pancreatic lesions such as PDAC, high-grade pancreatic-intraepithelial-neoplasia (PanIN3) and intraductal-papillary-mucinous-neoplasia (IPMN) with high-grade dysplasia. Screening results were compared between carriers of pathogenic variants and variant-negative IAR.

RESULTS

337 IAR, including 74 (22%) variant-carriers and 263 IAR of variant-negative FPC families (mean age 49; standard deviation [SD] + 8.9) were followed 64 (SD + 55) months. IAR underwent 5.1 (SD + 3.9) screening visits with 1733 MRI (5.1,SD + 3.9 per IAR) and 728 EUS (2.2,SD + 1.7 per IAR). In 12 (4%) cases, significant pancreatic lesions were detected, including 4 PDAC, 3 PanIN3 and 5 high-grade IPMN. Three of 4 IAR with PDAC died after a mean of 27 months postoperatively, and one IAR is alive without evidence of disease after 31 months. The diagnostic yield for significant lesions was 13.5% (10/74) for variant carriers compared to 0.8% (2/263) for IAR of variant-negative FPC families (p < 0.001). Logistic regression analysis revealed that a negative variant status was almost always accompanied by the absence of a significant lesion over time with a negative predictive value of 99.2% (95% CI 97.3%-99.9%).

CONCLUSION

The diagnostic yield seems to justify PDAC screening in IAR of FPC-families with pathogenic germline variants in PDAC predisposing genes, not in IAR of variant-negative families.

Aspects and outcomes of surveillance for individuals at high-risk of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related deaths and is associated with a poor prognosis. The majority of these cancers are detected at a late stage, contributing to the bad prognosis. This underscores the need for novel, enhanced early detection strategies to improve the outcomes. While population-based screening is not recommended due to the relatively low incidence of PDAC, surveillance is recommended for individuals at high risk for PDAC due to their increased incidence of the disease. However, the outcomes of pancreatic cancer surveillance in high-risk individuals are not sorted out yet. In this review, we will address the identification of individuals at high risk for PDAC, discuss the objectives and targets of surveillance, outline how surveillance programs are organized, summarize the outcomes of high-risk individuals undergoing pancreatic cancer surveillance, and conclude with a future perspective on pancreatic cancer surveillance and novel developments.

The Human Blood N-Glycome: Unraveling Disease Glycosylation Patterns

Most of the proteins in the circulation are N-glycosylated, shaping together the total blood N-glycome (TBNG). Glycosylation is known to affect protein function, stability, and clearance. The TBNG is influenced by genetic, environmental, and metabolic factors, in part epigenetically imprinted, and responds to a variety of bioactive signals including cytokines and hormones. Accordingly, physiological and pathological events are reflected in distinct TBNG signatures. Here, we assess the specificity of the emerging disease-associated TBNG signatures with respect to a number of key glycosylation motifs including antennarity, linkage-specific sialylation, fucosylation, as well as expression of complex, hybrid-type and oligomannosidic N-glycans, and show perplexing complexity of the glycomic dimension of the studied diseases. Perspectives are given regarding the protein- and site-specific analysis of N-glycosylation, and the dissection of underlying regulatory layers and functional roles of blood protein N-glycosylation.

The role of clinical glyco(proteo)mics in precision medicine

Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity and half-life. The increasingly mature toolbox with glycomic- and glycoproteomic strategies is applied for the development of biopharmaceuticals and discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end it is noted that the identification of biomarkers has received more attention than corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes but developments to accurately quantify these have so far been limited. In this perspective a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address quantification of a multimarker panel will be discussed.