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. 2024 Mar 15;16(3):659-669.
doi: 10.4251/wjgo.v16.i3.659.

N-glycan biosignatures as a potential diagnostic biomarker for early-stage pancreatic cancer

Affiliations

N-glycan biosignatures as a potential diagnostic biomarker for early-stage pancreatic cancer

Yan-Rong Wen et al. World J Gastrointest Oncol. .

Abstract

Background: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of less than 10%, owing to its late-stage diagnosis. Early detection of pancreatic cancer (PC) can significantly increase survival rates.

Aim: To identify the serum biomarker signatures associated with early-stage PDAC by serum N-glycan analysis.

Methods: An extensive patient cohort was used to determine a biomarker signature, including patients with PDAC that was well-defined at an early stage (stages I and II). The biomarker signature was derived from a case-control study using a case-cohort design consisting of 29 patients with stage I, 22 with stage II, 4 with stage III, 16 with stage IV PDAC, and 88 controls. We used multiparametric analysis to identify early-stage PDAC N-glycan signatures and developed an N-glycan signature-based diagnosis model called the "Glyco-model".

Results: The biomarker signature was created to discriminate samples derived from patients with PC from those of controls, with a receiver operating characteristic area under the curve of 0.86. In addition, the biomarker signature combined with cancer antigen 19-9 could discriminate patients with PDAC from controls, with a receiver operating characteristic area under the curve of 0.919. Glyco-model demonstrated favorable diagnostic performance in all stages of PC. The diagnostic sensitivity for stage I PDAC was 89.66%.

Conclusion: In a prospective validation study, this serum biomarker signature may offer a viable method for detecting early-stage PDAC.

Keywords: Biomarkers; Glycomics; N-glycans; Pancreatic cancer; Predictive modeling.

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Conflict of interest statement

Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.

Figures

Figure 1
Figure 1
Overview of study design and patient cohort. PDAC: Pancreatic ductal adenocarcinoma.
Figure 2
Figure 2
N-glycome profile from desialylated serum. A: Typical desialylated N-glycan profiles from the total serum protein in patients with pancreatic ductal adenocarcinoma (PDAC), patients without PDAC, and healthy participants; B: Structure of nine N-glycan peaks (GPs). GP1 indicates an agalacto core α-1,6 fucosylated biantennary glycan (NGA2F), GP2 indicates an agalacto core α-1,6 fucosylated bisecting bian tennary glycan (NGA2FB), GP3 and GP4 indicate a single agalacto core α-1,6 fucosylated biantennary glycan (NG1A2F), GP5 indicates a bigalacto biantennary glycan (NA2), GP6 indicates a bigalacto core α-1,6 fucosylated biantennary glycan (NA2F), GP7 indicates a bigalacto core α-1,6 fucosylated bisecting biantennary glycan (NA2FB), GP8 indicates a triantennary glycan (NA3), and GP9 indicates a branching α-1,3 fucosylated triantennary glycan (NA3Fb); C: N-glycan analysis in the three groups of patients. aP < 0.05, bP < 0.01. GPs: Glycan peaks; PDAC: Pancreatic ductal adenocarcinoma.
Figure 3
Figure 3
Verification of N-glycan peaks for distinguishing malignant pancreatic cancer (pancreatic ductal adenocarcinoma) from non-pancreatic ductal adenocarcinoma cases. A: N-glycan analysis in pancreatic ductal adenocarcinoma (PDAC) and non-PDAC (intraductal papillary mucinous neoplasm, mucinous cyst neoplasm, pancreatic neuroendocrine tumor, serous cyst adenoma, solid pseudopapillary neoplasm) groups; B: Tumor markers analysis in PDAC and non-PDAC groups. aP < 0.05, bP < 0.01. GPs: Glycan peaks; PDAC: Pancreatic ductal adenocarcinoma; SPN: Solid pseudopapillary neoplasm; PNET: Pancreatic neuroendocrine tumor; SCN: Serous cyst adenoma; IPMN: Intraductal papillary mucinous neoplasm; MCN: Mucinous cyst neoplasm; AFP: Alpha fetoprotein; CEA: Carcinoembryonic antigen; CA19-9: Cancer antigen 19-9.
Figure 4
Figure 4
Comparative analysis of early-stage and advanced pancreatic ductal adenocarcinoma. A: Serum glycan peak (GP)2 and GP7 levels differ significantly between early (stage I and II) and advanced (stage III and IV) pancreatic ductal adenocarcinoma; B: Serum cancer antigen (CA)19-9 and CA242 levels differ significantly between early (stage I and II) and advanced (stage III and IV) pancreatic ductal adenocarcinoma. aP < 0.05, bP < 0.01. GPs: Glycan peaks; CA19-9: Cancer antigen 19-9.
Figure 5
Figure 5
Glyco-model for detecting patients with pancreatic ductal adenocarcinoma. A: Diagnostic model for detecting patients with pancreatic ductal adenocarcinoma (PDAC) using the 10-fold cross-validation diagnostic model; B: The diagnostic values for Glyco-model to distinguish patients with PDAC from those of non-PDAC. AUC: Area under the curve.

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References

    1. Ying H, Dey P, Yao W, Kimmelman AC, Draetta GF, Maitra A, DePinho RA. Genetics and biology of pancreatic ductal adenocarcinoma. Genes Dev. 2016;30:355–385. - PMC - PubMed
    1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022;72:7–33. - PubMed
    1. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73:17–48. - PubMed
    1. Walter FM, Mills K, Mendonça SC, Abel GA, Basu B, Carroll N, Ballard S, Lancaster J, Hamilton W, Rubin GP, Emery JD. Symptoms and patient factors associated with diagnostic intervals for pancreatic cancer (SYMPTOM pancreatic study): a prospective cohort study. Lancet Gastroenterol Hepatol. 2016;1:298–306. - PMC - PubMed
    1. Huang B, Huang H, Zhang S, Zhang D, Shi Q, Liu J, Guo J. Artificial intelligence in pancreatic cancer. Theranostics. 2022;12:6931–6954. - PMC - PubMed