ArticleJournal of the American College of Surgeons2020
Protein Signatures and Tissue Diagnosis of Pancreatic Cancer.
Article in Journal of the American College of Surgeons, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Proteomic Profiling of EUS-FNA Samples Differentiates Pancreatic Adenocarcinoma from Mass-Forming Chronic Pancreatitis.Biomedicines · 2025Article
- Pancreatic stellate cells and the interleukin family: Linking fibrosis and immunity to pancreatic ductal adenocarcinoma (Review).Molecular medicine reports · 2024Review
- Infiltration of CD3+ and CD8+ lymphocytes in association with inflammation and survival in pancreatic cancer.PloS one · 2024Article
- A protein-based machine learning approach to the identification of inflammatory subtypes in pancreatic ductal adenocarcinoma.Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2023Article
- Endoscopic Ultrasound-Guided Sampling for Personalized Pancreatic Cancer Treatment.Diagnostics (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundEndoscopic ultrasound-guided fine-needle aspiration fails to diagnose up to 25% of patients with pancreatic ductal adenocarcinoma (PDAC). Proteomics can help to overcome this clinical dilemma. We hypothesized that soluble protein signatures can differentiate PDAC from benign tissues. STUDY
designTissues were obtained from resected surgical specimens, lysed, and homogenates collected for analysis with a 41-protein multiplex assay. Analyte concentrations were normalized to total protein. Statistical analysis was performed to evaluate for differences in PDAC vs benign tissue.
resultsTissues were obtained from 159 patients, 82 patients with PDAC naïve to therapy and 77 with benign pancreatic pathology. Fourteen analytes had a receiver operating characteristic curve area of >0.75 for predicting PDAC vs benign tissue. A recursive partitioning model using only 2 analytes, interleukin 1 receptor antagonist and transforming growth factor-α, provided an accuracy, sensitivity, and specificity of 91.2%, 90.2%, and 92.2%, respectively. A penalized logistic regression model found 12 analytes that provide diagnostic value to a protein signature. The mean area under the receiver operating characteristic after 50 tenfold cross-validations was 0.951. Accuracy, sensitivity, and specificity of this model were 91.2%, 87.8%, and 94.8%, respectively. Applying the scenario of 80% disease prevalence in patients undergoing endoscopic ultrasound with fine-needle aspiration for a pancreatic head mass, positive predictive value is 98.5% (95% CI 93.0% to 99.7%) and negative predictive value is 66.0% (95% CI 54.9% to 75.6%).
conclusionsProtein signatures from pancreatic specimens can differentiate PDAC from benign tissue. Additional work to validate these findings in a unique sample set is warranted.
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