ArticleJournal of the National Cancer Institute2017
A Plasma Biomarker Panel to Identify Surgically Resectable Early-Stage Pancreatic Cancer.
Article in Journal of the National Cancer Institute, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed, 71 citations in OpenAlex.
- Pancreatic Cancer Detection Consortium Biomarker Bakeoff: A Phase II Blinded Biomarker Validation and Panel Discovery Study.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Proteomic meta-analysis unveils new frontiers for biomarkers research in pancreatic carcinoma.Oncogenesis · 2025Review
- Blood-based biomarkers in pancreatic ductal adenocarcinoma: developments over the last decade and what holds for the future- a review.Frontiers in oncology · 2025Review
- Host and bacterial urine proteomics might predict treatment outcomes for immunotherapy in advanced non-small cell lung cancer patients.Frontiers in immunology · 2025Article
- The Past, Present, and Future of Biomarkers for the Early Diagnosis of Pancreatic Cancer.Biomedicines · 2024Review
- Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma.Genes & diseases · 2024Review
- Multibiomarker panels in liquid biopsy for early detection of pancreatic cancer - a comprehensive review.Journal of experimental & clinical cancer research : CR · 2024Review
- Extracellular Vesicular Analysis of Glypican 1 mRNA and Protein for Pancreatic Cancer Diagnosis and Prognosis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- A Circulating Panel of circRNA Biomarkers for the Noninvasive and Early Detection of Pancreatic Ductal Adenocarcinoma.Gastroenterology · 2024Article
- A novel autoantibody signatures for enhanced clinical diagnosis of pancreatic ductal adenocarcinoma.Cancer cell international · 2023Article
- Blood-based Migration Signature Biomarker Panel Discriminates Early Stage New Onset Diabetes related Pancreatic Ductal Adenocarcinoma from Type 2 Diabetes.Clinica chimica acta; international journal of clinical chemistry · 2023Article
- Urine biomarkers enable pancreatic cancer detection up to 2 years before diagnosis.International journal of cancer · 2023Article
- TFPI inhibits breast cancer progression by suppressing ERK/p38 MAPK signaling pathway.Genes & genomics · 2022Article
- Article
- The Impact of Biomarkers in Pancreatic Ductal Adenocarcinoma on Diagnosis, Surveillance and Therapy.Cancers · 2022Review
- Early screening and diagnosis strategies of pancreatic cancer: a comprehensive review.Cancer communications (London, England) · 2021Review
- Biomarkers in the diagnosis of pancreatic cancer: Are we closer to finding the golden ticket?World journal of gastroenterology · 2021Review
- Extracellular Matrices and Cancer-Associated Fibroblasts: Targets for Cancer Diagnosis and Therapy?Cancers · 2021Review
- Plasma miRNA Biomarkers in Limited Volume Samples for Detection of Early-stage Pancreatic Cancer.Cancer prevention research (Philadelphia, Pa.) · 2021Observational
- Non-Invasive Biomarkers for Earlier Detection of Pancreatic Cancer-A Comprehensive Review.Cancers · 2021Review
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14 authors at 7 institutions in 1 country.
Funding
Abstract
Background: Blood-based biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) are urgently needed. Current biomarkers lack high sensitivity and specificity for population screening. The gold-standard biomarker, CA 19-9, also fails to demonstrate the predictive value necessary for early detection. Methods: To validate a functional genomics-based plasma migration signature biomarker panel, plasma tissue factor pathway inhibitor (TFPI), tenascin C (TNC-FN III-C), and CA 19-9 levels were measured by enzyme-linked immunosorbent assays in three early-stage PDAC plasma cohorts, including two independent blinded validation cohorts containing a total of 43 stage I, 163 stage II, 86 chronic pancreatitis, 31 acute biliary obstruction, and 108 controls. Logistic regression models developed classification rules combining TFPI and/or TNC-FN III-C with CA 19-9 for patient cases and control subjects, with or without adjustment for age and diabetes status. Model classification performance was evaluated and analyses repeated among subpopulations without diabetes and pancreatitis history. Two-sided P values were calculated using bootstrap method. Results: The TFPI/TNC-FN III-C/CA 19-9 panel improved CA 19-9 performance in all early-stage cohorts, including discriminating stage IA/IB/IIA, stage IIB, and all early-stage cancer from healthy controls. Statistical significance was reached for a number of subcohorts, including for all early-stage cancer vs healthy controls (cohort 1 AUC = 0.92, 95% CI = 0.86 to 0.96, P = .04; cohort 3 AUC = 0.83, 95% CI = 0.76 to 0.89, P = .045). Among subcohorts without diabetes and pancreatitis history, the panel approaches potential clinical utility for early detection to discriminate early-stage PDAC from healthy controls including an area under the curve (AUC) of 0.87 (95% CI = 0.77 to 0.95) for stage I/IIA, an AUC of 0.93 (95% CI = 0.87 to 0.98) for stage IIB, and a statistically significant AUC of 0.89 (95% CI = 0.82 to 0.95) for all early-stage cancer ( P = .03). Conclusions: TFPI/TNC-FN III-C migration signature adds statistically significantly to CA 19-9's predictive power to detect early-stage PDAC and may have clinical utility for early detection of surgically resectable PDAC, as well as for enhanced survival from this routinely lethal cancer.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.