ArticleCancer prevention research (Philadelphia, Pa.)2015
Plasma MicroRNAs as Novel Biomarkers for Patients with Intraductal Papillary Mucinous Neoplasms of the Pancreas.
Article in Cancer prevention research (Philadelphia, Pa.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 55 citations in OpenAlex.
- Bioinformatic Analysis and Integration of Transcriptome and Proteome Results Identify Key Coding and Noncoding Genes Predicting Malignancy in Intraductal Papillary Mucinous Neoplasms of the Pancreas.BioMed research international · 2021Pooled it
- Can we better predict the biologic behavior of incidental IPMN? A comprehensive analysis of molecular diagnostics and biomarkers in intraductal papillary mucinous neoplasms of the pancreas.Langenbeck's archives of surgery · 2018Pooled it
- Systematic Review and Meta-Analysis of Diagnostic Accuracy of miRNAs in Patients with Pancreatic Cancer.Disease markers · 2018Pooled it
- Circulating Leptin and Branched Chain Amino Acids-Correlation with Intraductal Papillary Mucinous Neoplasm Dysplastic Grade.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2019Trial
- Article
- Blood-Based microRNA Biomarker Signature of Early-Stage Pancreatic Ductal Adenocarcinoma With Lead-Time Trajectory in Prediagnostic Samples.Gastro hep advances · 2024Article
- Blood-Based Diagnosis and Risk Stratification of Patients with Pancreatic Intraductal Papillary Mucinous Neoplasm (IPMN).Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Article
- A pilot study to evaluate tissue- and plasma-based DNA driver mutations in a cohort of patients with pancreatic intraductal papillary mucinous neoplasms.G3 (Bethesda, Md.) · 2023Article
- Clinical and Molecular Attributes and Evaluation of Pancreatic Cystic Neoplasm.Biochimica et biophysica acta. Reviews on cancer · 2023Review
- Review
- A pilot study to troubleshoot quality control metrics when assessing circulating miRNA expression data reproducibility across study sites.Cancer biomarkers : section A of Disease markers · 2022Article
- Exosomal microRNA in Pancreatic Cancer Diagnosis, Prognosis, and Treatment: From Bench to Bedside.Cancers · 2021Review
- Micro-RNA Analysis of Pancreatic Cyst Fluid for Diagnosing Malignant Transformation of Intraductal Papillary Mucinous Neoplasm by Comparing Intraductal Papillary Mucinous Adenoma and Carcinoma.Journal of clinical medicine · 2021Article
- Article
- Comparison of Radiomic Features in a Diverse Cohort of Patients With Pancreatic Ductal Adenocarcinomas.Frontiers in oncology · 2021Article
- Exosomal miRNA signatures of pancreatic lesions.BMC gastroenterology · 2020Article
- Molecular Diagnosis of Cystic Neoplasms of the Pancreas: a Review.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2020Review
- Cancer Informatics for Cancer Centers (CI4CC): Building a Community Focused on Sharing Ideas and Best Practices to Improve Cancer Care and Patient Outcomes.JCO clinical cancer informatics · 2020Article
- Elevating pancreatic cystic lesion stratification: Current and future pancreatic cancer biomarker(s).Biochimica et biophysica acta. Reviews on cancer · 2020Review
- Cell-free microRNAs as Non-invasive Diagnostic and Prognostic Bio- markers in Pancreatic Cancer.Current genomics · 2019Review
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal cancers worldwide, partly because methods are lacking to detect disease at an early, operable stage. Noninvasive PDAC precursors called intraductal papillary mucinous neoplasms (IPMN) exist, and strategies are needed to aid in their proper diagnosis and management. Data support the importance of miRNAs in the progression of IPMNs to malignancy, and we hypothesized that miRNAs may be shed from IPMN tissues and detected in blood. Our primary goals were to measure the abundance of miRNAs in archived preoperative plasma from individuals with pathologically confirmed IPMNs and healthy controls and discover plasma miRNAs that distinguish between IPMN patients and controls and between "malignant" and "benign" IPMNs. Using novel nCounter technology to evaluate 800 miRNAs, we showed that a 30-miRNA signature distinguished 42 IPMN cases from 24 controls [area underneath the curve (AUC) = 74.4; 95% confidence interval (CI), 62.3-86.5, P = 0.002]. The signature contained novel miRNAs and miRNAs previously implicated in pancreatic carcinogenesis that had 2- to 4-fold higher expression in cases than controls. We also generated a 5-miRNA signature that discriminated between 21 malignant (high-grade dysplasia and invasive carcinoma) and 21 benign (low- and moderate-grade dysplasia) IPMNs (AUC = 73.2; 95% CI, 57.6-73.2, P = 0.005), and showed that paired plasma and tissue samples from patients with IPMNs can have distinct miRNA expression profiles. This study suggests feasibility of using new cost-effective technology to develop a miRNA-based blood test to aid in the preoperative identification of malignant IPMNs that warrant resection while sparing individuals with benign IPMNs the morbidity associated with overtreatment.
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Registered trials
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.