ArticleBritish journal of cancer2024
Early detection of pancreatic cancer by comprehensive serum miRNA sequencing with automated machine learning.
Article in British journal of cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Machine learning approaches for cancer prognosis and diagnosis via non-coding RNA: a comprehensive review.Briefings in bioinformatics · 2026Review
- Dynamics of the association between circulating levels of miRNA and pancreatic cancer risk through the years prior to pancreatic cancer diagnosis.International journal of cancer · 2026Article
- Pilot validation of a whole-blood mRNA expression-based diagnostic system for early-stage pancreatic ductal adenocarcinoma: a single-center case-control diagnostic accuracy study.Scientific reports · 2026Article
- Comparison of Comprehensive Serum miRNA Sequencing and Apolipoprotein A2 Isoforms for Early Detection of Pancreatic Cancer.Cancers · 2026Article
- Serum expression levels of HOTAIR and miR-646 in endometrial cancer.Oncology letters · 2026Article
- Detection and Classification of Pancreatic Cancer Nodules on CT Images using U-Net and Ensemble Models.Current medical imaging · 2026Article
- Decoding the microbial blueprint of pancreatic cancer.Frontiers in medicine · 2026Review
- Serum MicroRNA-196, -200 and -423 Improve Diagnostics and Differentiate Pancreatic Ductal Adenocarcinoma From Chronic Pancreatitis.Physiological research · 2025Article
- Serum-MiR-CanPred: deep learning framework for pan-cancer classification and miRNA-targeted drug discovery.RNA biology · 2025Article
- Unraveling the therapeutic landscape of miRNAs in pancreatic cancer.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Challenges of early detection of pancreatic cancer.The Journal of clinical investigation · 2025Review
- Harnessing artificial intelligence for detection of pancreatic cancer: a machine learning approach.Clinical and experimental medicine · 2025Article
- Early-Stage Pancreatic Cancer Diagnosis: Serum Biomarkers and the Potential for Aptamer-Based Biosensors.Molecules (Basel, Switzerland) · 2025Review
- Advances in research on malignant tumors and targeted agents for TOP2A (Review).Molecular medicine reports · 2025Review
- Extracellular derived-exosomal micrornas in pancreatic cancer: investigating their diagnostic importance and potential targets for the prevention and treatment in pancreatic cancer.Frontiers in oncology · 2025Review
- Prognostic implications of venous invasion in pancreatic cancer following radical surgical resection: a pathological perspective.Frontiers in medicine · 2025Article
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Authors and funding
41 authors.
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Abstract
backgroundPancreatic cancer is often diagnosed at advanced stages, and early-stage diagnosis of pancreatic cancer is difficult because of nonspecific symptoms and lack of available biomarkers.
methodsWe performed comprehensive serum miRNA sequencing of 212 pancreatic cancer patient samples from 14 hospitals and 213 non-cancerous healthy control samples. We randomly classified the pancreatic cancer and control samples into two cohorts: a training cohort (N = 185) and a validation cohort (N = 240). We created ensemble models that combined automated machine learning with 100 highly expressed miRNAs and their combination with CA19-9 and validated the performance of the models in the independent validation cohort.
resultsThe diagnostic model with the combination of the 100 highly expressed miRNAs and CA19-9 could discriminate pancreatic cancer from non-cancer healthy control with high accuracy (area under the curve (AUC), 0.99; sensitivity, 90%; specificity, 98%). We validated high diagnostic accuracy in an independent asymptomatic early-stage (stage 0-I) pancreatic cancer cohort (AUC:0.97; sensitivity, 67%; specificity, 98%).
conclusionsWe demonstrate that the 100 highly expressed miRNAs and their combination with CA19-9 could be biomarkers for the specific and early detection of pancreatic cancer.
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