ArticleScientific data2025
Proteomics profiling of research models for studying pancreatic ductal adenocarcinoma.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- Can Complex 3D Models Effectively Replace 2D and Animal Models to Investigate the Microbe-Tumor-Immune Axis in Pancreatic Cancer Studies?Nutrients · 2026Review
- Knowledge Discovery and Drug-Repurposing Framework for Pancreatic Ductal Adenocarcinoma: Molecular Networking and Computational Docking.Computational and structural biotechnology journal · 2026Article
- Genetic Variants and Soluble Isoforms of PD-1/PD-L1 as Novel Biomarkers for Pancreatic Ductal Adenocarcinoma (PDAC) Susceptibility and Prognosis.Biomedicines · 2025Article
- Knowledge Discovery in Databases of Proteomics by Systems Modeling in Translational Research on Pancreatic Cancer.Proteomes · 2025Article
- Proteomics profiling of research models for studying pancreatic ductal adenocarcinoma.Scientific data · 2025Article
- Translational studies on pancreatic cancer and gastric cancer: a methodology in PhD thesis.Frontiers in pharmacology · 2025Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival rate of 10-15% due to late-stage diagnosis and limited efficacy of existing treatments. This study utilized proteomics-based systems modelling to generate multimodal datasets from various research models, including PDAC cells, spheroids, organoids, and tissues derived from murine and human samples. Identical mass spectrometry-based proteomics was applied across the different models. The preparation and validation of the research models and the proteomics were described in detail. The assembly datasets we present here contribute to the data collection on PDAC, which will be useful for systems modelling, data mining, knowledge discovery in databases, and bioinformatics of individual models. Further data analysis may lead to the generation of research hypotheses, predictions of targets for diagnosis and treatment, and relationships between data variables.
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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.