ArticleStem cells international2026
Unraveling the Predictive Value of
Article in Stem cells international, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Precision Therapeutics in Pancreatic Cancer: Emerging Targeted, Immune, and Antibody-Drug Conjugate Strategies Exemplified by Adagrasib, Dostarlimab, and Trastuzumab Deruxtecan.Journal of clinical medicine · 2026Review
- Unraveling the Predictive Value ofStem cells international · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The progression of pancreatic adenocarcinoma (PAAD) is closely linked to autophagy and microRNA (miRNA) regulation. Therefore, constructing miRNA regulatory networks based on PAAD autophagy-related genes is essential for improving targeted therapy. Methods: In this study, we downloaded PAAD-related data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), PAAD-related miRNA data from Gene Expression Omnibus (GEO), and mined autophagy from existing literature reports for autophagy-related genes. Autophagy signature scores were assessed employing single-sample gene set enrichment analysis (ssGSEA) and screened for autophagy-associated candidate genes via weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Bioinformatics tools such as CIBERSORT and ESTIMATE were employed to assess the level of immune infiltration. The Encori database and Cytoscape 3.8.0 tools were used to construct the miRNA regulatory network. The PubChem website and AutoDockTools were used for targeted drug prediction and molecular docking of PAAD autophagy-related genes. Cell counting kit-8 (CCK-8), scratch healing assay, transwell assay, etc. were used to investigate the regulatory effect of biomarkers on the PAAD cells. Results: WGCNA combined differential expression analysis obtained candidate genes related to PAAD autophagy, which were primarily implicated in the pathways of phagocytosis and miRNAs in cancer. Among them, four characteristic genes ( Conclusion: The present study elucidated genes associated with autophagy features in PAAD by bioinformatics and constructed corresponding miRNA networks and molecular docking models, and predicted potential target drugs for PAAD, which will guide the development of prognostic therapeutic strategies for PAAD.
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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.