ArticleJournal of Cancer2022
Integrative analysis of metabolome and gut microbiota in Patients with pancreatic ductal adenocarcinoma.
Article in Journal of Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
16 citing papers in PubMed, 18 citations in OpenAlex.
- Microbiome-based diagnostic biomarkers in pancreatic ductal adenocarcinoma: Current evidence and translational challenges (Review).Oncology letters · 2026Review
- Detection of Pancreatic Cancer via Specific Metabolite Markers: A Metabolomics Approach.Health science reports · 2026Article
- Microbiome and pancreatic ductal adenocarcinoma: mechanistic insights, microenvironmental interactions, and therapeutic implications.Molecular biology reports · 2026Review
- Cecal microbiota regulates meat quality of Yanshan red jade broilers: insights from metagenomics and targeted metabolomics.Poultry science · 2026Article
- The role of theFrontiers in microbiology · 2026Review
- Oral and fecal microbiome alterations in pancreatic cancer: insights into potential diagnostic biomarkers.BMC microbiology · 2025Article
- Mendelian randomization study reveals causal association between skin microbiome and skin cancers.Scientific reports · 2025Article
- Microbiota as a state-of-the-art approach in precision medicine for pancreatic cancer management: A comprehensive systematic review.iScience · 2025Article
- From Microbiome to Malignancy: Unveiling the Gut Microbiome Dynamics in Pancreatic Carcinogenesis.International journal of molecular sciences · 2025Review
- ORASPORT study protocol: a prospective observational study on the impact of endurance physical activity on oral microbiology and immunology.Frontiers in oral health · 2025Article
- Microbiome as a biomarker and therapeutic target in pancreatic cancer.BMC microbiology · 2024Review
- Contributions of the Microbiome-Derived Metabolome for Risk Assessment and Prognostication of Pancreatic Cancer.Clinical chemistry · 2024Review
- Evaluating Metabolite-Based Biomarkers for Early Diagnosis of Pancreatic Cancer: A Systematic Review.Metabolites · 2023Review
- Microbiota Regulates Pancreatic Cancer Carcinogenesis through Altered Immune Response.Microorganisms · 2023Review
- Role of microbiota and microbiota-derived short-chain fatty acids in PDAC.Cancer medicine · 2023Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumour with a poor prognosis and a high mortality rate. It is of great significance to explore sensitive or specific biomarkers for early diagnosis and prognosis. We first examined the metabolome and gut microbiota of resectable and unresectable PDAC patients to comprehensively investigate the characteristics of PDAC at different stages of progression. At the genus level, we found that the relative abundances of Alistipes, Anaerostipes, Faecalibacterium and Parvimonas were reduced in unresectable PDAC patients, whereas Pseudonocardia, Cloacibacterium, Mucispirillum, and Anaerotruncus were increased. Metabolomics analysis showed that the main changed metabolites were amino acids, carnitine derivatives, lipids and fatty acids. ROC analysis showed that Oleic acid, Linoleic acid, Palmitic acid, Linoelaidyl carnitine, 2-Octenedioic acid, 3R, 7R-1,3,7-Octanetriol, LysoPE (P-16:0/0:0) and 3-Hydroxyanthranilic acid had high AUC values (>0.9). Function and network analyses showed that these altered metabolites correlated with NF-kappa B signalling, the FXR/RXR pathway, mitochondrial dysfunction, mTOR signalling and IL-6 signalling. In particular, the abundance of Palmitic acid, Oleic acid, Linoelaidyl carnitine and 2-Octenedioic acid positively correlated with
Indexed as
Identifiers
What OpenQuestion holds
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.