ArticleActa cirurgica brasileira2020
Differences in lipidomics may be potential biomarkers for early diagnosis of pancreatic cancer.
Article in Acta cirurgica brasileira, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 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
9 citing papers in PubMed.
- Diagnostic methods for pancreatic cancer and their clinical applications (Review).Oncology letters · 2025Review
- Anti-Toxoplasma gondii efficacy of beta, beta-dimethylacrylshikonin and isobutyrylshikonin in vitro and in vivo.Parasites & vectors · 2025Article
- Genetically predicted causal link between the plasma lipidome and pancreatic diseases: a bidirectional Mendelian randomization study.Frontiers in nutrition · 2024Article
- Multimodal Imaging of Pancreatic Cancer Microenvironment in Response to an Antiglycolytic Drug.Advanced healthcare materials · 2023Article
- Lipidomics and pancreatic cancer risk in two prospective studies.European journal of epidemiology · 2023Article
- Identification of the γ-glutamyl cycle as a novel therapeutic target and 5-oxoproline as a new biomarker for diagnosing pancreatic cancer.Annals of medicine · 2023Article
- Lipidomic Profiling Identifies a Novel Lipid Signature Associated with Ethnicity-Specific Disparity of Bladder Cancer.Metabolites · 2022Article
- Development of a lipid metabolism-related gene model to predict prognosis in patients with pancreatic cancer.World journal of clinical cases · 2021Article
- Pancreatic cancer and adaptive metabolism in a nutrient-deficient environment.Central-European journal of immunology · 2021Review
Corrections and comments
- Erratum issued
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo analyze the plasma lipid spectrum between healthy control and patients with pancreatic cancer and to select differentially expressed tumor markers for early diagnosis.
methodsIn total, 20 patents were divided into case group and healthy control group according to surgical pathology. Of almost 1206 plasma lipid molecules harvested from 20 patients were measured by HILIC using the normal phase LC/MS. Heat map presented the relative levels of metabolites and lipids in the healthy control group and patients with pancreatic cancer. The PCA model was constructed to find out the difference in lipid metabolites. The principal components were drawn in a score plot and any clustering tendency could be observed. PLS-DA were performed to distinguish the healthy control group and pancreatic cancer according to the identified lipid profiling datasets. The volcano plot was used to visualize all variables with VIP>1 and presented the important variables with P<0.01 and |FC|>2.
resultsThe upregulated lipid metabolites in patients with pancreatic cancer contained 9 lipids; however, the downregulated lipid metabolites contained 79 lipids.
conclusionThere were lipid metabolomic differences in patients with pancreatic cancer, which could serve as potential tumor markers for pancreatic cancer.
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.