Lipidomic Profiles from Pancreatic Cancer Fine-Needle Aspiration Biopsies

Shenhao Liu's dataset contains lipidomic profiles from 13 pancreatic ductal adenocarcinoma patients, published on figshare in 2026. It includes measurements of 1,822 lipid species across 47 classes from paired tumor and adjacent non-tumor tissues obtained via endoscopic ultrasound-guided fine-needle aspiration. An independent cohort of 30 patient serum samples is also included for exploratory analysis.

Use Cases

• Identifying differential lipid species between tumor and non-tumor tissues based on the described LC-MS/MS lipidomic analysis.
• Investigating lipid metabolic remodeling patterns, such as fatty acyl chain elongation and unsaturation, mentioned in the results.
• Developing composite lipid scores for diagnostic or prognostic models based on the principal component loadings methodology described.
• Exploring the translational potential of minimally invasive diagnostic samples for metabolic assessment as highlighted in the conclusion.

Strengths

• Includes paired samples from 13 patients, allowing for within-patient tumor vs. non-tumor comparisons.
• Profiles a large number of lipid features, with 1,822 species across 47 classes detected.
• Uses a widely targeted (pseudo-targeted) LC-MS/MS methodology, which is a standard for lipidomics.

Limitations

• Row count is unknown, which may limit suitability assessment for certain analyses.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 20.8 KB, indicating limited scope and likely a summary or processed results table rather than raw spectral data.

Provenance

Source

figshare, author Shenhao Liu.

Collection Method

Lipidomic analysis via liquid chromatography–tandem mass spectrometry (LC–MS/MS) on endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) derived specimens.

Freshness

Last updated 2026-05-29 04:46:54; freshness should be verified.