Glycerophospholipid Metabolism in Nasopharyngeal Carcinoma: Multi-Omics Analysis

Lipid Wang's dataset contains results from a multi-omics study of nasopharyngeal carcinoma (NPC). It integrates single-cell transcriptomics, 10x spatial transcriptomics, and spatial metabolomics to analyze gene expression and metabolite profiles in NPC tissues. The data was last updated on 2026-05-20.

Use Cases

• Identify diagnostic or prognostic markers based on the five upregulated glycerophospholipid-related genes (AGPAT3, DGAT2, SLC44A1, AGPAT5, LPGAT1).
• Analyze tumor-stromal interactions based on the described interplay between malignant epithelial cells and CCL11-expressing fibroblasts.
• Investigate spatial gene expression patterns based on the spatial trajectory analysis toward peritumoral and intratumoral immune regions.
• Study fatty acid accumulation and glycerophospholipid metabolism in the NPC microenvironment based on the described metabolic interactions.

Strengths

• Integrates three omics layers: single-cell transcriptomics, 10x spatial transcriptomics, and spatial metabolomics.
• Identifies five specific glycerophospholipid-related genes (AGPAT3, DGAT2, SLC44A1, AGPAT5, LPGAT1) as key findings.
• Released under a permissive CC-BY-4.0 license.

Limitations

• Dataset is very small at 10.0 KB, suggesting limited scope or summary-level data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare, author Liping Wang

Collection Method

Multi-omics approach integrating single-cell transcriptomics, 10x spatial transcriptomics, and spatial metabolomics on NPC tissues.

Freshness

Last updated 2026-05-20 05:47:46; freshness should be verified.