Spatial Transcriptomics of Pancreatic Ductal Adenocarcinoma Revealing Heterogeneity

18,075 spatial spots from one normal pancreatic tissue, PC tissue, adjacent tumor tissue, and tumor stroma were analyzed using spatial transcriptomics. The study, authored by Zhangyong Ren and last updated in April 2026, identified 22 distinct clusters, including a KRT13+FABP5+ malignant cell subpopulation and FGG+CRP+ inflammatory cancer-associated fibroblasts. Results highlight the spatial heterogeneity of dynamic changes and the significance of impaired exocrine function in pancreatic cancer progression.

Use Cases

• Identify malignant cell subpopulations based on keratinization characteristics like KRT13+FABP5+ expression.
• Analyze the functional roles of tumor-inhibiting fibroblasts based on pathways such as 'B-cell activation'.
• Study the replacement of pancreatic islets by inflammatory cancer-associated fibroblasts based on FGG+CRP+ markers.
• Compare damage to pancreatic exocrine (AMYA2+PRSS1+) versus endocrine (INS+GCG+) function during cancer progression.

Strengths

• Data is derived from spatial transcriptomics, a high-resolution technique for mapping gene expression.
• Analysis covers 18,075 spatial spots across four distinct tissue types (normal, tumor, adjacent, stroma).
• Results are structured into 22 biologically relevant clusters with functional pathway analysis.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (22.1 KB), suggesting it may contain summary results rather than raw expression data.

Provenance

Source

figshare

Collection Method

Spatial transcriptomics performed on pancreatic tissue samples.

Time Range

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Freshness

Last updated 2026-04-24 12:31:53; freshness should be verified.

Geography

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