Spatial Transcriptomics of Pancreatic Ductal Adenocarcinoma Revealing Heterogeneity

Zhangyong Ren published this dataset on figshare in April 2026. It contains spatial transcriptomics data from one normal pancreatic tissue, pancreatic ductal adenocarcinoma tissue, adjacent tumor tissue, and tumor stroma. The study analyzed 18,075 spatial spots, identifying 22 clusters to investigate the spatial heterogeneity of the tumor microenvironment.

Use Cases

• Cluster analysis of tumor microenvironment cell types based on the 22 identified gene expression clusters.
• Gene set enrichment analysis to study biological functions and signaling pathways in specific spatial spots.
• Characterizing the role of specific fibroblast subpopulations, such as FGG+CRP+ inflammatory cancer-associated fibroblasts.
• Comparing gene expression features between pancreatic exocrine and endocrine components during cancer progression.

Strengths

• Data is derived from spatial transcriptomics, a technique providing gene expression with spatial context.
• Analysis covers 18,075 spatial spots across four distinct tissue types.
• Results are published under a permissive CC-BY-4.0 license.

Limitations

• The dataset is very small at 23.6 KB, suggesting it may contain summary results or a document rather than raw expression matrices.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for machine learning.

Provenance

Source

figshare

Collection Method

Spatial transcriptomics performed on pancreatic tissue samples.

Time Range

The study's data collection timeframe is not specified.

Freshness

Last updated 2026-04-24 12:31:54; freshness should be verified.

Geography

The geographic origin of the tissue samples is not specified.