Single-Cell RNA-Seq Profiles of Colorectal Cancer Patients Before and After Immunotherapy

Heng Zhao reanalyzed spatiotemporal single-cell RNA-sequencing data from colorectal cancer patients treated with Pembrolizumab or Sintilimab. The dataset profiles immune and stromal compartments across pre- and post-treatment tumor, blood, and normal mucosa samples. It was last updated on May 4, 2026, and is shared under a CC-BY-4.0 license.

Use Cases

• Identify transcriptional signatures associated with treatment response based on differential gene expression of GNLY, GZMB, CXCL13, and HSPA1B.
• Analyze immune cell remodeling in T and B cell lineages based on single-cell profiles from tumor, blood, and normal tissue.
• Model cell-cell communication networks using inferred signaling pathways like CXCL, IL16, and CD22.
• Investigate the role of TXNIP in B-cell phenotype changes following immune checkpoint blockade treatment.

Strengths

• Data is licensed under CC-BY-4.0, allowing for broad reuse.
• The analysis integrates spatiotemporal single-cell profiles from multiple tissue types (tumor, blood, normal mucosa).
• The description details specific gene markers (e.g., GNLY, HSPA1B, TXNIP) and signaling pathways associated with clinical outcomes.

Limitations

• The dataset is very small at 9.2 KB, suggesting it contains summary or processed results rather than raw single-cell data.
• Row count and column-level documentation are absent, limiting suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Reanalysis of existing single-cell RNA-sequencing data from clinical trials using Seurat, Harmony, and CellChat tools.

Freshness

Last updated 2026-05-04 05:34:13