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

A reanalysis of spatiotemporal single-cell RNA-sequencing data profiles immune and stromal cells from colorectal cancer patients treated with Pembrolizumab or Sintilimab. The 120 KB dataset, authored by Heng Zhao and last updated in May 2026, compares pre- and post-treatment samples from tumor, blood, and normal mucosa. Results highlight distinct transcriptional states in T cells and B cells associated with treatment response or resistance.

Use Cases

• Identify transcriptional signatures predictive of immunotherapy response based on T-cell activation markers like GNLY and GZMB.
• Investigate cell-cell communication networks altered by treatment using inferred signaling pathways like CXCL and IL16.
• Compare immune population remodeling across tumor, blood, and normal tissue compartments at single-cell resolution.
• Analyze the role of stress-response genes like HSPA1B in treatment resistance mechanisms.

Strengths

• Data includes matched pre- and post-treatment samples from tumor, blood, and normal mucosa, enabling spatiotemporal analysis.
• Analysis characterizes major cell types and transcriptional programs using established tools like Seurat and Harmony.
• Findings are linked to clinical response categories (CR/PR vs. SD), providing mechanistic insights.

Limitations

• The dataset is very small at 120 KB, suggesting limited scope or a summary document rather than raw sequencing data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.

Provenance

Source

figshare

Collection Method

Reanalysis of existing single-cell RNA-sequencing data from CRC patients treated with immune checkpoint inhibitors.

Freshness

Last updated 2026-05-04 05:34:12; freshness should be verified.