Mouse Brain Single-Nucleus RNA-Seq Data in Response to Small-Cell Lung Cancer

48,686 nuclei from whole-brain single-nucleus RNA sequencing of an Rb1/Trp53/Myc-driven SCLC mouse model, integrated with tumor and plasma transcriptomic and metabolomic analyses. The dataset was created by Jingwei Duan and last updated on June 2, 2026. It provides cell-type-resolved transcriptional profiles to investigate systemic brain effects of primary lung cancer.

Use Cases

• Identify cell-type-specific transcriptional alterations in the brain based on the whole-brain single-nucleus RNA sequencing data.
• Analyze dysregulation of myelination-related genes (e.g., Mbp, Plp1, Mobp) in oligodendrocyte precursor cells as described.
• Investigate correlations between tumor metabolite levels (glutamate, GABA) and brain gene expression changes mentioned in the integrated analysis.
• Validate findings from the mouse model against public SCLC patient cohorts as referenced in the description.

Strengths

• Includes 48,686 sequenced nuclei, providing a substantial single-cell resolution view of brain-wide changes.
• Integrates multiple data modalities: single-nucleus RNA-seq, transcriptomics, and metabolomics from tumors and plasma.
• Findings are validated across public SCLC patient cohorts, suggesting translational relevance.

Limitations

• Row count for the primary data table is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is from a specific genetically engineered mouse model; direct applicability to human biology may be limited.

Provenance

Source

figshare, author Jingwei Duan.

Collection Method

Single-nucleus RNA sequencing of whole brains from an Rb1/Trp53/Myc-driven SCLC mouse model, integrated with tumor/plasma omics.

Freshness

Last updated 2026-06-02 05:26:47; freshness should be verified.