Bile Acid Profiles and Immune Cell Data from Mouse Cancer Models

A 14.0 MB dataset contains analytical results from mouse models of melanoma and breast cancer, including B16 and 4T1 cell lines. It was created by Hongyu Jiang to investigate how bile acids influence tumor glycolysis and immune evasion via the FXR-RARα pathway. The data supports findings from techniques like UPLC-MS, flow cytometry, and Seahorse extracellular flux analysis.

Use Cases

• Analyze bile acid (BA) enrichment profiles from UPLC-MS across different tumor microenvironments (TMEs) to identify metabolic signatures.
• Correlate flow cytometry immune cell analysis data with BA levels to study T cell infiltration and exhaustion states.
• Model the relationship between Seahorse extracellular flux analyzer outputs (oxygen consumption, acidification rates) and tumor progression under BA depletion.
• Investigate transcriptomic shifts toward oxidative phosphorylation genes in response to dietary BA depletion using the provided experimental results.

Strengths

• Data originates from multiple validated mouse models including C57BL/6J, BALB/c, and MMTV-PyMT strains.
• Analytical techniques are specified, including UPLC-MS for metabolite profiling and Seahorse for metabolic flux.
• The dataset is associated with a recent study, last updated in March 2026.

Limitations

• The dataset size is 14.0 MB, indicating a relatively small scale likely focused on summary or processed results rather than raw high-throughput data.
• Sample size, row count, and specific column structures are unknown, limiting assessment of statistical power and direct usability.
• Data is restricted to mouse models, and its direct applicability to human oncology may require validation.

Provenance

Source

Hongyu Jiang via figshare.

Collection Method

Experimental data from mouse cancer models analyzed with UPLC-MS, flow cytometry, and Seahorse extracellular flux analyzers.

Freshness

Last updated 2026-03-25.