Celecoxib-Cervical Cancer Relationship Analysis via In Vitro and Mendelian Randomization

A 709.1 KB Excel dataset presents results from a multi-method study investigating celecoxib's anticancer role against cervical cancer. The research combines in vitro assays, network pharmacology, and Mendelian randomization analyses to identify causal relationships and immune-related mechanisms. The dataset was authored by Tongfei Wang and last updated on May 19, 2026.

Use Cases

• Validate drug efficacy hypotheses based on in vitro assay results for proliferation, migration, and invasion.
• Explore causal drug-target relationships based on Mendelian randomization findings linking NEU1 inhibition to cancer risk.
• Analyze immune pathway mediation based on enrichment analysis results highlighting T-cell-related pathways.
• Assess genetic proxy effects based on odds ratio and confidence interval data for NEU1 inhibition.
• Study therapeutic mechanism mediation based on the reported percentage of effect mediated by specific immune cells.

Strengths

• Integrates results from three distinct methodological approaches: in vitro experiments, network pharmacology, and Mendelian randomization.
• Provides specific quantitative results, including an odds ratio of 0.736 with a 95% confidence interval for NEU1 inhibition.
• Identifies a concrete mediation percentage (28.458%) for a specific immune cell type in the therapeutic effect.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (709.1 KB), indicating limited scope and likely summary-level results rather than raw experimental data.

Provenance

Source

figshare

Collection Method

Results from integrated laboratory experiments, computational network analysis, and genetic causal inference.

Freshness

Last updated 2026-05-19 05:41:46; freshness should be verified.