Senescence-Circadian Interplay Score (SCore) for Colorectal Cancer Prognosis

A 10.0 KB Excel file contains a four-gene transcriptomic model for colorectal cancer risk stratification. The dataset, authored by Li-zhi Luo and last updated in June 2026, integrates bulk and single-cell RNA sequencing data from public cohorts like TCGA-COAD/READ, GSE12945, and GSE39582. It includes findings validated by RT-qPCR and immunohistochemistry on 120 paired CRC and adjacent non-tumor tissues.

Use Cases

• Validate prognostic biomarkers for colorectal cancer based on the senescence-circadian interplay score (SCore).
• Analyze associations between SCore and immune dysfunction/exclusion features mentioned in the description.
• Investigate cell-cell communication dynamics, such as MIF-(CD74+CXCR4) signaling, within the T-cell context.
• Correlate transcriptomic signatures with predicted drug sensitivity profiles for high-SCore tumors.

Strengths

• Includes orthogonal experimental validation from RT-qPCR and immunohistochemistry on 120 paired tissue samples.
• Model was evaluated in a training cohort (TCGA) and externally validated in two independent cohorts (GSE12945, GSE39582).
• Analysis spans multiple data modalities, including bulk transcriptomics, clinical data, and single-cell RNA sequencing.

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 (10.0 KB), indicating it likely contains summary results or model scores rather than raw expression data.

Provenance

Source

Integrated public CRC cohorts including TCGA-COAD/READ, GSE12945, and GSE39582.

Collection Method

Bulk and single-cell RNA sequencing data analysis, followed by experimental validation.

Freshness

Last updated 2026-06-03 06:19:04; freshness should be verified.