SCore: A Senescence-Circadian Interplay Score for Colorectal Cancer Prognosis

Li-zhi Luo published a transcriptomic dataset on figshare in 2026 for constructing a senescence-circadian interplay score (SCore) in colorectal cancer. The dataset integrates bulk transcriptomic and clinical data from public cohorts, including TCGA-COAD/READ, GSE12945, and GSE39582. It supports analyses of prognosis, immune landscape features, and drug sensitivity predictions.

Use Cases

• Training prognostic models based on the four-gene SCore signature derived from senescence and circadian genes.
• Analyzing associations between transcriptomic signatures and immune dysfunction/exclusion features mentioned in the description.
• Investigating cell-cell communication dynamics, such as MIF-(CD74+CXCR4) signaling, within the T-cell context using single-cell data references.
• Validating experimental findings, like NOX4 knockdown effects on ROS and PD-L1 expression, with orthogonal transcriptomic data.

Strengths

• Includes orthogonal experimental validation from RT-qPCR and immunohistochemistry on 120 paired CRC tissues.
• Model was evaluated in a training cohort (TCGA) and externally validated in two independent cohorts (GSE12945, GSE39582).
• The dataset links transcriptomic scores to functional experiments, such as NOX4 knockdown affecting migratory capacity.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale analyses.
• The dataset is small (24.3 KB), indicating it likely contains summary scores or model parameters rather than raw expression data.

Provenance

Source

figshare

Collection Method

Integrated bulk transcriptomic and clinical data from public CRC cohorts (TCGA, GEO).

Freshness

Last updated 2026-06-03 06:01:24; freshness should be verified.