Colorectal Cancer Prognostic Model Based on Six Folic Acid Metabolism Genes

A prognostic model for colorectal cancer built using six folic acid metabolism-related genes (PANX2, SLC16A8, MMP3, CILP2, ASPHD1, TSPEAR). The dataset was created by Lu Bai and last updated on 2026-05-17. It includes analysis of immune infiltration and molecular subtyping derived from TCGA-COAD/READ and GSE38832 datasets.

Use Cases

• Building a prognostic risk score for colorectal cancer patients based on the six identified folic acid metabolism-related genes.
• Analyzing immune cell infiltration differences between high-risk and low-risk patient groups.
• Exploring molecular mechanisms, such as enrichment in the Wnt signaling pathway, using differentially expressed genes between risk groups.
• Classifying colorectal cancer into molecular subtypes based on immune heterogeneity revealed by prognostic genes.

Strengths

• The model is built on six specific genes (PANX2, SLC16A8, MMP3, CILP2, ASPHD1, TSPEAR) identified through LASSO and Cox regression analyses.
• Validation was performed using an independent dataset (GSE38832) alongside the primary TCGA training set.
• Analysis includes multiple methodologies: immune infiltration assessment (CIBERSORT, ssGSEA, ESTIMATE) and molecular mechanism exploration (GSEA, GO, KEGG).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset size is 451.6 KB, indicating a limited scope focused on model results rather than raw patient-level data.

Provenance

Source

figshare, author Lu Bai

Collection Method

Data derived from TCGA-COAD/READ datasets (training) and GSE38832 (validation). Analysis involved molecular subtyping, LASSO regression, Cox analyses, and immune infiltration assessment.

Freshness

Last updated 2026-05-17 06:30:33; freshness should be verified.