Gastric Cancer Prognostic Gene Signature from Integrated Bulk and Single-Cell RNA Analysis

A study by Ruilong Kou, published on figshare in March 2026, identifies a four-gene signature (SERPINE1, CD36, MMRN1, GRP) related to stress granules and associated with prognosis in gastric cancer. The 150.9 KB CSV file contains results from an integrated analysis of bulk transcriptomics and single-cell RNA sequencing data from public databases, used to construct and validate a risk score model for patient survival.

Use Cases

• Validate prognostic risk models for gastric cancer based on the identified four-gene signature.
• Analyze associations between stress granule-related genes and immune cell infiltration patterns, such as mast cells.
• Investigate gene expression patterns in specific cell types, like endothelial cells, using single-cell RNA sequencing results.
• Assess potential chemotherapy drug sensitivity in patient subgroups stratified by the described risk model.

Strengths

• Integrated analysis combines bulk transcriptomics and single-cell RNA sequencing data.
• Model validation was performed in an independent cohort.
• Results include specific correlation coefficients (r > 0.3) and statistical significance (P < 0.001) for gene-immune cell associations.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small (150.9 KB), indicating limited scope, likely containing summary results rather than raw sequencing data.

Provenance

Source

figshare, author Ruilong Kou.

Collection Method

Data acquired from public databases and literature; analysis includes differential expression, Cox regression, and functional enrichment.

Time Range

Temporal coverage of the source data is not specified.

Freshness

Last updated 2026-03-17 13:05:14; freshness should be verified.

Geography

Geographic coverage of the patient cohorts is not specified.