Data Sheet 2_Unveiling prognostic genes and regulatory mechanisms of stress granules in ga

Ruilong Kou's dataset, last updated March 2026, contains a four-gene prognostic signature for gastric cancer derived from integrated bulk transcriptomics and single-cell RNA sequencing data. The 13.2 KB CSV file presents results from an analysis linking stress granule-related genes to patient survival and tumor biology. The study identified SERPINE1, CD36, MMRN1, and GRP as key prognostic markers and constructed a validated risk model.

Use Cases

• Building prognostic risk models for gastric cancer based on the identified four-gene signature.
• Analyzing associations between stress granule-related genes and immune cell infiltration patterns, such as mast cells.
• Investigating chemotherapy drug sensitivity predictions stratified by the described risk groups.
• Exploring cell-type-specific expression of prognostic genes, particularly in endothelial cells, using single-cell data.

Strengths

• Dataset is derived from an integrated analysis of both bulk and single-cell RNA sequencing data.
• The prognostic model was validated in an independent cohort, suggesting a tested methodology.
• Results include specific correlation coefficients (r > 0.3) and p-values (P < 0.001) for gene-immune cell associations.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• The dataset is very small at 13.2 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 involved differential expression, Cox regression, and functional enrichment.

Time Range

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Freshness

Last updated 2026-03-17 13:05:16; freshness should be verified.

Geography

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