Gastric Cancer Prognostic Gene Signature Derived from Bulk and Single-Cell RNA Sequencing

Ruilong Kou's 2026 analysis identifies a four-gene prognostic signature for gastric cancer. The 28.2 KB CSV file contains results from an integrated analysis of bulk transcriptomics and single-cell RNA sequencing data related to stress granules. The study validated a risk model for patient survival and linked gene expression to immune infiltration and drug sensitivity.

Use Cases

• Building prognostic risk models for gastric cancer based on the identified four-gene signature (SERPINE1, CD36, MMRN1, GRP).
• Analyzing associations between stress granule-related genes and immune cell infiltration patterns, such as mast cells.
• Investigating cell-type-specific expression of prognostic genes using single-cell RNA sequencing data.
• Assessing potential chemotherapy drug sensitivity in patient subgroups based on the described risk stratification.

Strengths

• Data is derived from an integrated analysis of both bulk and single-cell RNA sequencing, as described.
• The prognostic model was validated in an independent cohort, suggesting methodological rigor.
• File is small (28.2 KB) and in a standard CSV format, facilitating quick inspection.

Limitations

• Row count and column-level documentation are unknown; field semantics must be inferred after download.
• The dataset's 28.2 KB size indicates it contains summary-level results, not raw sequencing data.
• Data may reflect bias inherent to the specific public databases and literature sources used in the study.

Provenance

Source

figshare, author Ruilong Kou

Collection Method

Integrated analysis of public single-cell and transcriptomic data for gastric cancer and stress granule-related genes from literature.

Time Range

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Freshness

Last updated 2026-03-17 13:05:15

Geography

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