Tryptophan Metabolism Gene Signature for Melanoma Prognosis and Immune Features

Lei Zhao's research dataset contains transcriptomic and clinical data for 457 patients with skin cutaneous melanoma (SKCM). The data was used to build a five-gene risk model (HADHA, GOT2, STAT1, CAT, IDO1) predicting patient survival and immune features. The dataset was last updated on 2026-05-19 and is shared under a CC-BY-4.0 license on figshare.

Use Cases

• Predicting overall survival in melanoma patients based on the five-gene tryptophan metabolism-related signature.
• Analyzing links between gene expression and immune cell infiltration in the tumor microenvironment.
• Investigating drug sensitivity differences between patient risk groups for chemotherapeutic and targeted drugs.
• Studying the functional role of specific genes like IDO1 in melanoma cell proliferation, migration, and metabolism.

Strengths

• Data is derived from a cohort of 457 patients with SKCM, providing a substantial sample size for analysis.
• The prognostic model was validated in independent cohorts, suggesting robustness.
• Analysis integrates multiple data types, including bulk RNA-seq, single-cell RNA-seq, and in vitro experimental validation.

Limitations

• Row count and column-level documentation are absent, requiring manual inspection after download.
• The dataset is small (16.3 KB), indicating it likely contains summary or model data rather than raw patient-level records.
• Freshness should be verified as the last update is in the future (2026-05-19).

Provenance

Source

Lei Zhao

Collection Method

Analysis of transcriptomic and clinical data from 457 SKCM patients, using unsupervised clustering, Cox regression, and validation in independent cohorts.

Freshness

Last updated 2026-05-19 05:38:39; freshness should be verified.