Osteosarcoma Single-Cell Transcriptomics and Prognostic Gene Model

A bioinformatics study by Xuesong Li integrates single-cell and multi-cohort transcriptomic data to map intratumoral heterogeneity in osteosarcoma. The dataset, last updated in May 2026, identifies ten primary cell types, five malignant subtypes, and a prognostic risk model based on ten genes. It establishes CKMT2 as a key prognostic biomarker and therapeutic target validated through clinical and functional assays.

Use Cases

• Training prognostic models based on the identified ten-gene risk signature.
• Analyzing tumor immune infiltration patterns based on the defined molecular subtypes.
• Investigating the functional role of CKMT2 in osteosarcoma cell proliferation.
• Validating molecular subtypes against clinical outcomes using the integrated multi-cohort data.

Strengths

• Integrates single-cell transcriptomic data with multi-cohort datasets from public repositories.
• Validates findings through immunohistochemistry and in vitro functional assays.
• Identifies a specific prognostic biomarker (CKMT2) with clinical correlation.
• Defines five malignant subtypes from osteoblastic cells based on copy number variation analysis.

Limitations

• Dataset size is 175.0 B, indicating a very limited scope, likely containing only summary or model results.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale analysis.

Provenance

Source

figshare

Collection Method

Integrated single-cell and bulk transcriptomic data from public repositories, analyzed via a bioinformatics pipeline and validated with clinical/functional assays.

Freshness

Last updated 2026-05-26 09:03:41; freshness should be verified.