Heterogeneity-Based Stratification Data for Osteosarcoma Prognosis and CKMT2 Target

A 46.8 KB ZIP file contains transcriptomic data supporting a study on osteosarcoma intratumoral heterogeneity. The data, authored by Xuesong Li and last updated on 2026-05-26, was used to identify ten primary cell types and five malignant subtypes, leading to the discovery of CKMT2 as a prognostic marker. The analysis integrated single-cell transcriptomic data with multi-cohort datasets from public repositories.

Use Cases

• Training prognostic risk models based on the ten critical genes identified through machine learning.
• Analyzing immune infiltration patterns associated with distinct molecular subtypes of osteosarcoma.
• Validating the role of CKMT2 as a therapeutic target using the provided transcriptomic profiles.
• Studying copy number variation in malignant osteoblastic cells from single-cell data.

Strengths

• Data is derived from integrated single-cell and multi-cohort transcriptomic datasets, suggesting a multi-source validation approach.
• The study identified and validated a specific prognostic biomarker, CKMT2, through clinical and functional assays.
• The dataset is licensed under CC-BY-4.0, permitting open sharing and adaptation.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment.
• The dataset is small (46.8 KB), indicating it likely contains processed results or model outputs rather than raw sequencing data.
• Freshness should be verified as the last update is dated in the future (2026-05-26).

Provenance

Source

figshare, authored by Xuesong Li.

Collection Method

Integrated from single-cell transcriptomic data and multi-cohort transcriptomic datasets sourced from public repositories.

Freshness

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