Osteosarcoma Multi-Omics Data on Lactylation and HDGF Regulation

A research data sheet describes an integrative multi-omics study of osteosarcoma, combining single-cell RNA sequencing, spatial transcriptomics, and machine learning. The study investigates lactylation-driven metabolic reprogramming and its link to tumor progression via the HDGF factor. The document was authored by Shidong Hu and last updated on 2026-05-20.

Use Cases

• Study lactylation-associated gene networks in osteosarcoma based on the described multi-omics approach.
• Validate prognostic models for osteosarcoma based on the identified tumor subpopulation with high lactylation activity.
• Investigate the role of hepatoma-derived growth factor (HDGF) in tumor proliferation and immune modulation as described.
• Perform virtual screening for potential therapeutics targeting HDGF based on the study's findings.

Strengths

• Document is 5.4 MB, providing a detailed research context.
• Study employs multiple methodologies including single-cell RNA-seq, spatial transcriptomics, and SHAP analysis.
• Research includes experimental functional validation and in vivo studies as described.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The primary data file is a DOCX document, not a structured data table.

Provenance

Source

figshare

Collection Method

Integrative multi-omics approach combining single-cell RNA sequencing, spatial transcriptomics, and machine learning-based modeling.

Freshness

Last updated 2026-05-20 05:23:37; freshness should be verified.