Biomarkers for Prognosis in Osteosarcoma: From Molecular Signatures to Clinical Applications

Area of Science:

• Oncology
• Biomarker Discovery
• Molecular Diagnostics

Background:

• Osteosarcoma presents a significant clinical challenge, particularly in its metastatic form, with limited survival rates.
• The urgent need for reliable prognostic tools in osteosarcoma management is evident.

Purpose of the Study:

• To systematically review and identify consistent prognostic biomarkers for osteosarcoma.
• To evaluate the predictive value of various molecular and imaging markers for patient outcomes.

Main Methods:

• A comprehensive literature review of 93 studies was conducted.
• Analysis focused on identifying molecular markers (protein expression, gene amplification/disruption, epigenetic modifications, non-coding RNAs) and imaging metrics associated with prognosis.
• Statistical performance metrics, such as Area Under the Curve (AUC), were considered.

Main Results:

• p53 overexpression, high Ki-67, HER2 positivity, HIF-1α, VEGF, and MMP-9 were associated with reduced survival and advanced disease.
• MYC amplification, TP53/RB1 disruption, and loss of H4K20me3 indicated a worse prognosis.
• Epigenetic signatures predicted chemotherapy sensitivity, and non-coding RNAs (especially lncRNAs) demonstrated strong prognostic value (AUCs up to 0.88).
• CircRNAs, metabolomic markers, and 18F-FDG PET/CT metrics further refined risk stratification.

Conclusions:

• Multiple molecular and imaging biomarkers consistently predict osteosarcoma prognosis.
• These biomarkers can aid in risk stratification, treatment selection, and improving patient outcomes.
• Further validation of these prognostic tools is essential for clinical implementation.