期刊
CELLS
卷 12, 期 17, 页码 -出版社
MDPI
DOI: 10.3390/cells12172179
关键词
pediatric cancer; osteosarcoma; proteomics
类别
This study aimed to identify proteomic signatures that distinguish between different osteosarcoma subtypes, providing insights into their molecular heterogeneity and potential implications for personalized treatment approaches. The identified proteomics signature encompassed a diverse array of proteins involved in focal adhesion, ECM-receptor interaction, PI3K-Akt signaling pathways, and proteoglycans in cancer, among the top enriched pathways. By identifying subtype-specific proteomics signatures, clinicians may be able to tailor therapy regimens to individual patients, optimizing treatment efficacy and minimizing adverse effects.
Osteosarcoma is a primary malignant bone tumor affecting adolescents and young adults. This study aimed to identify proteomic signatures that distinguish between different osteosarcoma subtypes, providing insights into their molecular heterogeneity and potential implications for personalized treatment approaches. Using advanced proteomic techniques, we analyzed FFPE tumor samples from a cohort of pediatric osteosarcoma patients representing four various subtypes. Differential expression analysis revealed a significant proteomic signature that discriminated between these subtypes, highlighting distinct molecular profiles associated with different tumor characteristics. In contrast, clinical determinants did not correlate with the proteome signature of pediatric osteosarcoma. The identified proteomics signature encompassed a diverse array of proteins involved in focal adhesion, ECM-receptor interaction, PI3K-Akt signaling pathways, and proteoglycans in cancer, among the top enriched pathways. These findings underscore the importance of considering the molecular heterogeneity of osteosarcoma during diagnosis or even when developing personalized treatment strategies. By identifying subtype-specific proteomics signatures, clinicians may be able to tailor therapy regimens to individual patients, optimizing treatment efficacy and minimizing adverse effects.
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