Novel candidate metastasis-associated genes for synovial sarcoma.
Zhiqing ZhaoJianfang NiuJichuan WangRanxin ZhangHaijie LiangYingteng MaAlexander FerrenaWei WangRui YangDavid S GellerWei GuoTingting RenBang H HoangXiaodong TangTaiqiang YanPublished in: Journal of cellular and molecular medicine (2024)
Synovial sarcoma (SS) is an aggressive soft tissue sarcoma with poor prognosis due to late recurrence and metastasis. Metastasis is an important prognostic factor of SS. This study aimed to identify the core genes and mechanisms associated with SS metastasis. Microarray data for GSE40021 and GSE40018 were obtained from the Gene Expression Omnibus database. 186 differentially expressed genes (DEGs) were identified. The biological functions and signalling pathways closely associated with SS metastasis included extracellular matrix (ECM) organization and ECM-receptor interaction. Gene set enrichment analysis showed that the terms cell cycle, DNA replication, homologous recombination and mismatch repair were significantly enriched in the metastasis group. Weighted gene co-expression network analysis identified the most relevant module and 133 hub genes, and 31 crossover genes were identified by combining DEGs. Subsequently, four characteristic genes, EXO1, NCAPG, POLQ and UHRF1, were identified as potential biomarkers associated with SS metastasis using the least absolute shrinkage and selection operator algorithm and validation dataset verification analysis. Immunohistochemistry results from our cohort of 49 patients revealed visible differences in the expression of characteristic genes between the non-metastatic and metastatic groups. Survival analysis indicated that high expression of characteristic genes predicted poor prognosis. Our data revealed that primary SS samples from patients who developed metastasis showed activated homologous recombination and mismatch repair compared to samples from patients without metastasis. Furthermore, EXO1, NCAPG, POLQ and UHRF1 were identified as potential candidate metastasis-associated genes. This study provides further research insights and helps explore the mechanisms of SS metastasis.
Keyphrases
- poor prognosis
- genome wide
- bioinformatics analysis
- genome wide identification
- gene expression
- long non coding rna
- cell cycle
- prognostic factors
- extracellular matrix
- end stage renal disease
- network analysis
- dna methylation
- genome wide analysis
- dna damage
- chronic kidney disease
- small cell lung cancer
- emergency department
- cell proliferation
- computed tomography
- ejection fraction
- dna repair
- big data
- clinical trial
- transcription factor
- deep learning
- binding protein
- patient reported
- data analysis