Identification Of 9-Gene Epithelial-Mesenchymal Transition Related Signature Of Osteosarcoma By Integrating Multi Cohorts

TECHNOLOGY IN CANCER RESEARCH & TREATMENT(2020)

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Abstract
Background:The prognosis of patients with osteosarcoma is still poor due to the lack of effective prognostic markers. The EMT (epithelial-mesenchymal transition) serves as a promoter in the progression of osteosarcoma. This study systematically analyzed EMT-related genes to explore new markers for predicting the prognosis of osteosarcoma.Methods:RNA-Seq data and clinical information were obtained from the GEO database; GSVA and GSEA analysis were used to enrich pathways related to osteosarcoma progression; LASSO method analysis was used to construct the prognosis risk signature. The "Nomogram" package generated the risk prediction nomogram, and its clinical applicability was evaluated by decision curve analysis (DCA).Results:GSVA and GSEA analysis showed that the EMT signaling pathway was closely related to osteosarcoma progression. A 9-genes signature (LAMA3, LGALS1, SGCG, VEGFA, WNT5A, MATN3, ANPEP, FUCA1, and FLNA) was constructed. The overall survival (OS) of the high-risk scores group was significantly lower than the low-risk scores group. The 9-gene signature demonstrated good predictive accuracy. Cox regression analysis showed that the 9-gene signature provided independent prognostic factors for osteosarcoma patients. In addition, the predictive nomogram model could effectively predict the prognosis of osteosarcoma patients.Conclusion:This study constructed a 9-gene signature as a new prognostic marker to predict osteosarcoma patients' survival.
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Key words
osteosarcoma, GSVA, EMT, nine gene, prognostic markers
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