Systematic Profiling of Alternative Splicing for Sarcoma Patients Reveals Novel Prognostic Biomarkers Associated with Tumor Microenvironment and Immune Cells
| Autor: | Lin Ye, Chuan Liu, Shaoqi Tian, Kang Sun, Rui Shen, Huili Rao, Jian-jun Ye, Yuanhe Wang, Chuan Hu, Bo Chen |
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| Rok vydání: | 2020 |
| Předmět: |
Oncology
Adult Male medicine.medical_specialty Gene Expression Subgroup analysis Disease-Free Survival Cohort Studies Immune system Internal medicine Databases Genetic medicine Biomarkers Tumor Tumor Microenvironment Humans RNA Messenger Proportional Hazards Models Tumor microenvironment business.industry Proportional hazards model Gene Expression Profiling Area under the curve Sarcoma General Medicine Nomogram Middle Aged medicine.disease Prognosis Alternative Splicing Nomograms Area Under Curve Immune System Database Analysis Biomarker (medicine) Female business Transcriptome |
| Zdroj: | Medical Science Monitor : International Medical Journal of Experimental and Clinical Research |
| ISSN: | 1643-3750 |
| Popis: | BACKGROUND Alternative splicing (AS) events is a novel biomarker of tumor prognosis, but the role of AS events in sarcoma patients remains unclear. MATERIAL AND METHODS RNA-seq and clinicopathologic data of the sarcoma cohort were extracted from the TCGA database and data on AS events were downloaded from the TCGASpliceSeq database. Univariate Cox analysis, LASSO regression analysis, and multivariate Cox analysis were performed to determine the overall survival (OS)- and disease-free survival (DFS)-related AS events. Two nomograms were developed based on the independent variables, and subgroup analysis was performed. The area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomograms. Then, we used the CIBERSORT and ESTIMATE package to determine the immune cell proportion and tumor microenvironment (TME) score, respectively. The associations between AS events-based clusters and TME and immune cells were studied. RESULTS We identified 1945 and 1831 AS events as OS- and DFS-related AS events, respectively. Two nomograms based on the AS events and clinical data were established and the AUCs of nomograms ranged from 0.807 to 0.894. The calibration curve and DCA showed excellent performance of nomograms. In addition, the results indicated the distinct relationships between AS events-based clusters and OS, DFS, immune score, stromal score, and 10 immune cells. CONCLUSIONS Our study indicated that AS events are novel prognostic biomarkers for sarcoma patients that may be associated with the TME and immune cells. |
| Databáze: | OpenAIRE |
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