Weifeng Hong1, Weicong Zhang2, Renguo Guan3, Yuying Liang1, Shixiong Hu3, Yayun Ji1, Mouyuan Liu1, Hai Lu2, Min Yu3, Liheng Ma1. 1. Department of Medical Imaging, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China. 2. Department of Orthopaedics, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, China. 3. Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510000, China.
Abstract
BACKGROUND: Sarcomas (SARCs) are rare malignant tumors with poor prognosis. Increasing evidence has suggested that aberrant alternative splicing (AS) is strongly associated with tumor initiation and progression. We considered whether survival-related AS events might serve as prognosis predictors and underlying targeted molecules in SARC treatment. METHODS: RNA-Seq data of the SARC cohort were downloaded from The Cancer Genome Atlas (TCGA) database. Survival-related AS events were selected by univariate and multivariate Cox regression analyses. Metascape was used for constructing a gene interaction network and performing functional enrichment analysis. Then, prognosis predictors were established based on statistically significant survival-related AS events and evaluated by receiver operator characteristic (ROC) curve analysis. Finally, the potential regulatory network was analyzed via Pearson's correlation between survival-related AS events and splicing factors (SFs). RESULTS: A total of 3,610 AS events and 2,291 genes were found to be prognosis-related in 261 SARC samples. The focal adhesion pathway was identified as the most critical molecular mechanism corresponding to poor prognosis. Notably, several prognosis predictors based on survival-related AS events showed excellent performance in prognosis prediction. The area under the curve of the ROC of the risk score was 0.85 in the integrated predictor. The splicing network proved complicated regulation between prognosis-related SFs and AS events. Also, driver gene mutations were significantly associated with AS in SARC patients. CONCLUSIONS: Survival-related AS events may become ideal indictors for the prognosis prediction of SARCs. Corresponding splicing regulatory mechanisms are worth further exploration. 2019 Annals of Translational Medicine. All rights reserved.
BACKGROUND: Sarcomas (SARCs) are rare malignant tumors with poor prognosis. Increasing evidence has suggested that aberrant alternative splicing (AS) is strongly associated with tumor initiation and progression. We considered whether survival-related AS events might serve as prognosis predictors and underlying targeted molecules in SARC treatment. METHODS: RNA-Seq data of the SARC cohort were downloaded from The Cancer Genome Atlas (TCGA) database. Survival-related AS events were selected by univariate and multivariate Cox regression analyses. Metascape was used for constructing a gene interaction network and performing functional enrichment analysis. Then, prognosis predictors were established based on statistically significant survival-related AS events and evaluated by receiver operator characteristic (ROC) curve analysis. Finally, the potential regulatory network was analyzed via Pearson's correlation between survival-related AS events and splicing factors (SFs). RESULTS: A total of 3,610 AS events and 2,291 genes were found to be prognosis-related in 261 SARC samples. The focal adhesion pathway was identified as the most critical molecular mechanism corresponding to poor prognosis. Notably, several prognosis predictors based on survival-related AS events showed excellent performance in prognosis prediction. The area under the curve of the ROC of the risk score was 0.85 in the integrated predictor. The splicing network proved complicated regulation between prognosis-related SFs and AS events. Also, driver gene mutations were significantly associated with AS in SARC patients. CONCLUSIONS: Survival-related AS events may become ideal indictors for the prognosis prediction of SARCs. Corresponding splicing regulatory mechanisms are worth further exploration. 2019 Annals of Translational Medicine. All rights reserved.