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Updated: Jan 20, 2026
Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
Published on: June 24, 2021
Determining the prognostic significance of alternative splicing events in soft tissue sarcoma using data from The
Xia Yang1, Wen-Ting Huang1, Rong-Quan He2
1Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.
Background:
Surgery, adjuvant chemotherapy, and radiotherapy are the primary treatment options for soft tissue sarcomas (STSs). However, identifying ways to improve the prognosis of patients with STS remains a considerable challenge. Evidence shows that the dysregulation of alternative splicing (AS) events is involved in tumor pathogenesis and progression. The present study objective was to identify survival-associated AS events that could serve as prognostic biomarkers and potentially serve as tumor-selective STS drug targets.
Methods:
STS-specific 'percent spliced in' (PSI) values for splicing events in 206 STS samples were downloaded from The Cancer Genome Atlas SpliceSeq® database. Prognostic analyses were performed on seven types of AS events to determine their prognostic value in STS patients, for which prediction models were constructed with the risk score formula [Formula: see text]. Prediction models were also constructed to determine the prognostic value of AS events, and Spearman's rank correlation coefficients were calculated to determine the degree of correlation between splicing factor expression and the PSI values.
Results:
A total 10,439 events were found to significantly correlate with patient survival rates. The area under the time-dependent receiver operating characteristic curve for the prognostic predictor of STS overall survival was 0.826. Notably, the splicing events of certain STS key genes were significantly associated with STS 2-year overall survival in the present study, including exon skip (ES) events in MDM2 and EWSR1, alternate terminator events in CDKN2A and HMGA2 for dedifferentiated liposarcoma, ES in MDM2 and alternate promoter events in CDKN2A for leiomyosarcoma, and ES in EWSR1 for undifferentiated pleomorphic sarcoma. Moreover, splicing correlation networks between AS events and splicing factors revealed that almost all of the AS events showed negatively correlations with the expression of splicing factors.
Conclusion:
An in-depth analysis of alternative RNA splicing could provide new insights into the mechanisms of STS oncogenesis and the potential for novel approaches to this type of cancer therapy.
Insights
Alternative splicing events significantly impact soft tissue sarcoma (STS) patient survival. Identifying these alternative splicing (AS) events can lead to new prognostic biomarkers and potential drug targets for STS.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Soft tissue sarcomas (STSs) present treatment challenges, with limited options for improving patient prognosis.
- Alternative splicing (AS) dysregulation is implicated in tumor pathogenesis and progression.
- Identifying survival-associated AS events is crucial for developing novel therapeutic strategies.
Purpose of the Study:
- To identify survival-associated alternative splicing (AS) events in soft tissue sarcomas (STSs).
- To evaluate AS events as potential prognostic biomarkers for STS.
- To explore AS events as potential tumor-selective drug targets for STS.
Main Methods:
- Downloaded STS-specific 'percent spliced in' (PSI) values for splicing events from The Cancer Genome Atlas SpliceSeq database for 206 STS samples.
- Performed prognostic analyses on seven types of AS events to determine their prognostic value, constructing prediction models with a risk score formula.
- Calculated Spearman's rank correlation coefficients to assess the relationship between splicing factor expression and PSI values.
Main Results:
- Identified 10,439 splicing events significantly correlating with patient survival rates, with a high predictive accuracy (AUC=0.826) for overall survival.
- Found significant associations between specific AS events in key STS genes (e.g., MDM2, EWSR1, CDKN2A, HMGA2) and 2-year overall survival.
- Revealed predominantly negative correlations between AS events and splicing factor expression through splicing correlation network analysis.
Conclusions:
- Alternative RNA splicing analysis offers novel insights into STS oncogenesis mechanisms.
- Survival-associated AS events represent promising prognostic biomarkers and potential therapeutic targets for soft tissue sarcomas.
- Further investigation into AS could pave the way for innovative cancer therapies.
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