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Updated: Dec 11, 2025
Detection of Alternative Splicing During Epithelial-Mesenchymal Transition
Published on: October 9, 2014
Features of alternative splicing in stomach adenocarcinoma and their clinical implication: a research based on
Yuanyuan Zhang1, Shengling Ma2, Qian Niu3
1Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. u201310506@hust.edu.cn.
Background:
Alternative splicing (AS) offers a main mechanism to form protein polymorphism. A growing body of evidence indicates the correlation between splicing disorders and carcinoma. Nevertheless, an overall analysis of AS signatures in stomach adenocarcinoma (STAD) is absent and urgently needed.
Results:
2042 splicing events were confirmed as prognostic molecular events. Furthermore, the final prognostic signature constructed by 10 AS events gave good result with an area under the curve (AUC) of receiver operating characteristic (ROC) curve up to 0.902 for 5 years, showing high potency in predicting patient outcome. We built the splicing regulatory network to show the internal regulation mechanism of splicing events in STAD. QKI may play a significant part in the prognosis induced by splicing events.
Conclusions:
In our study, a high-efficiency prognostic prediction model was built for STAD patients, and the results showed that AS events could become potential prognostic biomarkers for STAD. Meanwhile, QKI may become an important target for drug design in the future.
Insights
Alternative splicing (AS) events are crucial for stomach adenocarcinoma (STAD) prognosis. A new model using 10 AS events accurately predicts patient outcomes, identifying QKI as a potential therapeutic target.
Area of Science:
- Molecular biology
- Genomics
- Cancer research
Background:
- Alternative splicing (AS) generates protein diversity and is linked to various cancers.
- Splicing dysregulation is implicated in tumorigenesis.
- A comprehensive analysis of AS signatures in stomach adenocarcinoma (STAD) was lacking.
Purpose of the Study:
- To identify and analyze alternative splicing events as prognostic biomarkers in STAD.
- To develop a predictive model for STAD patient outcomes based on AS signatures.
- To explore the role of splicing factors in STAD prognosis.
Main Methods:
- Bioinformatic analysis of AS events in STAD patient data.
- Construction of a prognostic signature using selected AS events.
- Development of a splicing regulatory network.
- Evaluation of the predictive accuracy using ROC curve analysis.
Main Results:
- Identified 2042 significant AS events with prognostic value in STAD.
- Developed a 10-AS event signature with high predictive accuracy (AUC = 0.902 at 5 years).
- Constructed a splicing regulatory network, highlighting QKI as a key factor in STAD prognosis.
Conclusions:
- Alternative splicing events serve as potent prognostic biomarkers for STAD.
- A novel, high-efficiency prognostic prediction model for STAD was developed.
- The splicing factor QKI presents a potential therapeutic target for drug development in STAD.
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