Abstract
Purpose: Alternative splicing (AS) is a post-transcriptional process that plays a significant role in enhancing the diversity of transcription and protein. Accumulating evidences have demonstrated that dysregulation of AS is associated with oncogenic processes. However, AS signature specifically in lung squamous cell carcinoma (LUSC) remains unknown. This study aimed to evaluate the prognostic values of AS events in LUSC patients.Methods: The RNA-seq data, AS events data and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis was performed to identify survival-related AS events and survival-related parent genes were subjected to Gene Ontology enrichment analysis and gene network analysis. The least absolute shrinkage and selection operator (LASSO) method and multivariate Cox regression analysis were used to construct prognostic prediction models, and their predictive values were assessed by Kaplan-Meier analysis and receiver operating characteristic (ROC) curves. Then a nomogram was established to predict the survival of LUSC patients. And the interaction network of splicing factors (SFs) and survival-related AS events was constructed by Spearman correlation analysis and visualized by Cytoscape.Results: Totally, 467 LUSC patients were included in this study and 1,991 survival-related AS events within 1,433 genes were identified. SMAD4, FOS, POLR2L, and RNPS1 were the hub genes in the gene interaction network. Eight prognostic prediction models (seven types of AS and all AS) were constructed and all exhibited high efficiency in distinguishing good or poor survival of LUSC patients. The final integrated prediction model including all types of AS events exhibited the best prognostic power with the maximum AUC values of 0.778, 0.816, 0.814 in 1, 3, 5 years ROC curves, respectively. Meanwhile, the nomogram performed well in predicting the 1-, 3-, and 5-year survival of LUSC patients. In addition, the SF-AS regulatory network uncovered a significant correlation between SFs and survival-related AS events.Conclusion: This is the first comprehensive study to analyze the role of AS events in LUSC specifically, which improves our understanding of the prognostic value of survival-related AS events for LUSC. And these survival-related AS events might serve as novel prognostic biomarkers and drug therapeutic targets for LUSC.
Highlights
Lung cancer is the leading cause of cancer-related deaths across the world, and non-small cell lung cancer (NSCLC) is the most prevalent subtype, accounting for more than 80% of all cases [1,2,3]
Alternative splicing (AS) events data were obtained from the The Cancer Genome Atlas (TCGA) SpliceSeq database, including seven types: alternate acceptor site (AA), alternate donor site (AD), alternate promoter (AP), alternate terminator (AT), exon skip (ES), mutually exclusive exons (ME), and retained intron (RI), and the intersections among these AS types were presented by the Upset plot [33]
We chose the corresponding genes of most significant survival-related AS events whose univariate regression P < 0.01 to construct gene interaction network by the Cytoscape’s Reactome FI plugin and determined top 10 hub genes according to the number of connections [35]
Summary
Lung cancer is the leading cause of cancer-related deaths across the world, and non-small cell lung cancer (NSCLC) is the most prevalent subtype, accounting for more than 80% of all cases [1,2,3]. Significant progress has been achieved in treating NSCLC, such as immunotherapy and targeted therapy, the prognosis of advanced LUSC is still poor, and the 5-year survival rate is
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