Identification of Survival-Associated Alternative Splicing Signatures in Lung Squamous Cell Carcinoma

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.

N6-Methyladenosine RNA Methylation Regulator-Related Alternative Splicing (AS) Gene Signature Predicts Non–Small Cell Lung Cancer Prognosis

“…In addition, in our current study, we constructed the risk signature using these altered genes in m6A and AS events to associate with NSCLC prognosis, and the AUC of the ROC curves showed the sensitivity and specificity of LUAD and LUSC, respectively, which are better than other recent studies (Zhao et al, 2020) (Liu et al, 2020). In these risk signatures, a previous study showed that S100A14 overexpression was able to promote LUAD cell migration and invasion (Ding et al, 2018).…”

“…Indeed, AS events is an important mRNA modification process and produce a large number of mRNA and protein isoforms with different regulatory functions (Bonnal et al, 2020;Liu et al, 2020). The prognostic value of the AS events in NSCLC has well been documented, for example, Zhao et al (2020) built a predictive model of aberrant AS events and predicated NSCLC prognosis.…”

“…In all recent studies of the AS events in NSCLC, Li et al (2017) were the first to construct an AS risk signature for the prediction of NSCLC prognosis, while Zhao et al (2020) constructed the AS risk signature stratified by gender of patients. Liu et al (2020) formed an AS signature for LUSC. Our current study also explored abnormal expression of the splicing factors in NSCLC as well as the C-index (Supplementary Table S7).…”

“…Aberrant BCL2L1, MDM2, MDM4, NUMB, and MET mRNA splicing occurred in lung cancer and altered cell apoptosis, proliferation, and cohesion (Coomer, Black). Thus, further investigation related to the abnormal GAS events to lung tumorigenesis (Coomer et al, 2019) and novel strategy for cancer targeting therapy (Frankiw et al, 2019) as well as biomarkers for various human cancers, including NSCLC (Li et al, 2017;Paschalis et al, 2018;Yang et al, 2019;Liu et al, 2020;Zhang et al, 2020a).…”

Identification of Mutator-Derived Alternative Splicing Signatures of Genomic Instability for Improving the Clinical Outcome of Cholangiocarcinoma

“…Some formula based on alternative splicing signature have been applied to quantify genomic instability degree (20). Recent studies have focused on the AS network, leading to the construction of prognostic signature models based on comprehensive AS events which suitable levels of predictivity and efficiency for carcinoma prognosis (21)(22)(23). Whether genomic instability-related AS events could effectively predict prognosis of cholangiocarcinoma remains unclear.…”