Abstract
Alternative splicing (AS) is fundamental to transcriptome and proteome richness, and data from recent studies suggested a critical association between AS and oncogenic processes. To date, no systematic analysis has been conducted on AS from the perspective of different sexes and subtypes in non-small-cell lung cancer (NSCLC). Thus, we integrated the information of NSCLC patients from The Cancer Genome Atlas (TCGA) and evaluated AS profiles from the perspectives of sex and subtype. Eventually, a total of 813 and 1020 AS events were found to be significantly related to the overall survival (OS) of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients. Four prognostic prediction models performed well at 1, 3, and 5 years, with an area under the receiver operating characteristic (ROC) curve (AUC) greater than 0.75. Notably, we explored the upstream splicing factors (SFs) and downstream regulatory mechanisms of the OS-associated AS events and verified four differentially expressed alternative splicing (DEAS) events via qPCR. These findings can provide important guidance for subsequent studies. In addition, we also constructed nomograms to facilitate early screening by clinicians and to determine patient outcomes in NSCLC.
Highlights
Worldwide, lung cancer remains the leading cause of cancer morbidity and mortality, and it was estimated that there were 2.1 million new lung cancer patients and 1.8 million deaths in 2018 [1]
We found that a number of alternative splicing (AS) events showed significant differences after distinguishing sex, and differentially expressed alternative splicing (DEAS) events in the female group were more common than those in the male group in lung adenocarcinoma (LUAD), while the opposite trend was observed in lung squamous cell carcinoma (LUSC)
Gathering diverse biomarkers and establishing a model is an effective way to predict tumor prognosis compared to using a single clinical indicator
Summary
Lung cancer remains the leading cause of cancer morbidity and mortality, and it was estimated that there were 2.1 million new lung cancer patients and 1.8 million deaths in 2018 [1]. Different transcriptions of the same gene could produce proteins with different structures, and increasing evidence has revealed that proteins generated by multiple alternative splicing (AS) play key roles in carcinogenesis (including limitless replication, tissue invasion and metastasis, sustained angiogenesis, and avoidance of immune destruction) [3,4,5,6,7] In recent decades, many breakthroughs have been made in the field of AS, which has attracted much attention for its clinical potential in cancer therapy [8,9,10]. Four powerful prognostic models and a splicing factor (SF)AS network were constructed to reveal the mechanism of AS events affecting the prognosis of NSCLC. We established a nomogram model to help clinicians detect early relapses and assess patient prognosis. This work has great guiding significance for experimental exploration and clinical research
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