Abstract
Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.
Highlights
Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs
Whole-genome analysis of alternative splicing (AS) events in lung carcinoma (LC) has resulted in the identification of several candidate splicing factors, which might act as therapeutic targets of LUAD, and help in disease prognosis of patients via the construction of gene signatures [13, 14], demonstrating the role of AS in LC
Analyzing the link between stromal‐ or immune‐scores and prognosis of LUAD patients To assess the impact of the microenvironment on tumor cells regarding the evolution of genomic changes, the immune- and stromal-scores for the outcomes of the expression of mRNA were evaluated by using the ESTIMATE algorithm in the R program [25]
Summary
Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. A better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Whole-genome analysis of AS events in LC has resulted in the identification of several candidate splicing factors, which might act as therapeutic targets of LUAD, and help in disease prognosis of patients via the construction of gene signatures [13, 14], demonstrating the role of AS in LC. The prognosis of cancer patients is known to be directly related to the immune cell count in the TME, which can act as a useful prognostic marker [20,21,22]. Except for some preliminary studies on LC-related AS events [13, 14] and immunological microenvironment [23, 24], there is a lack of sufficient data on the immunological relevance of AS events
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