Ferroptosis-related alternative splicing signatures as potential biomarkers for predicting prognosis and therapy response in gastric cancer

Ferroptosis is linked to various tumor biological traits, and alternative splicing (AS), a crucial step in mRNA processing, plays a role in the post-transcriptional regulation of ferroptosis-related genes (FRGs). A least absolute shrinkage and selection operator (LASSO) penalized Cox regression anal...

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Published inHeliyon Vol. 10; no. 14; p. e34381
Main Authors Long, Gang, Li, Zhiyong, Gao, Yue, Zhang, Xu, Cheng, Xiyang, Daniel, Irankunda Eric, Zhang, Lisha, Wang, Dawei, Li, Zhengtian
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 30.07.2024
Elsevier
Subjects
Alternative splicing
Ferroptosis
Gastric cancer
Prognosis
Tumor microenvironment
Alternative splicing
Ferroptosis
Prognosis
Tumor microenvironment
Gastric cancer
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Summary:Ferroptosis is linked to various tumor biological traits, and alternative splicing (AS), a crucial step in mRNA processing, plays a role in the post-transcriptional regulation of ferroptosis-related genes (FRGs). A least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis was utilized to build a prognostic signature based on 12 AS events (p < 0.05), which was validated in gastric cancer (GC) patients. The high-risk group (n = 203) showed enrichment in cancer and metastasis pathways (p < 0.05). Significant differences existed between the high- and low-risk groups in terms of tumor microenvironment (TME) cell infiltration and immune activities (p < 0.05). The low-risk group (n = 203) was characterized by immune activation and improved prognosis (p < 0.001). Additionally, targeted treatment and immunotherapy were more likely to benefit the low-risk group (p < 0.05). Correlation analysis was performed to detect related splicing factors (SF) (Cor>0.4, FDR<0.05). Furthermore, our functional assay results suggested that high SF3A2 expression might increase ferroptosis resistance and promote cell proliferation. In conclusion, the FRAs model we built has an advantage in predicting GC prognosis. The model's demonstration of variations in the immune microenvironment and drug response could potentially inform decisions regarding treatment strategies.
ISSN:2405-8440
2405-8440
DOI:10.1016/j.heliyon.2024.e34381