ArticleAging2021
Development and validation of an individual alternative splicing prognostic signature in gastric cancer.
Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Genome-Wide Analyses of Prognostic and Therapeutic Alternative Splicing Signatures in Bladder Urothelial Carcinoma.Frontiers in oncology · 2021Article
- Comprehensive Characterization of RNA Processing Factors in Gastric Cancer Identifies a Prognostic Signature for Predicting Clinical Outcomes and Therapeutic Responses.Frontiers in immunology · 2021Article
- Patient-Level DNA Damage Repair Pathway Profiles and Anti-Tumor Immunity for Gastric Cancer.Frontiers in immunology · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastric cancer (GC) is a heterogeneous disease with different clinical manifestations and prognoses. Alternative splicing (AS) is a determinant of gene expression and contributes to protein diversity from a rather limited gene transcript in metazoans. AS events are associated with different aspects of cancer biology, including cell proliferation, apoptosis, invasion, etc. Here, we present a comprehensive analysis of the prognostic AS profile in GC. GC-specific AS (GCAS) events were analyzed, and overall survival-associated GCAS (OS-GCAS) events were verified among the genome-wide AS events identified in The Cancer Genome Atlas (TCGA) database. In total, 1,287 GCAS events of 837 genes and 173 OS-GCAS events of 130 genes were identified. The parental genes of OS-GCAS events were significantly enriched in the development of GC. Protein-protein interaction (PPI) and OS-GCAS-associated splicing factor (SF) interaction networks were constructed. Multivariate Cox regression analysis with least absolute shrinkage and selection operator (LASSO) penalty was performed to establish a prognostic risk formula, representing 23 OS-GCAS events. The low-risk group had better OS than the high-risk group and lower immune and stromal scores. Cox proportional hazard regression was applied to generate an AS-clinical integrated prognostic model with a considerable area under the curve (AUC) value in both the training and validation datasets. Our study provides a profile of OS-GCAS events and an AS-clinical nomogram to predict the prognosis of GC.
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