ArticleHeliyon2024
Identification of a novel histone acetylation-related long non-coding RNA model combined with qRT-PCR experiments for prognosis and therapy in gastric cancer.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Role of histone modifications in gastric cancer (Review).International journal of oncology · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastric cancer (GC) is considered a global health crisis due to the scarcity of early diagnostic methods. Numerous studies have substantiated the involvement of histone acetylation imbalance in the progression of diverse tumor types. The potential roles of long non-coding RNA (lncRNA) in improving prognostic, predictive as well as therapeutic approaches in cancers have made it a major hotspot in recent years. Nevertheless, existent studies have never concerned the prognostic and clinical value of histone acetylation-related lncRNAs (HARlncs) in GC. Based on the aforementioned rationale, we developed a prognostic model incorporating four HARlncs-AC114730.1, AL445250.1, LINC01778, and AL163953.1-which demonstrated potential as an independent predictor of prognosis. Subsequently, GC patients were stratified into high-risk and low-risk groups. The low-risk group exhibited significantly higher overall survival (OS) compared to the high-risk group. Based on the analyses of the tumor microenvironment (TME) and immune responses, significant differences were observed between the two risk groups in terms of immune cell infiltration, immune checkpoint (ICP) expression, and other TME alterations. Furthermore, the sensitivity of GC patients to some chemotherapeutic drugs and the discrepant biological behaviors of three tumor clusters were studied in this model. In summary, we developed an effective HARlncs model with the objective of offering novel prognostic prediction methods and identifying potential therapeutic targets for GC patients.
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