The mechanism of deleted in lymphocytic leukemia 2 (DLEU2)-long non-coding RNA in tumors has become a major point of interest in recent research related to the occurrence and development of a variety of tumors. Recent studies have shown that the long non-coding RNA DLEU2 (lncRNA-DLEU2) can cause abnormal gene or protein expression by acting on downstream targets in cancers. At present, most lncRNA-DLEU2 play the role of oncogenes in different tumors, which are mostly associated with tumor characteristics, such as proliferation, migration, invasion, and apoptosis. The data thus far show that because lncRNA-DLEU2 plays an important role in most tumors, targeting abnormal lncRNA-DLEU2 may be an effective treatment strategy for early diagnosis and improving the prognosis of patients. In this review, we integrated lncRNA-DLEU2 expression in tumors, its biological functions, molecular mechanisms, and the utility of DLEU2 as an effective diagnostic and prognostic marker of tumors. This study aimed to provide a potential direction for the diagnosis, prognosis, and treatment of tumors using lncRNA-DLEU2 as a biomarker and therapeutic target.

BackgroundGastric Cancer (GC) is a seriously heterogeneous disease, making the prognostic prediction challenging. The causal relationship between helicobacter pylori (Hp) infection and GC has been tightly entrenched by numerous epidemiological and clinical studies. Ferroptosis, a novel form of regulated cell death, is closely related to the increase and development of malignant tumors. ROS plays a key role in ferroptosis, whereas ROS produced by HP in some patients with GC also plays an important role in tumor progression. Whether the induction of ferroptosis can play a better role in the clinical treatment of GC caused by HP infection remains to be further studied. Therefore, the mRNA expression profiles and corresponding clinical data of patients with GC were downloaded from public databases. Methods Univariate Cox regression and LASSO regression were used to construct a multigene signature in the TCGA cohort. Patients with GC from the Gene Expression Omnibus (GEO) cohort were used for validation. The results showed that six differentially expressed genes (DEGs) were correlated with prognosis. Then, GSVA algorithm was used to calculate the enrichment score of each sample based on the six genes. Patients were divided into two risk groups (low and high) by the median risk score evaluated with the enrichment score and found statistically significant differences in their survival rates. ResultsA novel prognostic model integrating six ferroptosis-related and HP-related genes were firstly constructed, and a nomogram combining DEG signature with clinical features was constructed to confirm the robustness of the model for speculating about RFS in patients with GC. The receiver operating characteristic (ROC) curve, independent GEO datasets, and our experiments at the cellular level and with RNA extracted from patient tissues indicated that the signature endows a good predictive performance. The functions of this gene signature were assessed by gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis. Additionally, immune infiltration analysis, gene mutation analysis, and molecular docking were used to explore the potential mechanism of this gene signature.ConclusionsConclusively, a novel gene signature can be used for the prognostic prediction of GC. Targeting ferroptosis and HP may be a therapeutic alternative for patients with GC.