Background: Long noncoding RNAs (lncRNAs) are important regulators of gene expression and can affect a variety of physiological processes. Recent studies have shown that immune-related lncRNAs play an important role in the tumour immune microenvironment and may have potential application value in the treatment and prognosis prediction of tumour patients. Epithelial ovarian cancer (EOC) is characterized by a high incidence and poor prognosis. However, there are few studies on immune-related lncRNAs in EOC. In this study, we focused on immune-related lncRNAs associated with survival in EOC.Methods: We downloaded mRNA data for EOC patients from The Cancer Genome Atlas (TCGA) database and mRNA data for normal ovarian tissue from the Genotype-Tissue Expression (GTEx) database and identified differentially expressed genes through differential expression analysis. Immune-related lncRNAs were obtained through intersection and coexpression analysis of differential genes and immune-related genes from the Immunology Database and Analysis Portal (ImmPort). Samples in the TCGA EOC cohort were randomly divided into a training set, validation set and combination set. In the training set, Cox regression analysis and LASSO regression were performed to construct an immune-related lncRNA signature. Kaplan–Meier survival analysis, time-dependent ROC curve analysis, Cox regression analysis and principal component analysis were performed for verification in the training set, validation set and combination set. Further studies of pathways and immune cell infiltration were conducted through Gene Set Enrichment Analysis (GSEA) and the Timer data portal.Results: An immune-related lncRNA signature was identified in EOC, which was composed of six immune-related lncRNAs (KRT7-AS, USP30-AS1, AC011445.1, AP005205.2, DNM3OS and AC027348.1). The signature was used to divide patients into high-risk and low-risk groups. The overall survival of the high-risk group was lower than that of the low-risk group and was verified to be robust in both the validation set and the combination set. The signature was confirmed to be an independent prognostic biomarker. Principal component analysis showed the different distribution patterns of high-risk and low-risk groups. This signature may be related to immune cell infiltration (mainly macrophages) and differential expression of immune checkpoint-related molecules (PD-1, PDL1, etc.).Conclusions: We identified and established a prognostic signature of immune-related lncRNAs in EOC, which will be of great value in predicting the prognosis of clinical patients and may provide a new perspective for immunological research and individualized treatment in EOC.

Anti‐angiogenesis is a promising therapeutic strategy for delaying tumour progression that offers, new hope for gastric cancer targeted therapy. The purpose of this study was to investigate the precise mechanism by which Kin of IRRE‐like protein 1 (KIRREL) contributes to the development of gastric cancer, particularly in terms of tumour angiogenesis. Differential expression of KIRREL in tissues and cells was detected using quantitative real‐time polymerase chain reaction, western blotting and immunohistochemistry. A bioinformatics analysis was conducted to screen for the function and pathway enrichment of KIRREL in gastric cancer. Lentivirus‐induced KIRREL silencing in SNU‐5 cells and lentivirus‐induced KIRREL overexpression in AGS cells were used to study the effect of KIRREL on the proliferation, cell cycle and angiogenesis of gastric cancer cells. Moreover, the expressions of PI3K, P‐PI3K, AKT, P‐AKT, mTOR, P‐mTOR, HIF‐1α and VEGF were also detected. Gastric cancer tissues and cells had high levels of KIRREL expression, which is associated with the proliferation, cell cycle and angiogenesis of gastric cancer cells. After silencing and overexpressing KIRREL in SNU‐5 and AGS cells, respectively, the proliferation and angiogenesis of SNU‐5 cells were inhibited, while the proliferation and angiogenesis of AGS cells were promoted. According to a bioinformatics analysis of the KIRREL gene, angiogenesis regulation and the PI3K/AKT pathway were highly connected. The PI3K/AKT/mTOR pathway was repressed and stimulated by KIRREL silencing and overexpression, respectively. IGF‐1, an AKT agonist, and LY294002, an inhibitor, reversed the effects of KIRREL silencing and overexpression on the PI3K/AKT/mTOR pathway and on gastric cancer cell proliferation and angiogenesis. KIRREL may mediate the proliferation and angiogenesis of gastric cancer cells through the PI3K/AKT/mTOR signalling pathway. These findings could help in the further development of potential anti‐angiogenesis targets.

Gliomas are the most prevalent primary tumors in the central nervous system. Despite some breakthroughs in the treatment of glioma in recent years, survival rates remain low. Although genes of the Augmin family play a key role in microtubule nucleation, the role they play in gliomas is unclear. Transcriptome data were extracted from UCSC XENA and GTEx for low-grade glioma (LGG) and normal tissues, respectively. The protein interaction network associated with Augmin family genes was established using STRING and GeneMANIA databases. Enrichment analysis of gene-related functions and pathways was used to explore potential biological pathways and TIMER to assess immune cell infiltration. Regression analysis and Kaplan–Meier analysis were used to look at the clinical characteristics of the Augmin family genes and the association with the prognosis of patients with glioma. The results showed that the mRNA expression of Augmin family genes was significantly elevated in LGG tissues, except for HAUS7. Immunoregulation, cell cycle, apoptosis and other signaling pathways may be involved in the development and progression of LGG. Except for HAUS4 and HAUS7, the expression of all genes was positively correlated with immune cell infiltration. High expression of HAUS1, HAUS3, HAUS5, HAUS7, HAUS8 and low expression of HAUS4, HAUS6 in LGG was associated with poor prognosis. The risk models constructed based on the pivotal genes HAUS2, HAUS4 and HAUS8 were validated by nomogram and confirmed to be clinically useful for predicting the prognosis of LGG.

Background. Nomograms were established to predict the survival for gastric signet ring cell carcinoma (GSRC) in young and middle‐aged adults. Material and Methods. Eligible patients with GSRC from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and then divided into a training and a testing cohort in proportion. Independent prognostic factors were picked by univariate and multivariate Cox regression analysis to set up nomograms. The predictive effect and clinical value of nomograms were evaluated by the concordance index (C‐index), calibration curves, and receiver operating characteristic curve (ROC). Results. A total of 1686 GSRC patients were subsumed into this case for analysis, including a training (n = 1180) and a testing cohort (n = 506). Independent risk factors related to overall survival (OS) and cancer‐specific survival (CSS) comprised of race, TNM stage, tumor size, number of positive lymph nodes (PLNE), and chemotherapy. For OS, the C‐indexes of the training and testing cohorts were 0.737 and 0.752, while for CSS, C‐indexes were, respectively, 0.749 and 0.751. These revealed that nomograms accurately predicted OS and CSS. Calibration curves and ROC demonstrated the apparent superiority of nomograms. Conclusion. We built a well‐understood and comprehensive prognostic assessment model for GSRC, which provided an individualized survival prediction in the form of a quantitative score that can be considered for clinical practice.

Background: Long non-coding RNA (lncRNA), as an important regulator of gene expression, can affect a variety of physiological processes. Recent studies have shown that immune-related lncRNA play an important role in the tumor immune microenvironment and may have potential application value in the treatment and prognosis prediction of tumor patients. Epithelial ovarian cancer (EOC) is characterized by high incidence and poor prognosis. However, there are few studies on immune-related lncRNAs in EOC. In this study, we focused on the immune-related lncRNAs associated with survival in EOC. Methods: We downloaded mRNA data for EOC patients from The Cancer Genome Atlas (TCGA) database, and mRNA data for normal ovarian tissue from the Genotype-Tissue Expression (GTEx) database, and identified differential genes through differential Expression analysis. Immune-related lncRNAs were obtained through taking intersection and co-expression analysis of differential genes and immune-related genes from the Immunology Database and Analysis Portal (ImmPort). Samples in the TCGA EOC cohort were randomly divided into training set, validation set and combination set. In the training set, Cox regression analysis and LASSO regression were used to construct an immune-related lncRNA signature. Kaplan-Meier survival analysis, time-dependent ROC curve analysis, Cox regression analysis and principal component analysis were applied to verification in the training set, training set, validation set and combination set. Further studies of pathways and immune cell infiltration were conducted through Gene Set Enrichment Analysis (GESA) and the Timer data portal.Results: An immune-related lncRNA signature was identified in EOC, which was composed of six immune-related lncRNAs (KRT7-AS, USP30-AS1, AC011445.1, AP005205.2, DNM3OS and AC027348.1). The signature divided patients into high-risk and low-risk groups. The overall survival of the high-risk group was lower than that of the low-risk group, and was verified to be robust in both the training set and the combination set. This signature was identified as an independent prognostic biomarker. The signature was confirmed to be an independent prognostic biomarker. Principal component analysis showed the different distribution patterns of high-risk and low-risk groups. This signature may be related to immune cell infiltration (mainly macrophages) and differential expression of immune checkpoint-related molecules (PD-1, PDL1, etc.). Conclusions: we identified and established a prognostic signature of immune-related lncRNA in EOC, which is of great value in predicting the prognosis of clinical patients and may provide a new perspective for the immunological research and individualized treatment in EOC.