Comprehensive Analysis of Differentially Expressed lncRNAs in Gastric Cancer

Construction of a three-component regulatory network of transcribed ultraconserved regions for the identification of prognostic biomarkers in gastric cancer

Altered expression and functional roles of the transcribed ultraconserved regions (T-UCRs), as genomic sequences with 100% conservation between the genomes of human, mouse, and rat, in the pathophysiology of neoplasms has already been investigated. Nevertheless, the relevance of the functions for T-UCRs in gastric cancer (GC) is still the subject of inquiry. In the current study, we first used a genome-wide profiling approach to analyze the expression of T-UCRs in GC patients. Then, we constructed a three-component regulatory network and investigated potential diagnostic and prognostic values of the T-UCRs. The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) dataset was used as a resource for the RNA-sequencing data. FeatureCounts was utilized to quantify the number of reads mapped to each T-UCR. Differential expression analysis was then conducted using DESeq2. In the following, interactions between T-UCRs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were combined into a three-component network. Enrichment analyses were performed and a protein-protein interaction (PPI) network was constructed. The R Survival package was utilized to identify survival-related significantly differentially expressed T-UCRs (DET-UCRs). Using an in-house cohort of GC tissues, expression of two DET-UCRs was furthermore experimentally verified. Our results showed that several T-UCRs were dysregulated in TCGA-STAD tumoral samples compared to nontumoral counterparts. The three-component network was constructed which composed of DET-UCRs, miRNAs, and mRNAs nodes. Functional enrichment and PPI network analyses revealed important enriched signaling pathways and gene ontologies such as "pathway in cancer" and regulation of cell proliferation and apoptosis. Five T-UCRs were significantly correlated with the overall survival of GC patients. While no expression of uc.232 was observed in our in-house cohort of GC tissues, uc.343 showed an increased expression, although not statistically significant, in gastric tumoral tissues. The constructed three-component regulatory network of T-UCRs in GC presents a comprehensive understanding of the underlying gene expression regulation processes involved in tumor development and can serve as a basis to investigate potential prognostic biomarkers and therapeutic targets.

Identification and validation of a novel angiogenesis-related gene signature for predicting prognosis in gastric adenocarcinoma

Background

Angiogenesis is a major promotor of tumor progression and metastasis in gastric adenocarcinoma (STAD). We aimed to develop a novel lncRNA gene signature by identifying angiogenesis-related genes to better predict prognosis in STAD patients.

Methods

The expression profiles of angiogenesis-related mRNA and lncRNA genes were collected from The Cancer Genome Atlas (TCGA). Then, the "limma" package was used to identify differentially expressed genes (DEGs). The expression profiles of angiogenesis-related genes were clustered by consumusclusterplus. The Pearson correlation coefficient was further used to identify lncRNAs coexpressed with angiogenesis-related clustere genes. We used Lasso Cox regression analysis to construct the angiogenesis-related lncRNAs signature. Furthermore, the diagnostic accuracy of the prognostic risk signature were validated by the TCGA training set, internal test sets and external test set. We used multifactor Cox analysis to determine that the risk score is an independent prognostic factor different from clinical characteristics. Nomogram has been used to quantitatively determine personal risk in a clinical environment. The ssGSEA method or GSE176307 data were used to evaluate the infiltration state of immune cells or predictive ability for the benefit of immunotherapy by angiogenesis-related lncRNAs signature. Finally, the expression and function of these signature genes were explored by RT-PCR and colony formation assays.

Results

Among angiogenesis-related genes clusters, the stable number of clusters was 2. A total of 289 DEGs were identified and 116 lncRNAs were screened to have a significant coexpression relationship with angiogenic DEGs (P value<0.001 and |R| >0.5). A six-gene signature comprising LINC01579, LINC01094, RP11.497E19.1, AC093850.2, RP11.613D13.8, and RP11.384P7.7 was constructed by Lasso Cox regression analysis. The multifactor Cox analysis and Nomogram results showed that our angiogenesis-related lncRNAs signature has good predictive ability for some different clinical factors. For immune, angiogenesis-related lncRNAs signature had the ability to efficiently predict infiltration state of 23 immune cells and immunotherapy. The qPCR analysis showed that the expression levels of the six lncRNA signature genes were all higher in gastric adenocarcinoma tissues than in adjacent tissues. The functional experiment results indicated that downregulation of the expression of these six lncRNA signature genes suppressed the proliferation of ASG and MKN45 cells.

Conclusion

Six angiogenesis-related genes were identified and integrated into a novel risk signature that can effectively assess prognosis and provide potential therapeutic targets for STAD patients.

Long non-coding RNAs as potential biomarkers or therapeutic targets in gastric cancer

Aim

This study aimed to find lncRNAs and mRNAs that were expressed differently by combining microarray datasets from different studies. This was done to find important target genes in gastric cancer for anti-cancer therapy.

Background

Gastric cancer (GC) is the fourth most frequent and second-most deadly malignancy worldwide. Thus, genetic diagnosis and treatment should focus on genetic and epigenetic variables. Based on several studies, disordered expression of non-coding RNAs (ncRNAs), such as lncRNAs, regulate gastric cancer invasion and metastasis. Besides, lncRNAs cooperatively regulate gene expression and GC progression.

Methods

We obtained differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) from three GC tissue microarray datasets by meta-analysis and screened genes using the "Limma" package. Then, using the RNAInter database, we allocated DEmRNAs to each DElncRNA. ClusterProfiler and GOplot programs were used to analyze function enrichment pathways and gene ontologies for final DEmRNAs.

Results

A total of 9 differentially expressed lncRNAs (DElncRNAs) (5 up-regulated and 4 down-regulated), and 856 DEmRNAs (451 up-regulated and 405 down-regulated) between tumor and adjacent normal samples were found. Finally, 117 differentially expressed mRNAs were predicted as interactors of six DElncRNAs (H19, WT1-AS, EMX2OS, HOTAIR, ZEB1-AS1, and LINC00261).

Conclusion

In order to promote cancer therapeutics and give knowledge on the process of carcinogenesis, our study projected a network of drug-gene interactions for discovered genes and presented relevant prospective biomarkers for the prognosis of patients with stomach cancer.

Overexpression of long noncoding RNA LINC00638 inhibits inflammation and oxidative stress in rheumatoid arthritis fibroblast-like synoviocytes by regulating the Nrf2/HO-1 pathway

Background

Abnormal expression of long noncoding RNAs (lncRNAs) is involved in several autoimmune diseases including rheumatoid arthritis (RA). In this study, we intended to explore the expression of lncRNA LINC00638 in RA and its potential mechanism of action related to inflammation and oxidative stress.

Methods

The level of LINC00638 in the peripheral blood mononuclear cells (PBMCs) obtained from 45 RA patients and 30 normal controls was analyzed and its correlation with clinical indicators was investigated. In vitro, we used tumor necrosis factor‐α to stimulate fibroblast‐like synoviocytes (FLS) of RA patients for cell based experiments. Subsequently, the overexpressed plasmid and small interfering RNA of LINC00638 were designed. Furthermore, we further analyzed the potential effects of LINC00638 on the proliferation and migration of RA‐FLS and the nuclear factor erythrocyte derived 2 related factor 2 (Nrf2)/heme oxygenase 1 (HO‐1) pathway.

Results

LINC00638 expression was found to be significantly decreased in PBMCs of RA patients, and it was negatively correlated with erythrocyte sedimentation rate, interleukin (IL)‐17, reactive oxygen species (ROS), and disease activity scores for 28 joints (DAS28). Overexpression of LINC00638 activated the Nrf2/HO‐1 pathway, markedly decreased the expressions of IL‐6, IL‐17, IL‐23, ROS, as well as malondialdehyde, increased the total antioxidant capacity, and attenuated the proliferation and migration of RA‐FLS, while silencing of LINC00638 reversed these manifestations.

Conclusions

LINC00638 was found to be expressed at low levels in RA patients and was associated with immune inflammation, oxidative stress, and disease activity. Overexpression of LINC00638 can reduce the proliferation as well as migration of RA‐FLS, and activate the Nrf2/HO‐1 pathway to inhibit the inflammation and oxidative stress.

Construction and validation of a prognostic risk model of angiogenesis factors in skin cutaneous melanoma

Melanoma can secrete tumor angiogenesis factors, which is the essential factor for tumor growth and metastasis. However, there are few reports on the relationship between angiogenesis factors and prognosis risk in melanoma. This study aimed to develop a prognostic risk model of angiogenesis for melanoma. Forty-nine differentially expressed angiogenesis were identified from the TCGA database, which were mainly involved in PI3K/Akt pathway, focal adhesion, and MAPK signaling pathway. We then establish an eleven-gene signature. The model indicated a strong prognostic capability in both the discovery cohort and the validation cohort. Patients of smaller height (<170 cm) and lower weight (<80 kg) and those with advanced-stage and ulcerated melanoma had higher risk scores. The risk score was positively correlated with mutation load, homologous recombination defect, neoantigen load and chromosome instability. In addition, the high-risk group had a higher degree of immune cell infiltration, better response to immunotherapy and lower immune score. Therefore, these results indicate that the risk model is an effective method to predict the prognosis of melanoma.

LncRNA DLGAP1-AS2 overexpression associates with gastric tumorigenesis: a promising diagnostic and therapeutic target

BACKGROUND

Aberrant expression of long noncoding RNAs (lncRNAs) is associated with the progression of human cancers, including gastric cancer (GC). The function of lncRNA DLGAP1-AS2, as a promising oncogene, has been identified in several human cancers. Therefore, this study was aimed to explore the association of DLGAP1-AS2 with gastric tumorigenesis, as well.

METHODS AND RESULTS

The expression level of DLGAP1-AS2 was initially pre-evaluated in GC datasets from Gene Expression Omnibus (GEO). Moreover, qRT-PCR experiment was performed on 25 GC and 25 adjacent normal tissue samples. The Cancer Genome Atlas (TCGA) data were also analyzed for further validation. Consistent with data obtained from GEO datasets, qRT-PCR results revealed that DLGAP1-AS2 was significantly (p < 0.0032) upregulated in GC specimens compared to normal samples, which was additionally confirmed using TCGA analysis (p < 0.0001). DLGAP1-AS2 expression level was also correlated with age (p = 0.0008), lymphatic and vascular invasion (p = 0.0415) in internal samples as well as poor survival of GC patients (p = 0.00074) in GEO datasets. Also, Gene Ontology analysis illustrated that DLGAP1-AS2 may be involved in the cellular process, including hippo signaling, regulated by YAP1, as its valid downstream target, in GC samples. Moreover, ROC curve analysis showed the high accuracy of the DLGAP1-AS2 expression pattern as a diagnostic biomarker for GC.

CONCLUSION

Our findings indicated that DLGAP1-AS2 might display oncogenic properties through gastric tumorigenesis and could be suggested as a therapeutic, diagnostic, and prognostic target.

Long non-coding RNAs: Biogenesis, functions, and clinical significance in gastric cancer

Gastric cancer (GC) is one of the most prevalent malignant tumor types and the third leading cause of cancer-related death worldwide. Its morbidity and mortality are very high due to a lack of understanding about its pathogenesis and the slow development of novel therapeutic strategies. Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs with a length of more than 200 nt. They play crucial roles in a wide spectrum of physiological and pathological processes by regulating the expression of genes involved in proliferation, differentiation, apoptosis, cell cycle, invasion, metastasis, DNA damage, and carcinogenesis. The aberrant expression of lncRNAs has been found in various cancer types. A growing amount of evidence demonstrates that lncRNAs are involved in many aspects of GC pathogenesis, including its occurrence, metastasis, and recurrence, indicating their potential role as novel biomarkers in the diagnosis, prognosis, and therapeutic targets of GC. This review systematically summarizes the biogenesis, biological properties, and functions of lncRNAs and highlights their critical role and clinical significance in GC. This information may contribute to the development of better diagnostics and treatments for GC.

lncRNAs as Hallmarks for Individualized Treatment of Gastric Cancer

Gastric cancer is global cancer with a high mortality rate. A growing number of studies have found the abnormal expression of lncRNA (long noncoding RNA) in many tumors, which plays a role in promoting or inhibiting cancer. Similarly, lncRNA abnormal expression plays an essential biological function in gastric cancer. This article focuses on lncRNA involvement in the development of gastric cancer in terms of cell cycle disorder, apoptosis inhibition, metabolic remodeling, promotion of tumor inflammation, immune escape, induction of angiogenesis, and epithelial mesenchymal transition (EMT). The involvement of lncRNA in the development of gastric cancer is related to drug resistance, such as cisplatin and multi-drug resistance. It can also be used as a potential marker for the diagnosis and prognosis of gastric cancer and a target for the treatment. With an in-depth understanding of the mechanism of lncRNA in gastric cancer, new ideas for personalized treatment of gastric cancer are expected.

GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest

Predicting disease-related long non-coding RNAs (lncRNAs) is beneficial to finding of new biomarkers for prevention, diagnosis and treatment of complex human diseases. In this paper, we proposed a machine learning techniques-based classification approach to identify disease-related lncRNAs by graph auto-encoder (GAE) and random forest (RF) (GAERF). First, we combined the relationship of lncRNA, miRNA and disease into a heterogeneous network. Then, low-dimensional representation vectors of nodes were learned from the network by GAE, which reduce the dimension and heterogeneity of biological data. Taking these feature vectors as input, we trained a RF classifier to predict new lncRNA-disease associations (LDAs). Related experiment results show that the proposed method for the representation of lncRNA-disease characterizes them accurately. GAERF achieves superior performance owing to the ensemble learning method, outperforming other methods significantly. Moreover, case studies further demonstrated that GAERF is an effective method to predict LDAs.