Prognostic Biomarker For Gastric Cancer Research Articles

NRSN2 is a Prognostic Biomarker in Gastric Cancer and Facilitates the Growth and Migration of Gastric Cancer Cells.

Neurensin-2 (NRSN2) is reported to be associated with the progression of many tumors. This work aimed at investigating the biological function and prognostic significance of NRSN2 in gastric cancer (GC). NRSN2 expression in various cancer tissue was analyzed by the TIMER database. NRSN2 expression in GC tissue samples of different groups was analyzed by the UALCAN database. The survival analysis was performed with the Kaplan-Meier database. NRSN2 expression in GC tissues and cell lines was measured by qRT-PCR and Western blot. CCK-8, Transwell and scratch healing assays were conducted to detect the proliferative, migrative and invasive capabilities of GC cells, respectively. The LinkedOmics database and StarBase database were utilized to analyze the related genes with NRSN2 in GC. The association of NRSN2 expression with tumor immune infiltrating cells and molecular markers of immune cells was investigated with the TIMER database. NRSN2 expression was up-regulated in GC tissues, which was correlated with GC tumor grade, lymph node metastasis, and TP53 mutation. The prognosis of GC patients with high NRSN2 expression was worse than those of the patients with low NRSN2 expression. NRSN2 expression was also associated with the TNM stage, and Lauren subtype of GC patients. NRSN2 overexpression promoted the growth, migration and invasion of GC cells lines; knocking down NRSN2 worked oppositely. NRSN2 expression in GC was associated with Wnt, p53, and NOD-like receptor signaling pathways. NRSN2 expression was also significantly associated with the infiltration of CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells in the GC microenvironment. NRSN2 expression in GC tissues is up-regulated, which correlates with a poor prognosis and immune cell infiltration of GC patients. NRSN2 facilitates the growth and aggressiveness of GC cells, implying that it may be a diagnostic biomarker and therapy target for GC.

Characteristic of molecular subtype based on lysosome-associated genes reveals clinical prognosis and immune infiltration of gastric cancer.

Lysosome are involved in nutrient sensing, cell signaling, cell death, immune responses and cell metabolism, which play an important role in the initiation and development of multiple tumors. However, the biological function of lysosome in gastric cancer (GC) has not been revealed. Here, we aim to screen lysosome-associated genes and established a corresponding prognostic risk signature for GC, then explore the role and underlying mechanisms. The lysosome-associated genes (LYAGs) were obtained from MSigDB database. Differentially expressed lysosome-associated genes (DE-LYAGs) of GC were acquired based on the TCGA database and GEO database. According to expression profiles of DE-LYAGs, we divided the GC patients into different subgroups and then explored tumor microenvironment (TME) landscape and immunotherapy response in LYAG subtypes using GSVA, ESTIMATE and ssGSEA algorithms. Univariate Cox regression analysis, LASSO algorithm and multivariate Cox regression analysis were adopted to identify the prognostic LYAGs and then establish a risk model for patients with GC. The Kaplan-Meier analysis, Cox regression analysis and ROC analysis were utilized to evaluate the performance of the prognostic risk model. Clinical GC specimens were also used to verify the bioinformatics results by qRT-PCR assay. Thirteen DE-LYAGs were obtained and utilized to distinguish three subtypes in GC samples. Expression profiles of the 13 DE-LYAGs predicted prognosis, tumor-related immunological abnormalities and pathway dysregulation in these three subtypes. Furthermore, we constructed a prognostic risk model for GC based on DEG in the three subtypes. The Kaplan-Meier analysis suggested that higher risk score related to short OS rate. The Cox regression analysis and ROC analysis indicated that risk model had independent and excellent ability in predicting prognosis of GC patients. Mechanistically, a remarkable difference was observed in immune cell infiltration, immunotherapy response, somatic mutation landscape and drug sensitivity. qRT-PCR results showed that compared with corresponding adjacent normal tissues, most screened genes showed significant abnormal expressions and the expression change trends were consistent with the bioinformatics results. We established a novel signature based on LYAGs which could be served as a prognostic biomarker for GC. Our study might provide new insights into individualized prognostication and precision treatment for GC.

Evaluation of the TXNIP gene expression in gastric adenocarcinoma and its relationship with overall survival of patients

Background. Gastric Cancer (GC) is a common gastrointestinal tumor, and its incidence is increasing. The pathogenesis of GC is very complex and remains unclear. Recent basic studies of GC have focused on gene expression dysregulation. Accumulating evidence has demonstrated that thioredoxin-interacting protein (TXNIP) is abnormally expressed in a variety of malignant tumors but it is obscure in GC. This study aimed to compare the expression of the TXNIP gene in cancerous and adjacent tissue of gastric cancer and evaluate its clinical significance in the prognosis and survival analysis of gastric cancer patients. Methods. A total of 50 tumor tissues and marginal non-tumor control tissues were obtained from GC patients. Also, TXNIP gene expression levels were evaluated by real-time PCR. Meanwhile, bioinformatic approaches were used to evaluate TXNIP expression in two different cohorts of GC patients. A data mining study was also performed to determine the prognostic role of TXNIP expression in the overall survival of GC. Furthermore, a pan-cancer analysis of TXNIP expression was performed using TCGA data. Results. The TXNIP gene was down-regulated in tumor samples with a fold change of 0.33, and the same results were repeated in bioinformatics analysis. Decreased expression of TXNIP was significantly associated with metastasis, poor differentiation, and drug abuse. Our results provided evidence that TXNIP gene expression level is positively correlated with the overall survival of GC patients. Pan-cancer analysis of TCGA data revealed down-regulated TXNIP in a variety of malignant tumors. Conclusion. This study established low TXNIP expression as a prognostic biomarker in GC. It also revealed that the decrease in TXNIP expression likely favors metastatic GC. Practical Implications. Evaluation of TXNIP expression is informative in the prognosis of GC patients.

CircRNA CDR1as: a novel diagnostic and prognostic biomarker for gastric cancer

Background Circular RNA (circRNA) CDR1as is emerging as a vital tumour regulator. This study aimed to investigate its diagnostic and prognostic value and molecular mechanisms for gastric cancer (GC). Methods CDR1as expression in GC and adjacent normal tissues (n = 82), paired plasma (n = 65) and plasma exosome samples (n = 68) from GC patients and healthy controls were determined by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Correlations between CDR1as level and clinicopathological factors of GC patients were analysed. Its diagnostic and prognostic value was evaluated by receiver operating characteristic (ROC) curves and Cox regression analysis combined with Kaplan-Meier plots. CDR1as-regulated proteins and signalling pathways were identified by quantitative proteomics and bioinformatic analysis. Results CDR1as was downregulated in GC tissues and associated with tumour size and neural invasion. Plasma- and exosome-derived CDR1as was upregulated in GC patients while plasma-derived CDR1as level was related to lymphatic metastasis. Area under ROC curve (AUC) of tissue-, plasma- and exosome-derived CDR1as was 0.782, 0.641, 0.536 while combination of plasma CDR1as, serum CEA and CA19-9 increased AUC to 0.786. Distal metastasis, TNM stage and tissue-derived CDR1as level were independent predictors for overall survival (OS) of patients. MiRNA signalling networks and glycine, serine and threonine metabolism were regulated by CDR1as and HSPE1 might be a key protein. Conclusions CDR1as is a crucial regulator and promising biomarker for GC diagnosis and prognosis.

CircRNA circSLIT2 is anovel diagnostic and prognostic biomarker for gastric cancer.

Many diseases can mimic the symptoms of gastric cancer (GC). Therefore, misdiagnosis of GC is common. Our preliminary sequencing analysis revealed the altered expression of circSLIT2 in GC. In this study, we further explored the role of circSLIT2 in GC. The research subjects included GC patients, patients with irritable bowel syndrome (IBS), patients with gastric ulcer (GU), patients with gastric tuberculosis (GT), patients with Crohn's disease (CD), and healthy controls (HC). Accumulation of circSLIT2 RNA in both tissue and plasma samples was determined with RT-qPCR. The diagnostic and prognostic values of circSLIT2 for GC were explored by performing ROC and survival curve analysis. The χ2-test was applied for association analysis. Increased circSLIT2 RNA accumulation was observed in GC tissues compared to non-tumor tissues. Compared to the HC group, increased plasma circSLIT2 RNA accumulation was only observed in the GC group, but not in the IBS, GU, GT, and CD groups. Plasma circSLIT2 showed apositive correlation with circSLIT2 in GC tissues but not circSLIT2 in non-tumor tissues. Using increased plasma circSLIT2 as abiomarker, GC patients were effectively separated from other disease groups and the HC group. Survival curve analysis revealed that most patients who died during the 5‑year follow-up had high levels of circSLIT2 accumulation in GC tissues and plasma. CircSLIT2 in plasma and GC tissue was only closely associated with distant tumor metastases, but not other clinical factors. Increased circSLIT2 accumulation may serve as anovel diagnostic and prognostic biomarker for GC.

A nine-gene signature as prognostic biomarker in gastric cancer by bioinformatics analysis.

The prognosis of advanced gastric cancer (GC) remains poor. It is urgent and necessary to find suitable prognostic markers. miR-619-5p is highly expressed in GC. However, the value of miR-619-5p and its target genes as prognostic biomarkers of GC is unclear. RT-PCR was performed to verify the expression of miR-619-5p in GC cell lines and their exosomes. Western blotting and transmission electron microscope were used to identify exosomes. The target genes of miR-619-5p were predicted by RNA22 and TargetScan. The differentially expressed genes (DEGs) and prognosis-related genes (PRGs) were obtained using The Cancer Genome Atlas (TCGA) database. The DAVID database was used to analyse pathway enrichment and functional annotation of common target genes. The STRING database and Cytoscape software were used to screen key genes and visualize their functional modules. The survival analysis was conducted using TCGA and Kaplan-Meier Plotter (KMP) databases. Finally, a prognostic model was constructed on the foundation of the key genes to assess the reliability of the screening process. The expression of miR-619-5p in GC cells and their exosomes was proved to be significantly higher than that in normal cell lines. There are 129 common target genes involved in 3 pathways and 28 functional annotations. Finally, nine key target genes of GC (BRCA1, RAD51, KIF11, ERCC6L, BRIP1, TIMELESS, CDC25A, CLSPN and NCAPG2) were identified, and a prognostic model was successfully constructed with a good predictive ability. The model of 9-gene signature could effectively predict the prognosis of GC, and have great potential to be novel prognostic factors and therapeutic targets for patients with GC.

Identification and validation of anoikis-associated gene SNCG as a prognostic biomarker in gastric cancer

As a type of cell apoptosis, anoikis is caused by cells detachment from the extracellular matrix and anoikis resistance is central to cancer metastasis. Here, SNCG was identified as hub anoikis-associated gene in GC and associated with prognosis of patients with GC. To screen the hub anoikis-associated genes connected to GC, the database of Cancer Genome Atlas (TCGA) was employed. For further validating these identified genes, the Gene Expression Omnibus (GEO) dataset was applied, and Western blotting and quantitative Real-Time PCR were carried out. To Identify hub genes, we conducted the analyses of univariate Cox regression, differential expression, and weighted gene co-expression network analysis (WGCNA). According to the identified hub genes, we constructed a model of prognosis. Following complex analysis, SNCG was finally identified as hub anoikis-associated gene in GC. Indeed, K-M and receiver operating characteristic analyses suggested that the expression patterns of SNCG can be used as prognostic factors for GC survival. The expression and survival trends of SNCG were verified in the validation cohort and in vitro experimental analyses. The analysis of immune cell infiltration showed that the infiltrated immune cells varied among patients with GC and gene SNCG. Furthermore, due to the significant association of the constructed risk signature with patient age and survival, this risk signature can be used to predict the prognosis of GC. We suggest that SNCG was served as hub anoikis-associated gene in GC. Meanwhile, SNCG may have prognostic potential for overall patient survival.

Hsa_circ_0079598 acts as a potential diagnostic and prognostic biomarker for gastric cancer

Abstract Objectives The work discussed the expression level circular RNA (circRNA) hsa_circ_0079598 for gastric cancer (GC) patients as well as clinicopathological significance. Methods qRT-PCR was utilized for determining the expression level of hsa_circ_0079598 in GC cell lines, 40 GC tissue pairs and their paracancerous tissue specimens, 60 pairs of preoperative and postoperative plasma specimens of GC patients, 20 plasma specimens of patients with gastric polyps, and 60 plasma specimens of the healthy control group. Besides, the correlation with clinicopathological parameters was analyzed. Tumor indices glycan antigen 199 (CA199), glycan antigen 724 (CA724), and pepsinogen I (PGI) were combined to evaluate their auxiliary diagnostic value. The values of hsa_circ_0079598 in the prognosis of GC patients were analyzed using survival curves. Results The relative expression of hsa_circ_0079598 in the cancerous tissues of GC patients was lower than that of their paracancerous tissues (p=0.004). The relative expression of plasma hsa_circ_0079598 in GC patients was lower than that of the healthy control group (p<0.001) and patients with gastric polyps. Moreover, the relative expression of human gastric epithelial cell lines (GES-1) (p<0.05) was higher than that of hsa_circ_0079598 of HGC-27, AGS, and MGC-803 cancer cell lines in GC cell lines. The total survival time of the high-expression patient group (p=0.040) was higher than that of hsa_circ_0079598 in the low-expression patient group. The expression of hsa_circ_0079598 in patients with the tissues and plasma of GC was related to the differentiated degree of tumors and TNM staging (p<0.05). The auxiliary diagnostic value of hsa_circ_0079598 for GC was analyzed using ROC curves. When GC was distinguished from gastric polyps and the healthy control group, the areas under the ROC curve (AUCs) were 0.856 and 0.930, respectively. Hsa_circ_0079598 combined with tumor indices CA199, CA724, and PGI detection had higher specificity and accuracy than those of a single index. Conclusions Hsa_circ_0079598 was low-expression in cell lines, plasma, and GC tissues, which was related to the progress and prognosis of GC. Hsa_circ_0079598 combined with CA199, CA724, and PGI detection can improve the diagnosis of GC.

Comprehensive analysis of COMMD10 as a novel prognostic biomarker for gastric cancer.

COMMD10 has an important role in the development of certain tumors, but its relevance to gastric cancer (GC) is unclear. The purpose of this study is to investigate the difference of COMMD10 expression in gastric adenocarcinoma (STAD) and analyze the correlation between COMMD10 expression and prognosis of STAD patients. The expression levels of COMMD10 between STAD and normal tissues were explored using the The Cancer Genome Atlas (TCGA) database. In addition, the expression of COMMD10 in GC was further validated by immunohistochemistry (IHC) staining, qRT-PCR and Western blot. Dot blot experiments were used for exploring m6A expression levels in tissues with high and low COMMD10 expression. Kaplan-Meier analysis and COX regression analysis were used to explore the relationship between COMMD10 and STAD prognosis. A nomogram was constructed to predict the survival probability of STAD patients. GO and KEGG functional enrichment of COMMD10-related genes were performed. The Corrlot software package was used to analyze the correlation between COMMD10 expression levels and m6A modifications in STAD. An analysis of immune infiltration based on the CIBERSOFT and the single-sample GSEA (ssGSEA) method was performed. COMMD10 expression was significantly associated with multiple cancers, including STAD in TCGA. COMMD10 expression was elevated in STAD cancer tissues compared to paracancerous tissues. COMMD10 upregulation was associated with poorer overall survival (OS), clinical stage, N stage, and primary treatment outcome in STAD. Functional enrichment of COMMD10-related genes was mainly involved in biological processes such as RNA localization, RNA splicing, RNA transport, mRNA surveillance pathways, and spliceosomes. The dot blot experiment showed that m6A levels were higher in cancer tissues with high COMMD10 expression compared with paracancerous tissues. COMMD10 was significantly correlated with most m6A-related genes. COMMD10 was involved in STAD immune cells infiltration, correlated with macrophage cells expression. High COMMD10 expression was significantly associated with poor prognosis in STAD patients, and its functional realization was related to m6A modification. COMMD10 involved in STAD immune infiltration.

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.

Comprehensive analysis of the molecular mechanism for gastric cancer based on competitive endogenous RNA network

Objective: To explore the regulatory mechanism of competitive endogenous RNAs (ceRNA) in gastric cancer (GC) and to predict the prognosis of GC. Materials and Methods: Expression profiles of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs were obtained from The Cancer Genome Atlas platform. Differentially expressed RNAs (DERNAs) were screened to construct a lncRNA-miRNA-mRNA ceRNA network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed on the ceRNA network-related differentially expressed mRNAs (DEmRNAs). Next, the DERNAs were subjected to Cox regression and survival analyses to identify crucial prognostic factors for patients with GC. Results: We detected 1029 differentially expressed lncRNAs, 104 differentially expressed miRNAs, and 1659 DEmRNAs in patients with GC. Next, we performed bioinformatic analysis to construct the lncRNA-miRNA-mRNA ceRNA network, which included 10 miRNAs, 65 lncRNAs, and 10 mRNAs. Subsequently, KaplanMeier (K-M) analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group, and the area under the curve value of the receiver operating characteristic curve revealed that the polygenic model had good predictive ability. The results indicated that ADAMTS9-AS1, ATAD2, and CADM2 might be potential therapeutic targets and prognostic biomarkers for GC. Conclusions: Our study has implications for predicting prognosis and monitoring surveillance of GC and provides a new theoretical and experimental basis for the clinical prognosis of GC.

Identification of Potential Diagnostic and Prognostic Biomarkers for Gastric Cancer Based on Bioinformatic Analysis.

Gastric cancer (GC) ranks third for cancer-related fatalities worldwide. It is still unclear what causes GC to progress. Using integrated bioinformatics analysis, COL5A2 has been proved to be related to GC development, which may identify the likely pathogenic mechanism. Data from GC patients were gathered using The Cancer Gene Atlas (TCGA) and the gene expression omnibus (GEO). The level of COL5A2 expression was compared between paired GC and normal tissues. The differentially expressed genes (DEGs) in GC patients with high and low COL5A2 expression were identified using functional enrichment analysis to identify the signature pathways linked to the DEGs. The clinical pathologic traits connected to overall survival (OS) of GC patients were examined utilizing Cox regression and the Kaplan-Meier method. To assess the prognostic significance of COL5A2, receiver operating characteristic (ROC) curves was drawn. How the immune system infiltrate both normal gastric and GC tumor tissues was investigated. Using the human protein atlas (HPA) database, regression, and the Kaplan-Meier method, immunohistochemical analysis of DEG COL5A2 expression in GC tissues was carried out. The correlation between COL5A2 expression and the GC grouping was found to be highly significant. Functional annotations revealed that COL5A2 participates in extracellular matrix structure, collagen metabolism, and other biological processes (BPs). High COL5A2 expression was associated with poor prognostic and clinical features, such as clinical T, N, and M stages. ROC curves exhibited that COL5A2 might predict the occurrence of gastric cancer. The infiltration degree of 21 immune cell subsets, including activated dendritic cells (aDCs), CD8+ T cells, and cytotoxic cells, was found to be dramatically relevant to COL5A2. Immunohistochemical analysis indicated that the expression of COL5A2 in tumor tissues is higher than that in normal tissues. The COL5A2 gene may offer fresh perspectives on the pathogenic mechanism underlying GC, as well as potential biomarkers for estimating GC patient prognosis. As a result, COL5A2 may be a useful biomarker for predicting patient survival.

The prognostic value of NLRP1/NLRP3 and its relationship with immune infiltration in human gastric cancer.

Inflammasomes are related to tumorigenesis and immune-regulation. Here, we investigated the prognostic value of the NLR family pyrin domain containing (NLRP) 1/NLRP3 inflammasome and its potential mechanisms in immune-regulation in gastric cancer (GC). We analyzed the differential expression of NLRP1/NLRP3 between tumor and normal tissues using the Oncomine and Tumor Immune Estimate Resource (TIMER) databases. Immunohistochemistry and western blotting were used to detect NLRP1/NLRP3 protein expression in GC tissues. Correlations between NLRP1/NLRP3 expression levels and patient survival were analyzed using Kaplan-Meier survival curves. The relationships of NLRP1/NLRP3 expression and tumor-infiltrating immune cells/marker genes were assessed using the TIMER database. NLRP1/NLRP3 and immune checkpoint gene correlations were verified by single-gene co-expression analyses, and tumor immune-related pathways involving NLRP1/NLRP3 were analyzed using gene set enrichment analysis (GSEA). Elevated NLRP1/NLRP3 expression was significantly correlated with lymph node metastasis, poor survival, immune-infiltrating cell abundances, and immune cell markers. NLRP3 showed stronger correlations with immune infiltration and the prognosis of gastric cancer. NLRP1 and NLRP3 might be involved in the same tumor immune-related pathways. Thus, high NLRP1/NLRP3 expression promotes immune cell infiltration and poor prognosis in GC. NLRP1/NLRP3, particularly NLRP3, may have important roles in immune infiltration and may serve as a prognostic biomarker for GC. NLRP1/NLRP3, particularly NLRP3, may have important roles in immune infiltration and may serve as a prognostic biomarker for GC.

Comprehensive analysis to identify pseudogenes/lncRNAs-hsa-miR-200b-3p-COL5A2 network as a prognostic biomarker in gastric cancer

ObjectiveGastric cancer is one of the most common and deadly types of cancer. The molecular mechanism of gastric cancer progression remains unclear.Materials and methodsFour hub genes were identified through GEO and TCGA database screening and analysis. Prognostic analysis revealed that COL5A2 was the most likely to affect the prognosis of gastric cancer among the four hub genes. The relationships between COL5A2 and clinical variables and immune cell infiltration were analyzed. Then, COL5A2 was analyzed for single-gene differences and related functional enrichment. Using the starBase database for prediction and analysis, miRNAs and pseudogenes/lncRNAs that might combine with COL5A2 were identified; thus, the ceRNA network was constructed. Finally, the network was verified by Cox analysis and qPCR, and a nomogram was constructed.ResultsFirst, we found that COL5A2, COL12A1, BGN and THBS2 were highly expressed in gastric cancer. COL5A2 had statistical significance in overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) analysis. Immune infiltration analysis suggested that COL5A2 might influence the changes in the tumor immune microenvironment. The StarBase database was used to predict that 3 pseudogenes and 7 lncRNAs might inhibit the hsa-miR-200b-3p-COL5A2 axis in gastric cancer. The pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 ceRNA network was identified and verified using Cox regression analysis and PCR. Finally, we constructed a nomogram.ConclusionsWe elucidated the regulatory role of the pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 network in gastric cancer progression and constructed a nomogram. These studies may provide effective treatments and potential prognostic biomarkers for gastric cancer.

Expression of Karyopherin Alpha 2 and Karyopherin Beta 1 Correlate with Poor Prognosis in Gastric Cancer

Introduction: Karyopherin alpha 2 (KPNA2) and karyopherin beta 1 (KPNB1) constitute nuclear transport protein complexes involved in nuclear import and are significant in tumor progression. Although high KPNA2 expression was associated with poor prognosis in solid tumors, the relationship between KPNA2 and KPNB1 expression and their prognostic role in gastric cancer (GC) remains unclear. Methods: Immunohistochemistry was used to correlate the expression of KPNA2 and KPNB1 with various features, including clinicopathological characteristics in 130 patients with GC and survival in 94 patients with invasive lesions extending to the submucosa or deeper. Results: High expression of KPNA2 and KPNB1 was found in 25% and 36% of the patients, respectively. Both were significantly related to tumor depth, lymph node metastasis, lymphatic invasion, venous invasion, and Ki-67 expression. KPNA2 expression was significantly related to that of KPNB1 (p < 0.001). Patients with high KPNB1 expression had poorer prognosis than those with low expression (p = 0.027), as was also observed in case of KPNA2 (p < 0.001). Patients with high expression of both KPNA2 and KPNB1 accounted for 18% and had a poorer prognosis than those with high expression of either and those with low expression of both (p = 0.001). Multivariate analysis revealed that high expression of both KPNA2 and KPNB1 was an independent prognostic factor in patients with GC (hazard ratio, 3.46; 95% confidence interval, 1.64–2.73, p = 0.001). Conclusion: KPNA2 expression was correlated with KPNB1 expression, and high co-expression of KPNA2 and KPNB1 may represent a strong prognostic biomarker in GC.

ZNF521 Is Correlated with Tumor Immune Cell Infiltration and Act as a Valuable Prognostic Biomarker in Gastric Cancer.

Aim To explore the correlations between the expression of zinc finger protein 521 (ZNF521) with immune invasion and prognosis of gastric cancer. Methods Expression of ZNF521 was examined by immunohistochemistry in gastric cancer cases. Kaplan–Meier plotter was used to determine the relationships between ZNF521 and prognosis. TIMER and GEPIA were used to analyze the correlation between ZNF521 expression and gene markers of immune cell infiltration. Results The expression of ZNF521 was up-regulated in gastric cancer samples. Kaplan–Meier analysis indicated that higher expression of ZNF521 was associated with poor prognosis. The expression of ZNF521 was correlated with infiltrating levels of CD4+ T and CD8+ T cells, macrophages, neutrophils, and dendritic cells in gastric cancer, which also correlated with diverse immune marker sets. Conclusions ZNF521 is correlated significantly with immune cell infiltration and is a valuable biomarker for prognosis in gastric cancer.

Long noncoding RNA ZNFX1-AS1 promotes the invasion and proliferation of gastric cancer cells by regulating LIN28 and CAPR1N1.

BACKGROUNDLong noncoding RNA (lncRNA) ZNFX1-AS1 (ZFAS1) is a newly discovered lncRNA, but its diagnostic value in gastric cancer is unclear.AIMTo investigate the potential role of ZFAS1 in gastric cancer and to evaluate the clinical significance of ZFAS1 as a biomarker for gastric cancer screening.METHODSQuantitative real-time polymerase chain reaction (qRT-PCR) was used to screen for gastric cancer-associated lncRNAs in gastric cancer patients, gastric stromal tumor patients, gastritis or gastric ulcer patients, and healthy controls. Correlations between ZFAS1 expression and clinicopathological features were analyzed. The biological effects of ZFAS1 on the proliferation, migration, and invasion of gastric cancer cells were studied by MTT, colony formation, and transwell mi-gration assays. The potential mechanism of ZFAS1 was demonstrated using enzyme-linked immunosorbent assay and qRT-PCR. The relationship between ZFAS1 and tumorigenesis was demonstrated using in vivo tumor formation assays.RESULTSThe plasma level of lncRNA ZFAS1 was significantly higher in preoperative patients with gastric cancer than in individuals in the other 4 groups. Increased expression of ZFAS1 was significantly associated with lymph node metastasis, advanced TNM stage, and poor prognosis. ZFAS1 regulated the proliferation, migration, and invasion of gastric cancer cells and regulated the growth of gastric cancer cells in vivo. LIN28 and CAPRIN1 were identified as key downstream mediators of ZFAS1 in gastric cancer cells.CONCLUSIONLncRNA ZFAS1 promoted the invasion and proliferation of gastric cancer cells by modulating LIN28 and CAPRIN1 expression, suggesting that ZFAS1 can be used as a potential diagnostic and prognostic biomarker in gastric cancer.

Myoferlin disturbs redox equilibrium to accelerate gastric cancer migration.

ObjectiveIn contrast to normal cells, in which reactive oxygen species (ROS) are maintained in redox equilibrium, cancer cells are characterized by ectopic ROS accumulation. Myoferlin, a newly identified oncogene, has been associated with tumor metastasis, intracellular ROS production, and energy metabolism. The mechanism by which myoferlin regulates gastric cancer cell migration and ROS accumulation has not been determined.MethodsMyoferlin expression, intracellular ROS levels, the ratios of reduced to oxidized glutathione (GSH/GSSG) and nicotinamide adenine dinucleotide phosphate (NADPH/NADP+) and migratory ability were measured in gastric cancer cells in vitro and in the TCGA and GEO databases in silico.ResultsMyoferlin was found to be more highly expressed in tumor than in normal tissues of gastric cancer patients, with higher expression of Myoferlin associated with shorter survival time. Myoferlin was associated with significantly higher intracellular ROS levels and enhanced migration of gastric cancer cells. N-acetyl-L-cysteine (NAC), a potent inhibitor of ROS, inhibited Myoferlin-induced ROS accumulation and cell migration.ConclusionsMyoferlin is a candidate prognostic biomarker for gastric cancer and plays an essential role in regulating redox equilibrium and gastric cancer cell migration. Myoferlin may also be a new target for treatment of patients with gastric cancer.

Analyses of the expression and prognosis of ILDR1 in human gastric cancer

The worldwide mortality rate of gastric cancer worldwide remains high. Immunoglobulin-like domain containing receptor 1 (ILDR1) belongs to an evolutionarily conserved protein family, and little is known about this gene in gastric cancer. In this paper, we analyzed the expression of ILDR1 and its relationship with clinical outcomes in gastric cancer using publicly available databases. ONCOMINE, GEPIA2, UALCAN, Kaplan–Meier Plotter, cBioPortal, GeneMANIA and LinkedOmics databases were used to analyze the expression, prognostic values, mutations and functional networks of ILDR1 in gastric cancer. We observed that ILDR1 was overexpressed in gastric cancer than in normal tissues. ILDR1 expression was significantly higher in patients with gastric cancer than in normal controls during subgroup analysis based on cancer stage, patient’s race, sex, age, tumor grade, H. pylori infection, histological subtype, and nodal metastasis status. Survival analysis showed that upregulation of ILDR1 expression was significantly associated with poor prognosis. Genomic alterations in ILDR1 were analyzed using cBioPortal, protein–protein interaction (PPI) networks were constructed using GeneMANIA and the co-expressed genes, gene ontology, and pathways of ILDR1 were determined using the LinkedOmics web tool. ILDR1 showed significant differences in expression between gastric cancer and normal tissues and, thus, may be a promising prognostic biomarker for gastric cancer.

RPP30 is a novel diagnostic and prognostic biomarker for gastric cancer.

Objective: This study aimed to identify the hub gene in gastric cancer (GC) tumorigenesis. A biomarker prediction model was constructed and analyzed, and protein expression in histopathological samples was verified in a validation cohort. Methods: Differentially expressed genes (DEGs) were identified from GC projects in The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis of DEGs was performed between the high- and low- Ribonuclease P protein subunit p30 (RPP30) expression groups. ROC analysis was performed to assess RPP30 expression to discriminate GC from normal tissues. Functional enrichment pathways and immune infiltration of DEGs were analyzed using GSEA and ssGSEA. Survival analysis and nomogram construction were performed to predict patient survival. Immunohistochemical staining of GC tissues was performed to validate RPP30 expression in GC and paracancerous samples. Results: Gene expression data and clinical information of 380 cases (375 GC samples and 32 para-cancerous tissues) were collected from TCGA database. The AUC for RPP30 expression was found to be 0.785. The G alpha S signaling pathway was the most significantly enriched signaling pathway. Primary therapy outcome (p < 0.001, HR = 0.243, 95% CI = 0.156–0.379), age (p = 0.012, HR = 1.748, 95% CI = 1.133–2.698), and RPP30 expression (p < 0.001, HR = 2.069, 95% CI = 1.346–3.181) were identified as independent prognostic factors. As a quantitative approach, a nomogram constructed based on RPP30 expression, age, and primary therapy outcome performed well in predicting patient survival. Nineteen of the 25 tissue samples from the validation cohort showed positive RPP30 expression in GC tissues, whereas 16 cases showed negative RPP30 staining in normal tissues. The difference between the two was statistically significant. Conclusion: High RPP30 expression was significantly correlated with disease progression and poor survival in GC, promoting tumorigenesis and angiogenesis via tRNA dysregulation. This study provides new and promising insights into the molecular pathogenesis of tRNA in GC.