RNAs In Gastric Cancer Research Articles

Interplay of circular RNAs in gastric cancer - a systematic review

Circular RNAs (circRNAs) have gained prominence as important players in various biological processes such as gastric cancer (GC). Identification of several dysregulated circRNAs may serve as biomarkers for early diagnosis or as novel therapeutic targets. Predictive models can suggest potential new interactions and regulatory roles of circRNAs in GCs. Experimental validations of key interactions are being performed using in vitro models, confirming the significance of identified circRNA networks. The aim of this review is to highlight the important circRNAs associated with GC. On top of that an overview of the mechanistic details of the biogenesis and functionalities of the circRNAs are also presented. Furthermore, the potentialities of the circRNAs in the field of new drug discovery are deciphered.

Investigating Full-Length circRNA Transcripts to Reveal circRNAMediated Regulation of Competing Endogenous RNAs in Gastric Cancer

Background: Circular RNAs (circRNAs) play important regulatory roles in the progression of gastric cancer (GC), but the exact mechanisms governing their regulation remain incompletely understood. Prior studies typically used back-spliced junctions (BSJs) to represent a range of circRNA isoforms, overlooking the prevalence of alternative splicing (AS) events within circRNAs, which could lead to unreliable or even incorrect conclusions in subsequent analyses, hindering our comprehension of the specific functions of circRNAs in GC. Objective: This study aimed to explore the potential functional roles of the dysregulated circRNA transcripts in GC and provide new biomarkers and effective novel therapeutic strategies for GC treatment. Methods: RNA-seq data with rRNA depletion and RNase R treatment was employed to characterize the expression profiles of circRNAs in GC, and RNA-seq data only with rRNA depletion was employed to identify differentially expressed mRNAs in GC. Based on the full-sequence information and accurate isoform-level quantification of circRNA transcripts calculated by the CircAST tool, we performed a series of bioinformatic analyses. A circRNA-miRNA-hub gene regulatory network was constructed to reveal the circRNA-mediated regulation of competing endogenous RNAs in GC, and then the protein-protein interaction (PPI) network was built to identify hub genes. Results: A total of 18,398 circular transcripts were successfully reconstructed in the samples. Herein, 351 upregulated and 177 downregulated circRNA transcripts were identified. Functional enrichment analysis revealed that their parental genes were strongly associated with GC. After several screening steps, 19 dysregulated circRNA transcripts, 40 related miRNAs, and 65 target genes (mRNAs) were selected to construct the ceRNA network. Through PPI analysis, five hub genes (COL5A2, PDGFRB, SPARC, COL1A2, and COL4A1) were excavated. All these hub genes may play vital roles in gastric cancer cell proliferation and invasion. Conclusion: Our study revealed a comprehensive profile of full-length circRNA transcripts in GC, which could provide potential prognostic biomarkers and targets for GC treatment. The results would be helpful for further studies on the biological roles of circRNAs in GC and offer new mechanistic insights into the pathogenesis of GC.

Prognostic signature and immune landscape of 5-methylcytosine-related long non-coding RNAs in gastric cancer

BackgroundLong non-coding RNAs (lncRNAs) have been demonstrated to be useful in assessing the prognosis of cancer patients. However, few studies have focused on 5-methylcytosine-related lncRNAs (m5C-lncRNAs) in gastric cancer (GC). In this study, we aimed to establish a m5C-lncRNAs prognostic signature (m5C-LPS) and explore its potential impact on guiding clinical practice for GC. MethodsRNA-sequence and clinicopathological data were retrieved from The Cancer Genome Atlas (TCGA) database, while the coexpression of long non-coding RNAs (lncRNAs) was determined using Pearson's correlation analysis. A m5C-LPS model was constructed using univariate and Lasso Cox regression, and its prognostic value and accuracy were subsequently validated. Subsequently, the expression of 11 m5C-lncRNAs was verified via quantitative real-time PCR (qRT-PCR) in gastric cancer (GC) cell lines. The potential biological mechanism of this signature was elucidated using Gene Set Enrichment Analysis (GSEA). Based on the GSEA findings, CIBERSORT and ESTIMATE algorithms were utilized to conduct a comprehensive investigation of the tumor immune microenvironment (TIME) in GC. Additionally, pRRophetic and TIDE algorithms were employed to predict drug sensitivity and the efficacy of immunotherapy for GC patients. Results280 lncRNAs were identified as m5C-lncRNAs, including RHPN1-AS1, AC093752.3, TSC22D1-AS1, AL391152.1, MAGI2-AS3, AC048382.2, AL033527.3, AC007405.2, AC036103.1, CCDC183-AS1, and ADORA2A-AS1. Their prognostic value was validated, and the expression of these 11 lncRNAs was confirmed in four gastric cancer cell lines using quantitative reverse transcription PCR (qRT-PCR). A nomogram incorporating a risk score was developed to provide more precise clinical decision-making. Gene Set Enrichment Analysis (GSEA) showed that many classical signaling pathways related to tumor progression were enriched in this signature. Analyses related to immunity and drug sensitivity demonstrated distinct differences in features between high-risk and low-risk subgroups. ConclusionThe m5C-LPS can predict the survival of gastric cancer (GC) patients, provide novel therapeutic targets, and thus offer more thoughtful perspectives for future clinical decisions regarding GC.

Construction of prognostic markers for gastric cancer and comprehensive analysis of pyroptosis-related long non-coding RNAs.

China's most frequent malignancy is gastric cancer (GC), which has a very poor survival rate, and the survival rate for patients with advanced GC is dismal. Pyroptosis has been connected to the genesis and development of cancer. The function of pyroptosis-related long non-coding RNAs (PRLs) in GC, on the other hand, remains uncertain. To explore the construction and comprehensive analysis of the prognostic characteristics of long non-coding RNA (lncRNA) related to pyroptosis in GC patients. The TCGA database provided us with 352 stomach adenocarcinoma samples, and we obtained 28 pyroptotic genes from the Reactome database. We examined the correlation between lncRNAs and pyroptosis using the Pearson correlation coefficient. Prognosis-related PRLs were identified through univariate Cox analysis. A predictive signature was constructed using stepwise Cox regression analysis, and its reliability and independence were assessed. To facilitate clinical application, a nomogram was created based on this signature. we analyzed differences in immune cell infiltration, immune function, and checkpoints between the high-risk group (HRG) and low-risk group (LRG). Five hundred and twenty-three PRLs were screened from all lncRNAs (absolute correlation coefficient > 0.4, P < 0.05). Nine PRLs were included in the risk prediction signature that was created through stepwise Cox regression analysis. We determined the risk score for GC patients and employed the median value as the dividing line between HRG and LRG. The ability of the risk signature to predict the overall survival (OS) of GC is demonstrated by the Kaplan-Meier analysis, risk curve, receiver operating characteristic curve, and decision curve analysis curve. The risk signature was shown to be an independent prognostic factor for OS in both univariate and multivariate Cox regression analyses. HRG showed a more efficient local immune response or modulation compared to LRG, as indicated by the predicted signal pathway analysis and examination of immune cell infiltration, function, and checkpoints (P < 0.05). In general, we have created a brand-new prognostic signature using PRLs, which may provide ideas for immunotherapy in patients with GC.

The Circular RNA Circ_0043947 Promoted Gastric Cancer Progression by Sponging miR-384 to Regulate CREB1 Expression.

: The occurrence and development of circular RNAs in gastric cancer (GC) has attracted increasing attention. This study focused on investigating the biological role and molecular mechanism of circ_0043947 in GC. : The expression levels of circ_0043947, miR-384 and CAMP response element binding protein (CREB1) were determined by quantitative real-time polymerase chain reaction or Western blotting. Cell proliferation, migration, and invasion, the cell cycle and apoptosis were determined using a cell counting kit-8 assay, 5-ethynyl-2'-deoxyuridine assay, colony formation assay, wound healing assay, transwell assay, and flow cytometry assay. The interaction between miR-384 and circ_0043947 or CREB1 was verified by dual-luciferase reporter assay and RNA pull-down assay. The in vivo assay was conducted using a xenograft mouse model. : Circ_0043947 and CREB1 expression levels were significantly upregulated, whereas miR-384 expression levels were downregulated in GC tissues and cells. Functionally, knockdown of circ_0043947 inhibited cell proliferation, migration and invasion and induced G0/G1 phase arrest and apoptosis in vitro. Circ_0043947 could upregulate CREB1 expression by directly sponging miR-384. Rescue experiments showed that a miR-384 inhibitor significantly reversed the inhibitory effect of si-circ_0043947 on GC progression, and CREB1 overexpression significantly reversed the inhibitory effect of miR-384 mimics on the progression of GC cells. Furthermore, silencing of circ_0043947 inhibited tumor growth in vivo. : Circ_0043947 acted as an oncogenic factor in GC to mediate GC cell proliferation, migration, and invasion, the cell cycle and apoptosis by regulating the miR-384/CREB1 axis. Circ_0043947 may be a potential target for GC diagnosis and therapy.

Transcription Analysis of the THBS2 Gene through Regulation by Potential Noncoding Diagnostic Biomarkers and Oncogenes of Gastric Cancer in the ECM-Receptor Interaction Signaling Pathway: Integrated System Biology and Experimental Investigation.

Gastric cancer (GC) is the second most frequent cause of cancer-related death worldwide and the fourth most common malignancy. Despite significant improvements in patient survival over the past few decades, the prognosis for patients with GC remains dismal because of the high recurrence rate. In this comprehensive system biology and experimental investigation, we aimed to find new novel diagnostic biomarkers of GC through a regulatory RNA interaction network. Gene expression, coexpression, and survival analyses were performed using microarray and RNAseq datasets (analyzed by RStudio, GEPIA2, and ENCORI). RNA interaction analysis was performed using miRWalk and ENCORI online databases. Gene set enrichment analysis (GSEA) was performed to find related signaling pathways of up- and downregulated genes in the microarray dataset. Gene ontology and pathway enrichment analysis were performed by the enrichr database. Protein interaction analysis was performed by STRING online database. Validation of expression and coexpression analyses was performed using a qRT-PCR experiment. Based on bioinformatics analyses, THBS2 (FC: 7.14, FDR < 0.0001) has a significantly high expression in GC samples. lncRNAs BAIAP2-AS1, TSIX, and LINC01215 have RNA interaction with THBS2. BAIAP2-AS1 (FC: 1.44, FDR: 0.018), TSIX (FC: 1.34, FDR: 0.038), and LINC01215 (FC: 1.19, FDR: 0.046) have significant upregulation in GC samples. THBS2 has a significant role in the regulation of the ECM-receptor signaling pathway. miR-4677-5p has a significant RNA interaction with THBS2. The expression level of THBS2, BAIAP2-AS1, TSIX, and LINC01215 has a nonsignificant negative correlation with the survival rate of GC patients (HR: 0.28, logrank p: 0.28). qRT-PCR experiment validates mentioned bioinformatics expression analyses. BAIAP2-AS1 (AUC: 0.7136, p value: 0.0096), TSIX (AUC: 0.7456, p value: 0.0029), and LINC01215 (AUC: 0.7872, p value: 0.0005) could be acceptable diagnostic biomarkers of GC. BAIAP2-AS1, lncRNA LINC01215, lncRNA TSIX, and miR-4677-5p might modulate the ECM-receptor signaling pathway via regulation of THBS2 expression level, as the high-expressed noncoding RNAs in GC. Furthermore, mentioned lncRNAs could be considered potential diagnostic biomarkers of GC.

Regulatory mechanism and promising clinical application of exosomal circular RNA in gastric cancer

Gastric cancer (GC) is one of the most common malignancies worldwide and the leading cause of cancer-related deaths. Exosomes are nanoscale extracellular vesicles secreted by a variety of cells and play an important role in cellular communication and epigenetics by transporting bioactive substances in the tumor microenvironment (TME). Circular RNA (circRNA) is a type of non-coding RNA (ncRNA) with a specific structure, which is widely enriched in exosomes and is involved in various pathophysiological processes mediated by exosomes. Exosomal circRNAs play a critical role in the development of GC by regulating epithelial-mesenchymal transition (EMT), angiogenesis, proliferation, invasion, migration, and metastasis of GC. Given the biological characteristics of exosomal circRNAs, they have more significant diagnostic sensitivity and specificity in the clinic and may become biomarkers for GC diagnosis and prognosis. In this review, we briefly describe the biogenesis of exosomes and circRNAs and their biological functions, comprehensively summarize the mechanisms of exosomal circRNAs in the development of GC and chemotherapy resistance, and finally, we discuss the potential clinical application value and challenges of exosomal circRNAs in GC.

N6-methyladenosine modification of OIP5-AS1 promotes glycolysis, tumorigenesis, and metastasis of gastric cancer by inhibiting Trim21-mediated hnRNPA1 ubiquitination and degradation

BackgroundOpa-interacting protein 5 antisense transcript 1 (OIP5-AS1) has been demonstrated to play vital roles in development and progression of tumors such as gastric cancer (GC). However, the detailed molecular mechanism of OIP5-AS1 has not been completely elucidated. Our study aimed to investigate the role and the epigenetic regulation mechanism of OIP5-AS1 in GC.MethodsOIP5-AS1 expression in GC tissues was detected by RT-qPCR. Loss- and gain-of-function experiments were conducted to assess the biological function of OIP5-AS1 in vitro and in vivo. The interaction of OIP5-AS1 with insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) or heterogeneous nuclear nucleoprotein A1 (hnRNPA1) was verified by bioinformatics analysis, RNA pull-down assays, and RNA immunoprecipitation assays.ResultsIn this study, we identified that OIP5-AS1 is specifically overexpressed in GC tumor tissues and cell lines and correlated with a poor prognosis. The loss of OIP5-AS1 suppressed the proliferation, migration, invasion, epithelial–mesenchymal transition (EMT), and glycolysis of GC cells, but the ectopic expression of OIP5-AS1 had the opposite impact. Meanwhile, knockdown of OIP5-AS1 inhibited tumor growth in patient-derived xenograft models, as well as repressed tumor metastasis. Mechanistically, IGF2BP3 could bind to OIP5-AS1 by N6-methyladenosine (m6A) modification sites on OIP5-AS1, thereby stabilizing OIP5-AS1. Moreover, OIP5-AS1 prevented Trim21-mediated ubiquitination and degradation of hnRNPA1, stabilizing hnRNPA1 protein and promoting the malignant progression of GC by regulating PKM2 signaling pathway.ConclusionsIn conclusion, this study highlighted that OIP5-AS1 is an oncogenic m6A-modified long non-coding RNA (lncRNA) in GC and that IGF2BP3/OIP5-AS1/hnRNPA1 axis may provide a potential diagnostic or prognostic target for GC.

Long Noncoding RNA ACTA2-AS1 Inhibits Cell Growth and Facilitates Apoptosis in Gastric Cancer by Binding with miR-6720-5p to Regulate ESRRB.

Gastric cancer (GC) is a common malignant tumor, posing a great threat to human's health and life. Previous studies have suggested aberrant expression of long non-coding RNAs (lncRNAs) in GC. This study elucidated the effects of lncRNA ACTA2-AS1 on the biological characteristics of GC. Gene expression in stomach adenocarcinoma (STAD) samples compared with normal tissues and the correlation between gene expression and prognosis of STAD patients were analyzed using bioinformatic tools. Gene expression at protein and mRNA levels in GC and normal cells was tested by western blotting and RT-qPCR. The subcellular localization of ACTA2-AS1 in AGS and HGC27 cells was identified by nuclear-cytoplasmic fractionation and FISH assay. EdU, CCK-8, flow cytometry analysis, TUNEL staining assays were conducted to evaluate the role of ACTA2-AS1 and ESRRB on GC cellular behaviors. The binding relationship among ACTA2-AS1, miR-6720-5p and ESRRB was verified by RNA pulldown, luciferase reporter assay and RIP assay. LncRNA ACTA2-AS1 was underexpressed in GC tissues and cell lines. ACTA2-AS1 elevation suppressed GC cell proliferation and induced apoptosis. Mechanistically, ACTA2-AS1 directly bound to miR-6720-5p and subsequently promoted the expression of target gene ESRRB in GC cells. Furthermore, ESRRB knockdown reversed the influence of ACTA2-AS1 overexpression on GC proliferation and apoptosis. ACTA2-AS1 plays an antioncogenic role in GC via binding with miR-6720-5p to regulate ESRRB expression.

Comprehensive analysis of circular RNA-associated competing endogenous RNA networks and immune infiltration in gastric cancer

BackgroundCircular RNA (circRNA) has been proved to be an important regulator of gastric cancer (GC). However, the role and regulatory mechanism of circrna related competitive endogenous RNA (ceRNA) in GC have not been established. MethodsCircRNA data and clinical data were obtained from the GEO and TCGA databases. The ceRNA networks were constructed and a function enrichment analysis was completed. Additionally, correlations between hub genes expression, immune cell infiltration, and clinical phenotypes were determined. The differentially expressed circRNAs and their downstream microRNAs (miRNAs) were validated by quantitative real-time polymerase chain reaction, and the hub genes were validated by western blot analysis. The migration and invasion ability of overexpressed hsa_circ_0002504 was determined by a transwell assay. ResultsThe ceRNA network contained 2 circRNAs, 3 miRNAs, and 55 messenger RNAs (mRNAs). 323 biological processes terms, 53 cellular components terms, 51 molecular functions terms, and 4 signaling pathways were revealed by the function enrichment analysis. The GSEA analysis revealed that the hub genes were positively correlated with the axon guidance and adhesion molecules pathways. The correlation analysis revealed that overexpressed EPHA4 and KCNA1 indicated poor tissue differentiation and were associated with clinically advanced stages of GC. The in vitro experiments showed that hsa_circ_0002504 was significantly down-regulated in GC cell lines. In addition, the overexpression of hsa_circ_0002504 led to a significant downregulation of hsa-miR-615-5p and hsa-miR-767-5p, as well as an upregulation of EPHA4, KCNA1, and NCAM1. Furthermore, it suppressed the migration and invasion ability of GC cells. ConclusionsHsa_circ_0002504 is a potential diagnostic biomarker for GC. High expression of EPHA4 and KCNA1 may indicate poor prognosis.

Prognosis and Immunotherapy Prediction Based on Immunogenic Cell Death-related lncRNA in Gastric Cancer

Gastric cancer (GC) is one of the most common malignancies, but research on it is still limited. The role of immuntonic cell death (ICD)-associated long non-coding RNA (lncRNA) in GC is still unclear. Therefore, this experiment aimed to investigate the role of ICD-related lncRNA in GC, its prognostic value, and immunotherapeutic potential.

CD44 is a prognostic biomarker and correlated with immune infiltrates in gastric cancer

ObjectiveGastric carcinoma is the most common malignant tumour of the human digestive system worldwide. CD44 serves as a marker for several tumour stem cells, including gastric cancer. However, the prognostic value of CD44 and its correlation with immune infiltration in gastric cancer remain unclear.MethodsThe relative expression level of CD44 RNA in gastric cancer was analysed in the TCGA and GEPIA2 databases and validated in the GEO database. Differences in CD44 between gastric cancer cell lines and normal cells were detected by real-time PCR, and the HPA database was used to analyse the differential expression of CD44 protein in gastric cancer and normal tissues. The effect of CD44 on the proliferation and migration of gastric cancer cells was detected by CCK8 and transwell assays. UALCAN was used to analyse the relationship between CD44 expression and clinical parameters, and the Kaplan‒Meier Plotter was used to evaluate the prognostic value, including overall survival (OS), progression-free survival (PFS) and post-progression survival (PPS). The CD44 gene and protein interaction network was constructed by using the Linked Omics, GeneMANIA, STRING and DisGeNET databases. GO and KEGG analyses and GSEA of CD44 were performed by using R language. The correlation between CD44 and immune infiltration was explored by using the TIMER, CIBERSORT and GEPIA databases.ResultsCD44 is highly expressed in gastric cancer compared with normal tissues. Inhibition of proliferation and migration of gastric cancer cells after CD44 knockdown was observed. The UALCAN database showed that CD44 was independent of sex in gastric cancer but correlated with cancer stage and lymph node metastasis. Kaplan‒Meier Plotter online analysis showed that OS, PFS and PPS were prolonged in the CD44 low-expression group. GO and KEGG analyses and GSEA results showed that CD44 was mainly located in the endoplasmic reticulum and the extracellular matrix containing collagen, which was mainly involved in protein digestion and absorption. TIMER, CIBERSORT and GEPIA showed that CD44 was associated with infiltrating immune cells and thereby affected survival prognosis.ConclusionCD44 is highly expressed in gastric cancer and is an independent prognostic factor associated with immune invasion, which can be used as a candidate prognostic biomarker to determine the prognosis associated with gastric immune invasion.

Network analysis reveals that the tumor suppressor lncRNA GAS5 acts as a double-edged sword in response to DNA damage in gastric cancer

The lncRNA GAS5 acts as a tumor suppressor and is downregulated in gastric cancer (GC). In contrast, E2F1, an important transcription factor and tumor promoter, directly inhibits miR-34c expression in GC cell lines. Furthermore, in the corresponding GC cell lines, lncRNA GAS5 directly targets E2F1. However, lncRNA GAS5 and miR-34c remain to be studied in conjunction with GC. Here, we present a dynamic Boolean network to classify gene regulation between these two non-coding RNAs (ncRNAs) in GC. This is the first study to show that lncRNA GAS5 can positively regulate miR-34c in GC through a previously unknown molecular pathway coupling lncRNA/miRNA. We compared our network to several in-vivo/in-vitro experiments and obtained an excellent agreement. We revealed that lncRNA GAS5 regulates miR-34c by targeting E2F1. Additionally, we found that lncRNA GAS5, independently of p53, inhibits GC proliferation through the ATM/p38 MAPK signaling pathway. Accordingly, our results support that E2F1 is an engaging target of drug development in tumor growth and aggressive proliferation of GC, and favorable results can be achieved through tumor suppressor lncRNA GAS5/miR-34c axis in GC. Thus, our findings unlock a new avenue for GC treatment in response to DNA damage by these ncRNAs.

Regulation of autophagy by non-coding RNAs in gastric cancer.

Autophagy is a conserved cellular self-digesting process that degrades obsoleting proteins and cellular components and plays a crucial role in the tumorigenesis, metastasis, and drug resistance of various tumors such as gastric cancer (GC). As a hotspot in molecular biology, non-coding RNAs (ncRNAs) are involved in the regulation of multiple biological processes, such as autophagy. Increasing evidence indicate that various ncRNAs exert double roles in the initiation and progression of GC, either serve as oncogenes or tumor suppressors. Recent studies have shown that some ncRNAs could modulate autophagy activity in GC cells, which would affect the malignant transformation and drug resistance. Whether the function of ncRNAs in GC is dependent on autophagy is undefined. Therefore, identifying the underlying moleculr targets of ncRNAs in autophagy pathways and the role of ncRNA-regulated autophagy in GC could develop new treatment interventions for this disease. This review summarizes the autophagy process and its role in GC, and the regulatory mechanisms of ncRNAs, as well as focuses on the dual role of ncRNAs-mediated autophagy in GC, for the development of potential therapeutic strategies in GC patients.

Identification of m6A-related long non-coding RNAs for predicting prognosis and immune characterizations in gastric cancer

Background: N6-methyladenosine (m6A) mRNA modification triggers malignant behavior in tumor cells, which promotes malignant progression and migration of gastric cancer (GC). Nevertheless, studies on the prognostic value of m6A-related long non-coding RNA (MRlncRNA) in GC remain quite restricted. The study aimed to develop a reasonable predictive model to explore the prognostic potential of MRlncRNAs in predicting the prognosis of GC patients and monitoring the efficacy of immunotherapy. Methods: Transcriptomic and clinical data for GC were derived from TCGA. Next, univariate Cox, LASSO and multivariate Cox regression analyses were next used to identify prognostic MRlncRNAs, calculate risk scores and build risk assessment models. The predictive power of the risk models was then validated by Kaplan-Meier analysis, ROC curves, DCA, C-index, and nomogram. We attempted to effectively differentiate between groups in terms of immune cell infiltration status, ICI-related genes, immunotherapy responses, and common anti-tumor drug sensitivity. Results: A risk model based on 11 MRlncRNAs was developed with an AUC of 0.850, and the sensitivity and specificity of this model in predicting survival probability is satisfactory. The Kaplan-Meier analysis revealed that the low-risk group in the model had a significantly higher survival rate, and the model was highly associated with survival status, clinical features, and clinical stage. Furthermore, the model was verified to be an independent prognostic risk factor, and the low-risk group in the model had a remarkable positive correlation with a variety of immune cell infiltrates. The expression levels of ICI-related genes differed significantly between the different groups. Lastly, immunotherapy responses and common anti-tumor drug sensitivity also differed significantly between different groups. Conclusion: The risk model on the basis of 11-MRlncRNAs can serve as independent predictors of GC prognosis and may be useful in developing personalized treatment strategies for patients.

Construction and validation of a novel prognostic model using the cellular senescence-associated long non-coding RNA in gastric cancer: a biological analysis

BackgroundThe onset and progression of many cancers, including gastric cancer (GC), are strongly influenced by cell senescence. Numerous studies have demonstrated that long non-coding RNA (lncRNA) impacts cell senescence, thus affecting cancer progression. However, it is not possible to develop a relevant predictive model for GC owing to the absence of a cell senescence-linked lncRNA. Since lncRNAs are linked to cellular senescence, the goal of this work was to create a prognostic signature for stomach adenocarcinoma (STAD) patients utilizing these lncRNAs.MethodsThrough the Pearson correlation, variance, and univariate Cox regression analyses, the cellular senescence lncRNAs that were related to the disease prognosis could be successfully identified. Using the least absolute shrinkage and selection operator (LASSO) regression algorithm, a predictive model that utilized the 11 cellular senescence-linked lncRNAs was constructed. Kaplan-Meier (KM) survival and the receiver operating characteristic (ROC) curve analyses, were employed for assessing the prognostic performance of the proposed model. In addition, ESTIMATE analysis of the low- and high-risk subtypes for the infiltration of various immune cells was carried out. Additionally, the CIBERSORT algorithm was utilized for investigating the infiltration status of numerous immune cells in both groups, while the expression of the immune checkpoint genes in the two groups, was also determined.ResultsIn this study, a new prognostic model was constructed using 11 cellular senescence-related lncRNAs. The findings revealed that the OS status of the patients in the low-risk group (category) was significantly higher compared to the high-risk category (P<0.001). The 1-year ROC-area under the curve (AUC) values for the risk score in the training group was 0.714, while the AUC value for the test and comprehensive groups were recorded to be 0.666 and 0.695, respectively, which were obviously due to stage, grade, age, etc. And based on univariate [hazard ratio (HR): 1.435; P<0.001; 95% confidence interval (CI): 1.295–1.589] and multivariate analyses (P<0.001; 95% CI: HR: 1.387; 1.247–1.543), it was noted that risk scores were effectively employed as a patient-independent prognostic factor.ConclusionsTaken together, these results suggest that cellular senescence-related lncRNAs are likely to be valuable prognostic markers for GC. They also reflect the situation of the STAD immune microenvironment and may provide direction for future GC treatment.

Identification of the KCNQ1OT1/ miR-378a-3p/ RBMS1 Axis as a Novel Prognostic Biomarker Associated With Immune Cell Infiltration in Gastric Cancer.

Background: Gastric cancer (GC) is the second leading cause of cancer-related mortality and the fifth most common cancer worldwide. However, the underlying mechanisms of competitive endogenous RNAs (ceRNAs) in GC are unclear. This study aimed to construct a ceRNA regulation network in correlation with prognosis and explore a prognostic model associated with GC. Methods: In this study, 1,040 cases of GC were obtained from TCGA and GEO datasets. To identify potential prognostic signature associated with GC, Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression were employed. The prognostic value of the signature was validated in the GEO84437 training set, GEO84437 test set, GEO15459 set, and TCGA-STAD. Based on the public databases, TargetScan and starBase, an mRNA-miRNA-lncRNA regulatory network was constructed, and hub genes were identified using the CytoHubba plugin. Furthermore, the clinical outcomes, immune cell infiltration, genetic variants, methylation, and somatic copy number alteration (sCNA) associated with the ceRNA network were derived using bioinformatics methods. Results: A total of 234 prognostic genes were identified. GO and GSEA revealed that the biological pathways and modules related to immune response and fibroblasts were considerably enriched in GC. A nomogram was generated to provide accurate prognostic outcomes and individualized risk estimates, which were validated in the training, test dataset, and two independent validation datasets. Thereafter, an mRNA-miRNA-lncRNA regulatory network containing 4 mRNAs, 22 miRNAs, 201 lncRNAs was constructed. The KCNQ1OT1/hsa-miR-378a-3p/RBMS1 ceRNA network associated with the prognosis was obtained by hub gene analysis and correlation analysis. Importantly, we found that the KCNQ1OT1/miR-378a-3p/RBMS1 axis may play a vital role in the diagnosis and prognosis of GC patients based on Cox regression analyses. Furthermore, our findings demonstrated that mutations and sCNA of the KCNQ1OT1/miR-378a-3p/RBMS1 axis were associated with increased immune infiltration, while the abnormal upregulation of the axis was primarily a result of hypomethylation. Conclusion: Our findings suggest that the KCNQ1OT1/miR-378a-3p/RBMS1 axis may be a potential prognostic biomarker and therapeutic target for GC. Moreover, such findings provide insights into the molecular mechanisms of GC pathogenesis.

An Updated Review on the Therapeutic, Diagnostic, and Prognostic Value of Long Non-Coding RNAs in Gastric Cancer.

As a novel group of non-coding RNAs, long non-coding RNA (lncRNAs) can substantially regulate various biological processes. Downregulated tumor-suppressive lncRNAs and upregulated oncogenic lncRNAs (onco-lncRNAs) have been implicated in gastric cancer (GC) development. These dysregulations have been associated with decreased chemosensitivity, inhibited apoptosis, and increased tumor migration in GC. Besides, growing evidence indicates that lncRNAs can be a valuable diagnostic and prognostic biomarker, and their expression levels are substantially associated with the clinicopathological features of affected patients. The current study aims to review the recent findings of the tumor-suppressive lncRNAs and onco-lncRNAs in GC development and highlight their therapeutic, diagnostic, and prognostic values in treating GC cells. Besides, it intends to highlight the future direction of lncRNAs in treating GC.

A new risk model based on a 11-m6A-related lncRNA signature for predicting prognosis and monitoring immunotherapy for gastric cancer

ObjectiveN6-methyladenosine (m6A) mRNA modification triggers malignant behaviors of tumor cells and thereby drives malignant progression in gastric cancer (GC). However, data regarding the prognostic values of m6A RNA methylation-related long non-coding RNAs (lncRNAs) in GC are very limited in the literature. We aimed to investigate the prognostic potential of m6A-related lncRNAs in predicting prognosis and monitoring immunotherapy efficacy in GC patients.MethodsTranscriptome and clinical data were obtained from GC biopsies from Cancer Genome Atlas (TCGA). M6A-related lncRNAs associated with GC were identified by constructing a co-expression network, and the gene pairs differentially expressed in GC were selected using univariate analysis. We constructed a risk model based on prognosis-related lncRNA pairs selected using the LASSO algorithm and quantified the best cutoff by comparing the area under the curve (AUC) for risk stratification. A risk model with the optimal discrimination between high- and low-risk GC patients was established. Its feasibility for overall survival prediction and discrimination of clinicopathological features, tumor-infiltrating immune cells, and biomarkers of immune checkpoint inhibitors between high- and low-risk groups were assessed.ResultsFinally, we identified 11 m6A-related lncRNA pairs associated with GC prognosis based on transcriptome analysis of 375 GC specimens and 32 normal tissues. A risk model was constructed with an AUC of 0.8790. We stratified GC patients into high- and low-risk groups at a cutoff of 1.442. As expected, patients in the low-risk group had longer overall survival versus the high-risk group. Infiltration of cancer-associated fibroblasts, endothelial cells, macrophages, particularly M2 macrophages, and monocytes was more severe in high-risk patients than low-risk individuals, who exhibited high CD4+ Th1 cell infiltration in GC. Altered expressions of immune-related genes were observed in both groups. PD-1 and LAG3 expressions were found higher in low-risk patients than high-risk patients. Immunotherapy, either single or combined use of PD-1 or CTLA4 inhibitors, had better efficacy in low-risk patients than high-risk patients.ConclusionThe new risk model based on a 11-m6A-related lncRNA signature can serve as an independent predictor for GC prognosis prediction and may aid in the development of personalized immunotherapy strategies for patients.

Long Non-Coding RNA in Gastric Cancer: Mechanisms and Clinical Implications for Drug Resistance.

Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide, with high recurrence and mortality rate. Chemotherapy, including 5-fluorouracil (5-FU), adriamycin (ADR), vincristine (VCR), paclitaxel (PTX), and platinum drugs, remains one of the fundamental methods of GC treatment and has efficiently improved patients’ prognosis. However, most patients eventually develop resistance to chemotherapeutic agents, leading to the failure of clinical treatment and patients’ death. Recent studies suggest that long non-coding RNAs (lncRNAs) are involved in the drug resistance of GC by modulating the expression of drug resistance-related genes via sponging microRNAs (miRNAs). Moreover, lncRNAs also play crucial roles in GC drug resistance via a variety of mechanisms, such as the regulation of the oncogenic signaling pathways, inhibition of apoptosis, induction of autophagy, modulation of cancer stem cells (CSCs), and promotion of the epithelial-to-mesenchymal transition (EMT) process. Some of lncRNAs exhibit great potential as diagnostic and prognostic biomarkers, as well as therapeutic targets for GC patients. Therefore, understanding the role of lncRNAs and their mechanisms in GC drug resistance may provide us with novel insights for developing strategies for individual diagnosis and therapy. In this review, we summarize the recent findings on the mechanisms underlying GC drug resistance regulated by lncRNAs. We also discuss the potential clinical applications of lncRNAs as biomarkers and therapeutic targets in GC.