Immune Infiltration In Gastric Cancer Research Articles

Bioinformatic Analysis and Experimental Validation of HMGA2-AS1 as a Prognostic Biomarker Associated with Immune Infiltration in Gastric Cancer.

Natural antisense long noncoding RNAs (lncRNAs) have the ability to modulate the expression of their corresponding sense genes. Consequently, any dysregulation of these lncRNAs can contribute to the development of pathological processes. The ambiguity surrounding the role of HMGA2-AS1 in gastric cancer (GC) requires further investigation. The aim of this study was to examine the involvement of HMGA2-AS1 in GC. The Kaplan-Meier method, Cox regression analysis, gene set enrichment analysis (GSEA), and immune infiltration analysis were used in this study. These methods were used to evaluate the relationship between clinical characteristics and HMGA2-AS1 expression, prognostic factors, and the significant functional impact of HMGA2-AS1. HMGA2-AS1 levels in GC cell lines were validated using quantitative real-time polymerase chain reaction (qRT-PCR). In patients diagnosed with GC, a significant correlation was observed between high expression of HMGA2-AS1 and the T stage (p = 0.01). Furthermore, the high expression of HMGA2- AS1 was identified as a prognostic indicator for poorer OS (p = 0.004), PFS (p = 0.006), and DSS (p = 0.011). Furthermore, the expression of HMGA2-AS1 (p < 0.001) demonstrated an independent association with OS in patients with GC. The presence of a low expression phenotype of HMGA2-AS1 was associated with differential enrichment of various pathways, including the focal adhesion-PI3K-Akt-mTOR signaling pathway, focal adhesion, ECM glycoproteins, MET promoting cell motility, among others. Furthermore, the expression of HMGA2-AS1 exhibited correlations with B cells, CD56 bright cells, and TFH and Th17 cells. Furthermore, GC cell lines demonstrated significantly higher expression of HMGA2-AS1. Elevated expression of HMGA2-AS1 in GC patients exhibited a significant correlation with unfavorable survival outcomes and increased immune infiltration. This suggests that HMGA2- AS1 holds promise as a potential prognostic biomarker and target for immunotherapy in GC.

Construction of an immune-related gene signature for overall survival prediction and immune infiltration in gastric cancer.

Treatment options for patients with gastric cancer (GC) continue to improve, but the overall prognosis is poor. The use of PD-1 inhibitors has also brought benefits to patients with advanced GC and has gradually become the new standard treatment option at present, and there is an urgent need to identify valuable biomarkers to classify patients with different characteristics into subgroups. To determined the effects of differentially expressed immune-related genes (DEIRGs) on the development, prognosis, tumor microenvironment (TME), and treatment response among GC patients with the expectation of providing new biomarkers for personalized treatment of GC populations. Gene expression data and clinical pathologic information were downloaded from The Cancer Genome Atlas (TCGA), and immune-related genes (IRGs) were searched from ImmPort. DEIRGs were extracted from the intersection of the differentially-expressed genes (DEGs) and IRGs lists. The enrichment pathways of key genes were obtained by analyzing the Kyoto Encyclopedia of Genes and Genomes (KEGGs) and Gene Ontology (GO) databases. To identify genes associated with prognosis, a tumor risk score model based on DEIRGs was constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression. The tumor risk score was divided into high- and low-risk groups. The entire cohort was randomly divided into a 2:1 training cohort and a test cohort for internal validation to assess the feasibility of the risk model. The infiltration of immune cells was obtained using 'CIBERSORT,' and the infiltration of immune subgroups in high- and low-risk groups was analyzed. The GC immune score data were obtained and the difference in immune scores between the two groups was analyzed. We collected 412 GC and 36 adjacent tissue samples, and identified 3627 DEGs and 1311 IRGs. A total of 482 DEIRGs were obtained. GO analysis showed that DEIRGs were mainly distributed in immunoglobulin complexes, receptor ligand activity, and signaling receptor activators. KEGG pathway analysis showed that the top three DEIRGs enrichment types were cytokine-cytokine receptors, neuroactive ligand receptor interactions, and viral protein interactions. We ultimately obtained an immune-related signature based on 10 genes, including 9 risk genes (LCN1, LEAP2, TMSB15A mRNA, DEFB126, PI15, IGHD3-16, IGLV3-22, CGB5, and GLP2R) and 1 protective gene (LGR6). Kaplan-Meier survival analysis, receiver operating characteristic curve analysis, and risk curves confirmed that the risk model had good predictive ability. Multivariate COX analysis showed that age, stage, and risk score were independent prognostic factors for patients with GC. Meanwhile, patients in the low-risk group had higher tumor mutation burden and immunophenotype, which can be used to predict the immune checkpoint inhibitor response. Both cytotoxic T lymphocyte antigen4+ and programmed death 1+ patients with lower risk scores were more sensitive to immunotherapy. In this study a new prognostic model consisting of 10 DEIRGs was constructed based on the TME. By providing risk factor analysis and prognostic information, our risk model can provide new directions for immunotherapy in GC patients.

Prediction and verification of the prognostic biomarker SLC2A2 and its association with immune infiltration in gastric cancer.

Gastric cancer (GC) is the fifth most common cause of cancer-associated deaths; however, its treatment options are limited. Despite clinical improvements, chemotherapy resistance and metastasis are major challenges in improving the prognosis and quality of life of patients with GC. Therefore, effective prognostic biomarkers and targets associated with immunological interventions need to be identified. Solute carrier family 2 member 2 (SLC2A2) may serve a role in tumor development and invasion. The present study aimed to evaluate SLC2A2 as a prospective prognostic marker and chemotherapeutic target for GC. SLC2A2 expression in several types of cancer and GC was analyzed using online databases, and the effects of SLC2A2 expression on survival prognosis in GC were investigated. Clinicopathological parameters were examined to explore the association between SLC2A2 expression and overall survival (OS). Associations between SLC2A2 expression and immune infiltration, immune checkpoints and IC50 were estimated using quantification of the tumor immune contexture from human RNA-seq data, the Tumor Immune Estimation Resource 2.0 database and the Genomics of Drug Sensitivity in Cancer database. Differential SLC2A2 expression and the predictive value were validated using the Human Protein Atlas, Gene Expression Omnibus, immunohistochemistry and reverse transcription-quantitative PCR. SLC2A2 expression was downregulated in most types of tumor but upregulated in GC. Functional enrichment analysis revealed an association between SLC2A2 expression and lipid metabolism and the tumor immune microenvironment. According to Gene Ontology term functional enrichment analysis, SLC2A2-related differentially expressed genes were enriched predominantly in 'chylomicron assembly', 'plasma lipoprotein particle assembly', 'high-density lipoprotein particle', 'chylomicron', 'triglyceride-rich plasma lipoprotein particle', 'very-low-density lipoprotein particle'. 'intermembrane lipid transfer activity', 'lipoprotein particle receptor binding', 'cholesterol transporter activity' and 'intermembrane cholesterol transfer activity'. In addition, 'cholesterol metabolism', and 'fat digestion and absorption' were significantly enriched in the Kyoto Encyclopedia of Genes and Genomes pathway analysis. Patients with GC with high SLC2A2 expression had higher levels of neutrophil and M2 macrophage infiltration and a significant inverse correlation was observed between SLC2A2 expression and MYC targets, tumor mutation burden, microsatellite instability and immune checkpoints. Furthermore, patients with high SLC2A2 expression had worse prognosis, including OS, disease-specific survival and progression-free interval. Multivariate regression analysis demonstrated that SLC2A2 could independently prognosticate GC and the nomogram model showed favorable performance for survival prediction. SLC2A2 may be a prospective prognostic marker for GC. The prediction model may improve the prognosis of patients with GC in clinical practice, and SLC2A2 may serve as a novel therapeutic target to provide immunotherapy plans for GC.

LUM as a novel prognostic marker and its correlation with immune infiltration in gastric cancer: a study based on immunohistochemical analysis and bioinformatics

BackgroundGastric cancer (GC) is considered the sixth highly prevailing malignant neoplasm and is ranked third in terms of cancer mortality rates. To enable an early and efficient diagnosis of GC, it is important to detect the fundamental processes involved in the oncogenesis and progression of gastric malignancy. The understanding of molecular signaling pathways can facilitate the development of more effective therapeutic strategies for GC patients.MethodsThe screening of genes that exhibited differential expression in early and advanced GC was performed utilizing the Gene Expression Omnibus databases (GSE3438). Based on this, the protein and protein interaction network was constructed to screen for hub genes. The resulting list of hub genes was evaluated with bioinformatic analysis and selected genes were validated the protein expression by immunohistochemistry (IHC). Finally, a competing endogenous RNA network of GC was constructed.ResultsThe three genes (ITGB1, LUM, and COL5A2) overexpressed in both early and advanced GC were identified for the first time. Their upregulation has been linked with worse overall survival (OS) time in patients with GC. Only LUM was identified as an independent risk factor for OS among GC patients by means of additional analysis. IHC results demonstrated that the expression of LUM protein was increased in GC tissue, and was positively associated with the pathological T stage. LUM expression can effectively differentiate tumorous tissue from normal tissue (area under the curve = 0.743). The area under 1-, 3-, and 5-year survival relative operating characteristics were greater than 0.6. Biological function enrichment analyses suggested that the genes related to LUM expression were involved in extracellular matrix development-related pathways and enriched in several cancer-related pathways. LUM affects the infiltration degree of cells linked to the immune system in the tumor microenvironment. In GC progression, the AC117386.2/hsa-miR-378c/LUM regulatory axis was also identified.ConclusionCollectively, a thorough bioinformatics analysis was carried out and an AC117386.2/hsa-miR-378c/LUM regulatory axis in the stomach adenocarcinoma dataset was detected. These findings should serve as a guide for future experimental investigations and warrant confirmation from larger studies.

Comprehensive analysis of tertiary lymphoid structures-related genes for prognostic prediction, molecular subtypes and immune infiltration in gastric cancer.

Gastric cancer (GC) is a highly heterogeneous malignancy and survival rates of advanced GC patients are unsatisfactory. Tertiary lymphoid structures (TLS) are recently identified as lymphoid-like structures that are directly related to tumor prognosis and immune response. However, the association of tertiary lymphoid structures-related genes (TLS-RGs) with prognosis and immune response in GC remains unclear. In our study, a comprehensive analysis of the role of TLS-RGs in GC was performed based on public data, and the difference of TLS-RGs expression, TLS-RGs mutation frequency, pathway enrichment, differentially expressed gene, immune landscape, immunotherapy and drug sensitivity was analyzed. We found that TLS-RGs were altered in GC in terms of expression and mutation. The difference of survival, immune landscape and enrichment pathway exists between TLS clusters. Immune checkpoint differences were also evident between gene clusters. The grouping by TLS score indicated that patients in the low TLS score group had a better prognosis and a lower degree of immune escape. For immunotherapy, the low TLS score group showed better outcomes than the high TLS score group. Sensitivity to chemotherapeutic agents differed between TLS score groups. In conclusion, we comprehensively analyzed the role of TLS-RGs in GC, constructed nomogram that can accurately predict the prognosis of GC patients, and the TLS score can reflect the immune landscape of patients, providing the possibility of personalized design of immunotherapy and targeted drug therapy for GC patients.

COL8A1 is a prognostic-related biomarker and correlated with immune infiltration in gastric cancer

BackgroundGastric cancer (GC) ranks as the fifth most prevalent malignancy and stands as the third principal contributor to cancer-related fatalities globally. COL8A1 (collagen type VIII, alpha-1) emerges as a pivotal regulator of tumor progression, but whether COL8A1 drives immune infiltration in GC remains elusive. The aim of our investigation is to elucidate the correlation between COL8A1 and the prognosis as well as immune infiltration in gastric cancer. MethodsThe GSE79973 and UALCAN databases were used for assessing the expression of COL8A1. Clinical data was obtained from the TCGA database to analyze the association between the expression of COL8A1 and clinicopathologic features of GC patients. Survival data of GC patients were acquired from the Kaplan-Meier Plotter database. Gene set enrichment analysis was conducted to characterize biological pathways of COL8A1. Immune infiltration analysis was conducted using the CIBERSORT method based on the TCGA database and online analysis within the TIMER2.0 database. ResultsWe unveiled a noteworthy upregulation of COL8A1 expression across multiple cancer types, particularly in GC. Subsequent analysis underscored a positive linkage between heightened COL8A1 expression and an unfavorable clinical progression in GC patients. Survival analysis indicated that GC patients with elevated COL8A1 expression exhibited a poorer prognosis. Gene enrichment analysis hinted that COL8A1 might participate in physiological processes such as anatomical structure morphogenesis, cell adhesion, focal adhesion, and ECM-receptor interaction et al. in GC. Eventually, we discerned a established association between COL8A1 expression and immune cell infiltration in GC. ConclusionOur results demonstrated that COL8A1 is a key factor which governs immune cell recruitment to GC, representing a valuable prognostic biomarker in GC patients and potentially playing a crucial role in modulating immune cell infiltration.

COL5A2 is a prognostic-related biomarker and correlated with immune infiltrates in gastric cancer based on transcriptomics and single-cell RNA sequencing

BackgroundThere is still a therapeutic challenge in treating gastric cancer (GC) due to its high incidence and poor prognosis. Collagen type V alpha 2 (COL5A2) is increased in various cancers, yet it remains unclear how it contributes to the prognosis and immunity of GC.MethodsThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to download transcriptome profiling (TCGA-STAD; GSE84437), single-cell RNA sequencing (scRNA-seq) data (GSE167297) and clinical information. COL5A2 expression and its relationship with clinicopathological factors were analyzed. We conducted survival analysis and Cox regression analysis to evaluate the prognosis and independent factors of GC. Co-expressed analysis was also performed. To identify the underlying mechanism, we conducted analyses of differentially expressed genes (DEGs) and functional enrichment. The correlations between COL5A2 expression and immune cell infiltration levels and immune infiltrate gene marker sets were further explored. Additionally, we analyzed the association of COL5A2 expression with immunological checkpoint molecules. Furthermore, the relationship between COL5A2 expression and immunotherapy sensitivity was also investigated.ResultsCOL5A2 expression was elevated in GC. More than this, the scRNA-seq analysis revealed that COL5A2 expression had a spatial gradient. The upregulated COL5A2 was associated with worse overall survival. A significant correlation was found between COL5A2 overexpression and age, T classification and clinical stage in GC. COL5A2 was found to be an independent factor for the unfortunate outcome in Cox regression analysis. The co-expressed genes of COL5A2 were associated with tumor stage or poor survival. Enrichment analysis revealed that the DEGs were mainly associated with extracellular matrix (ECM)-related processes, PI3K-AKT signaling pathway, and focal adhesion. GSEA analyses revealed that COL5A2 was associated with tumor progression-related pathways. Meanwhile, COL5A2 expression was correlated with tumor-infiltrating immune cells. Moreover, immunophenoscore (IPS) analysis and PRJEB25780 cohorts showed that patients with low COL5A2 expression were highly sensitive to immunotherapy.ConclusionsCOL5A2 might act as a prognostic biomarker of GC prognosis and immune infiltration and may provide a therapeutic intervention strategy.

CLEC11A expression as a prognostic biomarker in correlation to immune cells of gastric cancer.

Gastric cancer (GC) is a prevalent malignant cancer characterized by a poor survival rate. The C-type lectin domain family 11 member A (CLEC11A) is part of the C-type lectin superfamily, and its dysregulation has been implicated in the progression of several cancers. The specific role of CLEC11A and its association with immune infiltration in GC, however, remains unclear. In this study, we employed The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, Tumor IMmune Estimation Resource (TIMER) database, Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, Kaplan-Meier plotter databases, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and the CIBERSORT algorithm to investigate CLEC11A expression, its prognostic significance, its association with tumor immune infiltration, and gene function enrichment in GC. We conducted western blotting, Cell Counting Kit-8 (CCK-8), wound healing, and transwell assays to validate CLEC11A's function. We found that CLEC11A expression was significantly elevated in GC when compared to adjacent non-tumor tissues. Elevated CLEC11A expression was strongly associated with poor survival outcomes and advanced clinicopathological stages. Moreover, heightened CLEC11A expression positively correlated with immunomodulators, chemokines, and the infiltration of immune cells, especially M2 macrophages, in GC. Additionally, CLEC11A silencing suppressed GC cells proliferation, migration and invasion in vitro. Our results elucidate the functions of CLEC11A in GC, suggesting its potential as a valuable prognostic biomarker and therapeutic target for GC immunotherapy.

Neutrophil extracellular traps-related signature predicts the prognosis and immune infiltration in gastric cancer.

Gastric cancer (GC) is the fifth most prevalent cancer globally, with the third highest case fatality rate. Neutrophil extracellular traps (NETs) are a reticulated structure of DNA, histones, and antimicrobial peptides produced by active neutrophils that trap pathogens. Even though NETs are associated with poorer recurrence-free survival (RFS) and overall survival (OS), the specifics of this interaction between NETs and cancer cells are yet unknown. The keywords "neutrophil extracellular traps and gastric cancer" were used in the GEO database for retrieval, and the GSE188741 dataset was selected to obtain the NETs-related gene. 27 NETs-related genes were screened by univariate Cox regression analysis (p < 0.05). 27 NETs-related genes were employed to identify and categorize NETs-subgroups of GC patients under the Consensus clustering analysis. 808 GC patients in TCGA-STAD combined with GES84437 were randomly divided into a training group (n = 403) and a test group (n = 403) at a ratio of 1:1 to validate the NETs-related signature. Based on Multivariate Cox regression and LASSO regression analysis to develop a NETs-related prognosis model. We developed a very specific nomogram to improve the NETs-clinical score's usefulness. Similarly, we also performed a great result in pan-cancer study with NETs-score. Low NETs scores were linked to higher MSI-H (microsatellite instability-high), mutation load, and immune activity. The cancer stem cell (CSC) index and chemotherapeutic treatment sensitivity were also connected to the NET score. Our comprehensive analysis of NETs in GC suggests that NETs have a role in the tumor microenvironment, clinicopathological features, and prognosis. The NETs-score risk model provides a basis for better prognosis and therapy outcomes in GC patients.

EDIL3 is a potential prognostic biomarker that correlates with immune infiltrates in gastric cancer.

EDIL3, which contains epidermal growth factor-like repeats and discoidin I-like domains, is a secretory protein that plays an important role in embryonic development and various illnesses. However, the biological function of EDIL3 in gastric cancer (GC) is still unclear. The objective of this research was to explore the role and potential mechanism of EDIL3 in GC. In this study, we used the GEPIA, HPA, MethSurv, SMART, STRING, GeneMANIA, LinkedOmics TIMER, TIMER2.0, TISIDB, and RNAactDrug databases to comprehensively analyze the roles of EDIL3 in GC. To validate the in silico findings, EDIL3 expression was measured in our collected GC tissues. Meanwhile, several in vitro experiments were performed to test the function of EDIL3 in GC. We found that EDIL3 was highly expressed in GC and associated with adverse clinical features. In vitro assays revealed that EDIL3 promoted the proliferation, migration, and invasion of GC cells. The functions of EDIL3 and co-expression genes were significantly associated with extracellular structure organization and matrix receptor interaction. EDIL3 expression was positively associated with numerous tumor-infiltrating immune cells and their biomarkers. This study determined that EDIL3 may function as an oncogene and is associated with immune infiltration in GC. EDIL3 could be used as a potential therapeutic target for GC.

PRKAA1 predicts prognosis and is associated with immune characteristics in gastric cancer.

PRKAA1 is the α-subunit of 5-AMP-activated protein kinase. This study aimed to investigate the role of PRKAA1 expression with multiple clinical parameters, the overall survival rate, blood indexes, and immune infiltration in gastric cancer (GC) patients. We investigated PRKAA1 expression data in GC patients using ELISA, protein atlas, UALCAN, and GEPIA. PRKAA1 expression was associated with immune cell infiltration, and immune cell types were analyzed with the TIMER, DICE, and protein atlas databases. We compared the level of PRKAA1 expression based on the clinical features of GC patients (n = 345). GC patients were divided into two groups based on PRKAA1 expression, and the lymphocyte subsets, overall survival rate, and clinical parameters were compared with peripheral blood mononuclear cell and biochemical indexes. PRKAA1 was highly expressed in the serum of GC patients compared with that of healthy individuals. GC patients with distant metastases, a later TNM stage, and stage IV in UICC exhibited higher PRKAA1 expression. PRKAA1 expression was significantly correlated with circulating T cells. The protein atlas and DICE database results confirmed that PRKAA1 was closely associated with T cells in a single-cell cluster. Furthermore, GC patients with low PRKAA1 expression had better OS rates. PRKAA1 may serve as a potential prognostic biomarker for GC and have an association with immune infiltrates.

Aspartoacylase promotes the process of tumour development and is associated with immune infiltrates in gastric cancer

BackgroundAspartoacylase (ASPA) is a gene that plays an important role in the metabolic reprogramming of cancer. However, the clinical relevance of ASPA in gastric cancer (GC) has not been demonstrated.MethodsThe link between ASPA and the clinical features of GC was determined using two public genomic databases. The multivariate Cox proportional hazard model and generalised linear regression model were applied to examine whether the ASPA level is associated with the prognosis and other pathological factors. In addition, the role of specific genes in the infiltration of immune cells in the setting of GC was investigated using a further immunological database. The expression level of various proteins was detected using a western blotting assay. Transwell and methyl thiazolyl tetrazolium tests were applied for the detection of cellular invasion and proliferation, with small hairpin ribonucleic acid used to knockdown ASPA.ResultsAccording to the multivariate Cox regression results, the down-regulated ASPA expression is a distinct prognostic factor. Furthermore, ASPA has significant positive correlations with the infiltration of immune cells in GC lesions. Compared to the non-cancer tissues, the GC tissues had a significantly lower level of ASPA expression (p < 0.05). Using knockdown and overexpression techniques, it was demonstrated that ASPA affects the capacity of cell lines for GC to both proliferate and invade.ConclusionOverall, ASPA could promote the occurrence and development of GC and presents a promising predictive biomarker for the disease since it is favourably connected with immune infiltrates and negatively correlated with prognosis.

TMEM200A is a potential prognostic biomarker and correlated with immune infiltrates in gastric cancer.

Gastric cancer (GC) is one of the most common malignant tumors in the digestive system. Several transmembrane (TMEM) proteins are defined as tumor suppressors or oncogenes. However, the role and underlying mechanism of TMEM200A in GC remain unclear. We analyzed the expression of TMEM200A in GC. Furthermore, the influence of TMEM200A on survival of GC patients was evaluated. The correlations between the clinical information and TMEM200A expression were analyzed using chi-square test and logistic regression. Relevant prognostic factors were identified performing univariate and multivariate analysis. Gene set enrichment analysis (GSEA) was performed based on the TCGA dataset. Finally, we explore the relationship between TMEM200A expression and cancer immune infiltrates using CIBERSORT. TMEM200A was up-regulated in GC tissues than that in adjacent non-tumor tissues based on TCGA database. Meta-analysis and RT-qPCR validated the difference in TMEM200A expression. Kaplan-Meier curves suggested the increased TMEM200A had a poor prognosis in GC patients. The chi-square test and logistic regression analyses showed that the TMEM200A expression correlates significantly with T stage. Multivariate analysis showed that TMEM200A expression might be an important independent predictor of poor overall survival in GC patients. GSEA identified five immune-related signaling pathways and five tumor-related signaling pathways significantly enriched in the high TMEM200A expression phenotype pathway. Finally, we found CD8+ T cells is apparently decreased in high TMEM200A expression group. Conversely, eosinophils is increased in high expression group compared with low expression group. TMEM200A is a potential prognostic biomarker and correlated with immune infiltrates in GC.

Cuproptosis-related gene SERPINE1 is a prognostic biomarker and correlated with immune infiltrates in gastric cancer

PurposeThe serine protease inhibitor clade E member 1 (SERPINE1) has been studied as a potential biomarker in a variety of cancers, but poorly studied in gastric cancer (GC). The purpose of this study was to explore the prognostic value of SERPINE1 in GC and primarily analyze its functions.MethodsWe analyzed the the prognostic value of SERPINE1 and studied the relationship with clinicopathologic biomarkers in gastric cancer. The expression of SERPINE1 was analyzed by GEO and TCGA databases. Moreover, we validated the results by immunohistochemistry. Next, the correlation analysis between SERPINE1 and the cuproptosis-related genes was analyzed by the “Spearman” method. CIBERSORT and TIMER algorithms were used to analyze the correlation of SERPINE1 with immune infiltration. Furthermore, GO and KEGG gene enrichment analyses were used to study the functions and pathways that SERPINE1 might be involved in. Then, drug sensitivity analysis was performed using CellMiner database. Finally, a cuproptosis-immune-related prognostic model was constructed using genes related to immune and cuproptosis, and verified against external datasets.ResultsSERPINE1 was up-regulated in gastric cancer tissues, which tends toward poor prognosis. Using immunohistochemistry experiment, the expression and prognostic value of SERPINE1 were verified. Then, we found that SERPINE1 was negatively correlated with cuproptosis-related genes FDX1, LIAS, LIPT1, and PDHA1. On the contrary, SERPINE1 was positively correlated with APOE. This indicates the effect of SERPINE1 on the cuproptosis process. Furthermore, by conducting immune-related analyses, it was revealed that SERPINE1 may promote the inhibitory immune microenvironment. The infiltration level of resting NK cells, neutrophils, activated mast cells, and macrophages M2 was positively correlated with SERPINE1. However, B cell memory and plasma cells were negatively correlated with SERPINE1. Functional analysis showed that SERPINE1 was closely related to angiogenesis, apoptosis, and ECM degradation. The KEGG pathway analysis showed that SERPINE1 may be associated with P53, Pi3k/Akt, TGF-β, and other signaling pathways. Drug sensitivity analysis showed that SERPINE1 could be also seen as a potential treatment target. The risk model based on SERPINE1 co-expression genes could better predict the survival of GC patients than SERPINE1 alone. We also verified the prognostic value of the risk score by GEO external datasets.ConclusionSERPINE1 is highly expressed in gastric cancer and related to poor prognosis. SERPINE1 may regulate cuproptosis and the immune microenvironment by a series of pathways. Therefore, SERPINE1 as a prognostic biomarker and potential therapeutic target deserves further study.

CLDN5 identified as a biomarker for metastasis and immune infiltration in gastric cancer via pan-cancer analysis.

CLDN5 protein is essential for the formation of tight junctions in epithelial cells, and has been associated with epithelial-mesenchymal transition. Research has indicated that CLDN5 is associated with tumor metastasis, the tumor microenvironment, and immunotherapy in multiple types of cancer. Also, no comprehensive evaluation of the expression of CLDN5 and immunotherapy signatures through a pan-cancer analysis or immunoassay has been performed. We explored CLDN5's differential expression, survival analysis and clinicopathological staging through the TCGA database, and then corroborated the expression of CLDN5 by utilizing the GEO (Gene expression omnibus) database. To analyze CLDN5 KEGG, GO, and Hallmark mutations, as well as TIMER for immune infiltration, GSEA was utilized with ROC curve, mutation, and other factors such as survival, pathological stage, TME, MSI, TMB, immune cell infiltration, and DNA methylation. Immunohistochemistry was used to assess CLDN5 staining in gastric cancer tissues and paracancerous tissues. Visualization was done with R version 4.2.0 (http://www.rproject.org/). According to TCGA database, CLDN5 expression levels differed significantly between cancer and normal tissues, and the GEO database (GSE49051 and GSE 64951) and tissue microarrays confirmed this result. Infiltrating cluster of differentiation 8+ (CD8+) T cells, CD4+ cells, neutrophils, dendritic cells, and macrophages revealed a correlation with CLDN5 expression. DNA methylation, TMB, and MSI are related to CLDN5 expression. Based on the ROC curve analysis, CLDN5 demonstrates outstanding diagnostic effectiveness for gastric cancer and is comparable to CA-199. The findings suggest that CLDN5 is implicated in the oncogenesis of diverse cancer types, underscoring its potential significance in cancer biology. Notably, CLDN5 could have implications in immune filtration and immune checkpoint inhibitor therapies, however, further research is needed to confirm this.

BASP1 expression is associated with poor prognosis and is correlated with immune infiltration in gastric cancer.

BASP1 is a membrane-bound protein that plays a promotional or inhibitory role in a variety of tumors; however, its role in gastric cancer (GC) and in the immune microenvironment has not been reported. The objectives of this study were to determine whether BASP1 is a valuable prognostic marker for GC and to explore its role in the immune microenvironment of GC. The expression level of BASP1 in GC was analyzed based on the TCGA dataset and further verified using GSE54129 and GSE161533 datasets, immunohistochemistry, and western blotting. The association between BASP1 and clinicopathological characteristics, as well as its predictive value, were examined using the STAD dataset. Cox regression analysis was performed to determine whether BASP1 can be used as an independent prognostic indicator for GC, and a nomogram was constructed to predict OS. The association between BASP1 and immune cell infiltration, immune checkpoints, and immune cell markers was confirmed by enrichment analysis, as well as analysis based on the TIMER and GEPIA databases. BASP1 was observed to be highly expressed in GC and was associated with a poor prognosis. The expression of BASP1 was positively correlated with the expression of immune checkpoints and immune cell markers, as well as immune cell infiltration. Thus, BASP1 may serve as a standalone prognostic indicator for GC. BASP1 is highly correlated with immune processes, and its expression is positively correlated with the degree of immune cell infiltration, immune checkpoints, and immune cell markers.

Joint analysis identified FAP as a prognostic and diagnostic biomarker correlated immune infiltration in gastric cancer.

Gastric cancer is one of the most malignant types of cancer in the digestive system because of its high incidence and mortality. There is a notable association between gastric cancer progression and the level and sort of immune cells infiltrating the tumor microenvironment. First, 41 up-regulated differentially expressed genes (DEGs) and 91 down-regulated DEGs were identified from the Gene Expression Omnibus (GEO) database. Among the 21 core genes, prognosis biomarkers FAP, ASPN and CTHRC1 were identified for further study via Kaplan-Meier Plotter, with FAP having the highest prognostic value among them. In addition, the ROC curves of FAP (AUC=0.992), ASPN (AUC=0.955) and CTHRC1 (AUC=0.983) also showed high diagnostic value. Then the expression and mutation levels of the biomarkers were verified by GEPIA and cBioPortal. Their high expression levels were closely correlated to the clinical stages and metastasis status of gastric cancer. Furthermore, their expression was strongly relevant to immune infiltration and macrophage marker levels. In drug response analysis, gastric cancer cell lines with overexpression of FAP and ASPN were more sensitive to PI3K and MET inhibitors, respectively. Importantly, the meta-analysis showed that FAP had an overall positive rate of 68 % (63-73 %, 95 % CI; n=382) and the patients with high expression of FAP showed a poor prognosis in terms of OS (HR=1.82, 1.33-2.48, 95 % CI) in gastric cancer. In short, FAP, ASPN and CTHRC1 were identified as potential prognostic and diagnostic biomarkers related with immunity and might be effective therapeutic targets of gastric cancer, and the significance of FAP for the prognosis was further assessed by meta-analysis.

Overexpression of ferroptosis-related genes FSP1 and CISD1 is related to prognosis and tumor immune infiltration in gastric cancer.

Gastric cancer (GC) is one of the highest incidence rate cancers worldwide and the search for new biomarkers remains urgent due to its relatively poor prognosis and limited treatment methods. Ferroptosis suppressor protein 1 (FSP1) and iron sulfur domain 1 (CISD1) promoted malignant tumor progression as ferroptosis suppressors in a variety of tumors, but their study in GC remains to be explored. In our study, FSP1 and CISD1 expression were predicted through different databases and confirmed by qRT-PCR, immunohistochemistry and western blotting. Enrichment analyses were exploited to explore the potential functions of FSP1 and CISD1. Finally, their relationship with immune infiltration was determined by Tumor Immune Estimation Resource and ssGSEA algorithm. The expression of FSP1 and CISD1 was higher in GC tissues. Their strongly positive immunostaining was associated with increased tumor size, degree of differentiation, depth of invasion and lymph node metastasis in GC patients. Up-regulated FSP1 and CISD1 predicted poorer overall survival of patients with GC. Furthermore, FSP1 and CISD1 as ferroptosis inhibitors were predicted to be involved in GC immune cell infiltration. Our study suggested that FSP1 and CISD1 acted as biomarkers of poor prognosis and promising immunotherapeutic targets for GC.

DISC1 as a prognostic biomarker correlated with immune infiltrates in gastric cancer

Multiple mental diseases could arise in people who have the disrupted in schizophrenia 1 (DISC1) gene. However, it was unknown how DISC1 might contribute to the development of tumors and immune responses. We extracted data from the Cancer Genome Atlas (TCGA) and TISIDB databases from stomach adenocarcinoma (STAD) patients, which revealed that DISC1 overexpression was closely associated with tumor histological type (mucinous vs. tubular, OR = 2.860, CI = 1.423–5.872, p = 0.004), as well as tumor stage and grade. Furthermore, the higher the DISC1 expression, the lower the overall 10-year survival rate. Patients with low DISC1 expression had a significantly longer progression-free interval (PFI) and disease-specific survival (DSS) than patients with high DISC1 expression. However, patients with higher DISC1 expression in the T3&T4, N0&N1 and M0 subgroups had poorer prognosis in terms of OS, DSS and PFI, as could be seen in the subgroup survival analysis. Public datasets were used to predict lncRNA-miRNA-DISC1 regulation. DISC1 was significantly up-regulated in GC(gastric cancer), and its expression levels showed a moderate to strong positive correlation with infiltration levels of effector memory T cells (Tem) and central memory T cells (Tcm), and a negative correlation was observed with Th17 cells and NK CD56bright cells. In addition, concomitant with the high expression of the DISC1 gene was a decrease in MHC-I (Major Histocompatibility Complex-I)expression and an increase in MHC-II expression, and altered chemokine expression. The upregulation of CXCL12 and CXCR4 expression could be caused by an increase in DISC1 expression.The above expression variability and correlation suggest a role for DISC1 in regulating tumor immunity in GC. These findings suggest that high expression of DISC1 could be an independent prognostic factor for GC.

Identification of GNG7 as a novel biomarker and potential therapeutic target for gastric cancer via bioinformatic analysis and in vitro experiments.

Gastric cancer (GC) is one of the most common malignancies with unfavorable prognoses. The present study aimed to identify novel biomarkers or potential therapeutic targets in GC via bioinformatic analysis and in vitro experiments. The Gene Expression Omnibus and The Cancer Genome Atlas databases were used to screen the differentially expressed genes (DEGs). After protein-protein interaction network construction, both module and prognostic analyses were performed to identify prognosis-related genes in GC. The expression patterns and functions of G protein γ subunit 7 (GNG7) in GC were then visualized in multiple databases and further verified using in vitro experiments. A total of 897 overlapping DEGs were detected and 20 hub genes were identified via systematic analysis. After accessing the prognostic value of the hub genes using the online server Kaplan-Meier plotter, a six-gene prognostic signature was identified, which was also significantly correlated with the process of immune infiltration in GC. The results of open-access database analyses suggested that GNG7 is downregulated in GC; this downregulation was associated with tumor progression. Furthermore, the functional enrichment analysis unveiled that the GNG7-coexpressed genes or gene sets were closely correlated with the proliferation and cell cycle processes of GC cells. Finally, in vitro experiments further confirmed that GNG7 overexpression inhibited GC cell proliferation, colony formation, and cell cycle progression and induced apoptosis. As a tumor suppressor gene, GNG7 suppressed the growth of GC cells via cell cycle blockade and apoptosis induction and thus may be used as a potential biomarker and therapeutic target for GC.