Immune Microenvironment Of Gastric Cancer Research Articles

TOB1 modulates neutrophil phenotypes to influence gastric cancer progression and immunotherapy efficacy.

The ErbB-2.1(TOB1) signaling transducer protein is a tumor-suppressive protein that actively suppresses the malignant phenotype of gastric cancer cells. Yet, TOB1 negatively regulates the activation and growth of different immune cells. Understanding the expression and role of TOB1 in the gastric cancer immune environment is crucial to maximize its potential in targeted immunotherapy. This study employed multiplex immunofluorescence analysis to precisely delineate and quantify the expression of TOB1 in immune cells within gastric cancer tissue microarrays. Univariate and multivariate Cox analyses were performed to assess the influence of clinical-pathological parameters, immune cells, TOB1, and double-positive cells on the prognosis of gastric cancer patients. Subsequent experiments included co-culture assays of si-TOB1-transfected neutrophils with AGS or HGC-27 cells, along with EdU, invasion, migration assays, and bioinformatics analyses, aimed at elucidating the mechanisms through which TOB1 in neutrophils impacts the prognosis of gastric cancer patients. We remarkably revealed that TOB1 exhibits varying expression levels in both the nucleus (nTOB1) and cytoplasm (cTOB1) of diverse immune cell populations, including CD8+ T cells, CD66b+ neutrophils, FOXP3+ Tregs, CD20+ B cells, CD4+ T cells, and CD68+ macrophages within gastric cancer and paracancerous tissues. Significantly, TOB1 was notably concentrated in CD66b+ neutrophils. Survival analysis showed that a higher density of cTOB1/nTOB1+CD66b+ neutrophils was linked to a better prognosis. Subsequent experiments revealed that, following stimulation with the supernatant of tumor tissue culture, the levels of TOB1 protein and mRNA in neutrophils decreased, accompanied by enhanced apoptosis. HL-60 cells were successfully induced to neutrophil-like cells by DMSO. Neutrophils-like cells with attenuated TOB1 gene expression by si-TOB1 demonstrated heightened apoptosis, consequently fostering a malignant phenotype in AGS and HCG-27 cells upon co-cultivation. The subsequent analysis of the datasets from TCGA and TIMER2 revealed that patients with high levels of TOB1 combined neutrophils showed better immunotherapy response. This study significantly advances our comprehension of TOB1's role within the immune microenvironment of gastric cancer, offering promising therapeutic targets for immunotherapy in this context.

Discovery of a novel lipid metabolism-related gene signature to predict outcomes and the tumor immune microenvironment in gastric cancer by integrated analysis of single-cell and bulk RNA sequencing

Gastric cancer (GC) is a pressing global clinical issue, with few treatment options and a poor prognosis. The onset and spread of stomach cancer are significantly influenced by changes in lipid metabolism-related pathways. This study aimed to discover a predictive signature for GC using lipid metabolism-related genes (LMRGs) and examine its correlation with the tumor immune microenvironment (TIME). Transcriptome data and clinical information from patients with GC were collected from the TCGA and GEO databases. Data from GC samples were analyzed using both bulk RNA-seq and single-cell sequencing of RNA (scRNA-seq). To identify survival-related differentially expressed LMRGs (DE-LMRGs), differential expression and prognosis studies were carried out. We built a predictive signature using LASSO regression and tested it on the TCGA and GSE84437 datasets. In addition, the correlation of the prognostic signature with the TIME was comprehensively analyzed. In this study, we identified 258 DE-LMRGs in GC and further screened seven survival-related DE-LMRGs. The results of scRNA-seq identified 688 differentially expressed genes (DEGs) between the three branches. Two critical genes (GPX3 and NNMT) were identified using the above two gene groups. In addition, a predictive risk score that relies on GPX3 and NNMT was developed. Survival studies in both the TCGA and GEO datasets revealed that patients categorized to be at low danger had a significantly greater prognosis than those identified to be at high danger. Additionally, by employing calibration plots based on TCGA data, the study demonstrated the substantial predictive capacity of a prognostic nomogram, which incorporated a risk score along with various clinical factors. Within the high-risk group, there was a noticeable abundance of active natural killer (NK) cells, quiescent monocytes, macrophages, mast cells, and activated CD4 + T cells. In summary, a two-gene signature and a predictive nomogram have been developed, offering accurate prognostic predictions for general survival in GC patients. These findings have the potential to assist healthcare professionals in making informed medical decisions and providing personalized treatment approaches.

Pumilio1 regulates NPM3/NPM1 axis to promote PD-L1-mediated immune escape in gastric cancer

Abnormal regulation of RNA binding proteins (RBPs) plays an essential role in tumorigenesis and progression, but their functions and mechanisms remain largely elusive. Previously, we reported that Pumilio 1 (PUM1), a RBP, could regulate glycolysis metabolism and promote the progression of gastric cancer (GC). However, the role of PUM1 in tumor immune regulation remains largely elusive. In this study, we report that PUM1 induces immune escape through posttranscriptional regulation of PD-L1 in GC. We used multiplexed immunohistochemistry to analyze the correlation between PUM1 expression and immune microenvironment in GC. The effect of PUM1 deficiency on tumor killing of T cells was examined in vitro and in vivo. The molecular mechanism of PUM1 was evaluated via RNA immunoprecipitation, chromatin immunoprecipitation, Western blot, co-immunoprecipitation, and RNA stability assays. Clinically, elevated PUM1 expression is associated with high-expression of PD-L1, lack of CD8+ T cell infiltration and poor prognosis in GC patients. PUM1 positively regulates PD-L1 expression and PUM1 reduction enhances T cell killing of tumors. Mechanistically, PUM1 directly binds to nucleophosmin/nucleoplasmin 3 (NPM3) mRNA and stabilizes NPM3. NPM3 interacts with NPM1 to promote NPM1 translocation into the nucleus and increase the transcription of PD-L1. PUM1 inhibits the anti-tumor activity of T cells through the PUM1/NPM3/PD-L1 axis. In summary, this study reveals the critical post-transcriptional effect of PUM1 in the modulation of PD-L1-dependent GC immune escape, thus provides a novel indicator and potential therapeutic target for cancer immunotherapy.

Correlation of Neuroendocrine Differentiation with a Distinctively Suppressive Immune Microenvironment in Gastric Cancer

Introduction: Neuroendocrine neoplasms (NENs) harbored significantly suppressive tumor immune microenvironments (TIMEs). However, the immunological effects of neuroendocrine differentiation (NED) on non-NENs, such as gastric cancer (GC), were unknown. Methods: Between pure gastric cancer (PGC) and GC-NED, TIME features were scored based on expression data and validated on serial whole-tissue sections of surgical samples, with tertiary lymphoid structures (TLSs) and the extra-TLS zone evaluated independently using multi-marker immunohistochemical staining. Risk analyses of TIME features on tumor behaviors were performed in GC-NED. The universal immunological effects of NED were explored preliminarily in adenocarcinomas arising in other organs. Results: Based on over 11,500 annotated TLSs and 2,700 extra-TLS zones, compared with PGC, GC-NED harbored a distinctively more suppressive TIME characterized by increased but immature TLSs, with higher naïve B-cell and follicular regulatory T-cell densities and downregulated TLS maturation-related cell ratios inside TLSs; increased naïve B-cell and regulatory T-cell densities; and a high proportion of exhausted T cells in the extra-TLS zone. The upregulated tumor PD-L1 expression and its close correlations with TLS formation and maturation were remarkable exclusively in GC-NED. TIME features, especially those regarding TLSs, were significantly correlated with tumor growth and invasion. The desynchrony between TLS formation and maturation and increased naïve or regulatory immune cell infiltration was observed in adenocarcinomas of the colorectum, pancreas, lung, and prostate. Conclusion: NED highlighted a distinct GC entity with more suppressive TIME features correlated with tumor behaviors, indicating a cohort that would benefit more from immunotherapies.

Hierarchical clustering identifies oxidative stress-related subgroups for the prediction of prognosis and immune microenvironment in gastric cancer

BackgroundGastric cancer (GC) is a prevalent malignancy of the digestive tract globally, demonstrating a substantial occurrence of relapse and metastasis, alongside the absence of efficacious treatment. Tumor progression and the development of cancer are linked to oxidative stress. Our objective was twofold: first, to determine distinct subcategories based on oxidative stress in GC patients, and second, to establish oxidative stress-related genes that would aid in stratifying the risk for GC patients. MethodsTCGA-STAD and GSE84437 datasets were utilized to obtain the mRNA expression profiles and corresponding clinical information of GC patients. Through consensus clustering analysis, distinct subgroups related to oxidative stress were identified. To uncover the underlying mechanisms, GSEA and GSVA were performed. xCell, CIBERSORT, MCPCounter, and TIMER algorithms were employed to evaluate the immune microenvironment and immune status of the different GC subtypes. A prognostic risk model was developed using the TCGA-STAD dataset and substantiated using the GSE84437 dataset. Furthermore, qRT-PCR was employed to validate the expression of genes associated with prognosis. ResultsTwo distinct subtypes of oxidative stress were discovered, with markedly different survival rates. The C1 subtype demonstrated an activated immune signal pathway, a significant presence of immune cell infiltration, high immune score, and a high microenvironment score, indicating a poor prognosis. Moreover, a prognostic signature related to oxidative stress (IMPACT and PXDN) was able to accurately estimate the likelihood of survival for patients with gastric cancer. A nomogram incorporating the patients' gender, age, and risk score was able to predict survival in gastric cancer patients. Additionally, the expression of IMPACT and PXDN showed a strong correlation with overall survival and the infiltration of immune cells. ConclusionBased on signatures related to oxidative stress, we developed an innovative system for categorizing patients with GC. This stratification enables accurate prognostication of individuals with GC.

Integrated bioinformatics analysis of noncoding RNAs with tumor immune microenvironment in gastric cancer

In recent years, molecular and genetic research hotspots of gastric cancer have been investigated, including microRNAs, long noncoding RNAs (lncRNAs) and messenger RNA (mRNAs). The study on the role of lncRNAs may help to develop personalized treatment and identify potential prognostic biomarkers in gastric cancer. The RNA-seq and miRNA-seq data of gastric cancer were downloaded from the TCGA database. Differential analysis of RNA expression between gastric cancer samples and normal samples was performed using the edgeR package. The ceRNA regulatory network was visualized using Cytoscape. KEGG pathway analysis of mRNAs in the ceRNA network was performed using the clusterProfiler package. CIBERSORT was used to distinguish 22 immune cell types and the prognosis-related genes and immune cells were determined using Kaplan-Meier and Cox proportional hazard analyses. To estimate these nomograms, we used receiver operating characteristic and calibration curve studies. The ceRNA regulation network of gastric cancer was built in this study, and the genes in the network were analyzed for prognosis. A total of 980 lncRNAs were differentially expressed, of which 774 were upregulated and 206 were downregulated. A survival study identified 15 genes associated with gastric cancer prognosis, including VCAN-AS1, SERPINE1, AL139002.1, LINC00326, AC018781.1, C15orf54, hsa-miR-145. Monocytes and Neutrophils were associated with the survival rate of gastric cancer. Our research uncovers new ceRNA network for the detection, treatment, and monitoring of gastric cancer.

The bioinformatics analysis of CD59 in Helicobacter pylori infected gastric cancer.

Cell surface molecules play important roles in cell signal transduction pathways during microbial infection. In this study, the expression and the functions of CD59 was investigated in H. pylori infected gastric cancer (GC). The differential expression of CD59 and the influence of H. pylori on the expression of CD59 were analyzed via bioinformatics through Gene Set Enrichment in GC. In addition, the expression of CD59 in GES-1, AGS cells and GC tissues infected with H. pylori was confirmed by Western blot. Bioinformatics results and H. pylori infection experiments showed CD59 decreased obviously in H. pylori infected GC cells and tissues. The expression of CD59 was linked to the survival rate of GC patients, and influenced various immune cells in the immune microenvironment of GC. CD59 interacts with other genes to form a network in H. pylori infected GC. Certainly, CD59 decreased significantly in H. pylori infected GC tissues, GES-1 and AGS cells in vitro. H. pylori infection could influence the expression of CD59 in GC indicating that CD59 may be a promising treatment target.

Expression patterns and immunological characterization of PANoptosis -related genes in gastric cancer.

Accumulative studies have demonstrated the close relationship between tumor immunity and pyroptosis, apoptosis, and necroptosis. However, the role of PANoptosis in gastric cancer (GC) is yet to be fully understood. This research attempted to identify the expression patterns of PANoptosis regulators and the immune landscape in GC by integrating the GSE54129 and GSE65801 datasets. We analyzed GC specimens and established molecular clusters associated with PANoptosis-related genes (PRGs) and corresponding immune characteristics. The differentially expressed genes were determined with the WGCNA method. Afterward, we employed four machine learning algorithms (Random Forest, Support Vector Machine, Generalized linear Model, and eXtreme Gradient Boosting) to select the optimal model, which was validated using nomogram, calibration curve, decision curve analysis (DCA), and two validation cohorts. Additionally, this study discussed the relationship between infiltrating immune cells and variables in the selected model. This study identified dysregulated PRGs and differential immune activities between GC and normal samples, and further identified two PANoptosis-related molecular clusters in GC. These clusters demonstrated remarkable immunological heterogeneity, with Cluster1 exhibiting abundant immune infiltration. The Support Vector Machine signature was found to have the best discriminative ability, and a 5-gene-based SVM signature was established. This model showed excellent performance in the external validation cohorts, and the nomogram, calibration curve, and DCA indicated its reliability in predicting GC patterns. Further analysis confirmed that the 5 selected variables were remarkably related to infiltrating immune cells and immune-related pathways. Taken together, this work demonstrates that the PANoptosis pattern has the potential as a stratification tool for patient risk assessment and a reflection of the immune microenvironment in GC.

CLDN18.2 expression and its impact on prognosis and the immune microenvironment in gastric cancer

BackgroundThe investigational use of zolbetuximab (IMAB362), a groundbreaking monoclonal antibody medication targeting claudin 18.2 (CLDN18.2), for treatment of advanced gastrointestinal cancers is currently underway. The unclear clinicopathological characteristics and tumour immune microenvironment of CLDN18.2-positive gastric cancer (GC) make it difficult to develop and optimize CLDN18.2-targeted therapies.MethodsA total of 451 tumour tissues, 342 matched paraneoplastic tissues, and 107 matched metastatic lymph nodes were collected from GC patients. These specimens were stained for CLDN18.2 expression and quantified using immunohistochemistry (IHC). Correlations between CLDN18.2 expression and clinicopathological features as well as immune-related factors were analysed. Survival curves were drawn using the Kaplan‒Meier approach, and independent factors affecting GC prognosis were identified using Cox regression analysis. Information from relevant databases was used for corroboration.ResultsExpression of the CLDN18.2 gene was significantly lower in gastric tumour tissues than in normal tissues (p < 0.001) but comparable in metastatic lymph nodes (p = 0.851). CLDN18.2 expression was significantly associated with Borrmann type, degree of differentiation, PD-L1 expression, and survival in GC patients and was identified as an independent risk factor for patient prognosis (HR = 1.57, 95% CI 1.16–2.11, p = 0.003). There was no correlation between CLDN18.2 expression and HER2, Lauren type, tumour size, TNM stage, or any other clinicopathological characteristic. In CLDN18.2-positive tumours, fractions of CD4 + T cells and CD8 + T cells were significantly higher than those in CLDN18.2-negative tumours. Patients with CLDN18.2-negative expression and significant CD4 + T-cell or CD8 + T-cell infiltration had the best prognosis (5-year OS: 61.0%, P = 0.036; 5-year OS: 62.2%, P = 0.034).ConclusionsCLDN18.2 is expressed at a low level in tumour tissues and serves as an independent prognostic factor for patients with GC. Furthermore, CLDN18.2 correlates with immune infiltrating cells and PD-L1 expression.

A prognostic model for STAD based on hypoxia- and immune-related genes

IntroductionFeatured with vast heterogeneity, gastric cancer (GC) is one of the leading causes of cancer-related deaths. A specific prognostic model is necessary for the improvement of clinical treatment strategies. Hypoxia is a common feature in the tumor microenvironment that promotes tumor progression. However, the current evaluation of hypoxic tumor immune microenvironment in GC is still inadequate.Material and methodsWith sequence data and single nucleotide variants data obtained from The Cancer Genome Atlas-STAD dataset as well as hypoxia- and immune-related genes acquired from MsigDB and ImmPort, a hypoxia-immune-based gene signature of gastric adenocarcinoma (STAD) was built by Cox regression analysis. Riskscore could be used as an independent prognostic factor.ResultsReceiver operating characteristic curve and survival curve showed the accuracy of the model. Pearson correlation analysis showed that DUSP1, one of the hypoxia- and immune-related feature genes, was positively correlated with immune cell scores and immune-related function scores. In addition, low-risk group peers were found to be in higher immune infiltration status and had higher immunophenoscore as demonstrated by single-sample GSEA, indicating better response to immune checkpoint inhibitors (ICI) treatment among the low-risk group. q-PCR results showed that DUSP1, IGFBP1, CGB5, GPC3 and EGF were significantly highly expressed in STAD cells, while FAM3D and FGF8 were significantly down-regulated.ConclusionsOverall, our study not only paves the way for future studies focusing on hypoxia and immune microenvironment but also improves STAD patient’s prognosis and their response to immunotherapy.

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.

A novel immunogenic cell death-related subtype classification and risk signature for predicting prognosis and immunotherapy efficacy in gastric cancer.

The majority of gastric cancer (GC) patients are in a progressive stage at the initial stage of treatment, and the overall response rate to immunotherapy remains unsatisfactory largely due to the lack of effective prognostic biomarkers. Immunogenic cell death (ICD) was identified as a new form of regulated cell death that can activate adaptive immune responses and further promote immunotherapy efficacy. Therefore, we attempted to characterize the ICD-associated signature to stratify patients who could benefit from immunotherapy. In our study, two subgroups of patients were identified based on the data of 34 ICD-related genes extracted from The Cancer Genome Atlas database via consensus clustering. The estimated scores, stromal scores, immune scores, tumor purity, and survival rate showed significant differences between the low and high ICD groups. Then, we constructed an ICD-related risk signature, including IFNB1, IL6, LY96, and NT5E, using least absolute shrinkage and selection operator Cox regression analysis; then, high- and low-risk groups could be clearly distinguished. Notably, the risk score is a reliable predictor of the prognosis and immunotherapy outcome in GC, which was further validated in an immunohistochemistry assay. These results suggest that ICD is closely associated with the prognosis and tumor immune microenvironment in GC. Taken together, this study first constructed and validated a prognostic ICD-related signature to predict the survival and effect of immunotherapy in GC, which provided new insight for potent individualized immunotherapy strategies.

Effect of NETs/COX-2 pathway on immune microenvironment and metastasis in gastric cancer.

Neutrophil extracellular traps (NETs) are crucial in the progression of several cancers. The formation of NETs is closely related to reactive oxygen species (ROS), and the granule proteins involved in nucleosome depolymerization under the action of ROS together with the loosened DNA compose the basic structure of NETs. This study aims to investigate the specific mechanisms of NETs promoting gastric cancer metastasis in order to perfect the existing immunotherapy strategies. In this study, the cells and tumor tissues of gastric cancer were detected by immunological experiments, real-time polymerase chain reaction and cytology experiments. Besides, bioinformatics analysis was used to analyze the correlation between cyclooxygenase-2 (COX-2) and the immune microenvironment of gastric cancer, as well as its effect on immunotherapy. Examination of clinical specimens showed that NETs were deposited in tumor tissues of patients with gastric cancer and their expression was significantly correlated with tumor staging. Bioinformatics analysis showed that COX-2 was involved in gastric cancer progression and was associated with immune cell infiltration as well as immunotherapy. In vitro experiments, we demonstrated that NETs could activate COX-2 through Toll-like receptor 2 (TLR2) and thus enhance the metastatic ability of gastric cancer cells. In addition, in a liver metastasis model of nude mice we also demonstrated the critical role of NETs and COX-2 in the distant metastasis of gastric cancer. NETs can promote gastric cancer metastasis by initiating COX-2 through TLR2, and COX-2 may become a target for gastric cancer immunotherapy.

Construction and validation of a prognosis signature based on the immune microenvironment in gastric cancer.

Gastric cancer (GC) is an aggressive malignant tumor with a high degree of heterogeneity, and its immune microenvironment is closely associated with tumor growth, development and drug resistance. Therefore, a classification system of gastric cancer based explicitly on the immune microenvironment context might enrich the strategy for gastric cancer prognosis and therapy. A total of 668 GC patients were collected from TCGA-STAD (n = 350), GSE15459 (n = 192), GSE57303 (n = 70) and GSE34942 (n = 56) datasets. Three immune-related subtypes (immunity-H, -M, and -L) were identified by hierarchical cluster analysis based on the ssGSEA score of 29 immune microenvironment-related gene sets. The immune microenvironment-related prognosis signature (IMPS) was constructed via univariate Cox regression, Lasso-Cox regression and multivariate Cox regression, and nomogram model combining IMPS and clinical variables was further constructed by the "rms" package. RT-PCR was applied to validate the expression of 7 IMPS genes between two human GC cell lines (AGS and MKN45) and one normal gastric epithelial cell line (GES-1). The patients classified as immunity-H subtype exhibited highly expressed immune checkpoint and HLA-related genes, with enriched naïve B cells, M1 macrophages and CD8 T cells. We further constructed and validated a 7-gene (CTLA4, CLDN6, EMB, GPR15, ENTPD2, VWF and AKR1B1) prognosis signature, termed as IMPS. The patients with higher IMPS expression were more likely to be associated with higher pathology grade, more advanced TNM stages, higher T and N stage, and higher ratio of death. In addition, the prediction values of the combined nomogram in predicting 1-year (AUC = 0.750), 3-year (AUC = 0.764) and 5-year (AUC = 0.802) OS was higher than IMPS and individual clinical characteristics. The IMPS is a novel prognosis signature associated with the immune microenvironment and clinical characteristics. The IMPS and the combined nomogram model provide a relatively reliable predictive index for predicting the survival outcomes of gastric cancer.

Integrated analysis from multicentre studies identities m7G-related lncRNA-derived molecular subtypes and risk stratification systems for gastric cancer.

Gastric cancer (GC) is the fourth leading cause of cancer death worldwide. Due to the lack of effective chemotherapy methods for advanced gastric cancer and poor prognosis, the emergence of immunotherapy has brought new hope to gastric cancer. Further research is needed to improve the response rate to immunotherapy and identify the populations with potential benefits of immunotherapy. It is unclear whether m7G-related lncRNAs influence tumour immunity and the prognosis of immunotherapy. This study evaluated 29 types of immune cells and immune functions in gastric cancer patients, and m7G-related lncRNAs and their molecular subtypes were identified. In addition, we also studied the biological function characteristics of m7G-related lncRNA molecular subtypes. Finally, the patient's risk score was calculated based on m7G-related lncRNAs, and a nomogram of staging and risk groups was established to predict the prognosis. For experimental verification, RT-qPCR were preformed from the native cohort. After identifying m7G-related lncRNAs and their molecular subtypes, we found three molecular subtypes, the B subtype had the highest level of infiltration, and the B subtype may benefit more from immunotherapy. We divided GC patients into two regulator subtypes based on biological function. The two subtypes have significant immunological differences and can be used to judge ICI treatment. We established a risk score formula based on five lncRNAs, including LINC00924, LINC00944, LINC00865, LINC00702, and ZFAS1. Patients with poor prognoses were closely related to patients in the high-risk group. After comprehensive analysis of different risk groups, the efficacy of the high-risk group on bleomycin, cisplatin, docetaxel, doxorubicin and etoposide was better than that of the low-risk group, suggesting that risk subgroups based on risk scores play a guiding role in chemotherapy and that the high-risk group may benefit more from immunotherapy. RT-qPCR results showed that LINC00924, LINC00944, and LINC00865 were highly expressed in tumour tissues, while LINC00702 and ZFAS1 were expressed at low levels in tumour tissues. In conclusion, we were the first to discover that m7G-related lncRNAs play a vital role in the tumour immune microenvironment of gastric cancer, and a risk prediction model was established to identify patients with potential benefits from immunotherapy and predict the prognosis of GC patients.

Cancer-Associated Fibroblasts Affect Tumor Metabolism and Immune Microenvironment in Gastric Cancer and Identification of Its Characteristic Genes.

Cancer-associated fibroblasts (CAFs) have reported widely involved in cancer progression. However, its underlying mechanism in gastric cancer is still not clarified. The data used in this study were all downloaded from the Cancer Genome Atlas database. R software and the R packages were used for all the analyses. In our study, we first quantified the CAFs infiltration using the ssGSEA algorithm. The clinical correlation result showed that CAFs were associated with a worse prognosis and clinical features. Pathway enrichment also indicated several oncogenic pathways in GC patients with high CAFs infiltration, including epithelial-mesenchymal transition (EMT), myogenesis, allograft rejection, the inflammatory response, and IL2/STAT5 signaling. Furthermore, FNDC1 and RSPO3 were identified as the characteristic genes of CAFs through two machine learning algorithms, LASSO logistic regression and SVM-RFE. The following analysis showed that FNDC1 and RSPO3 were associated with more progressive clinical features and had a good prediction efficiency of the CAFs infiltration status in GC patients. Pathway enrichment and genomic instability were performed to explore the underlying mechanisms of FNDC1 and RSPO3. Immune infiltration analysis showed that CAFs were positively correlated with M2 macrophages. Moreover, we found that the GC patients with low CAFs infiltration were more sensitive to immunotherapy. Also, the CAFs, FNDC1, and RSPO3 could generate a certain effect on the sensitivity of doxorubicin, mitomycin, and paclitaxel. In summary, our study comprehensively investigated the role of CAFs in GC, which might be associated with immunotherapy sensitivity. Meanwhile, FNDC1 and RSPO3 were identified as the underlying targets of GC.

Identification and validation of signature for prognosis and immune microenvironment in gastric cancer based on m6A demethylase ALKBH5.

N6-methyladenosine (m6A) RNA regulators play important roles in cancers, but their functions and mechanism have not been demonstrated clearly in gastric cancer (GC). In this study, the GC samples with clinical information and RNA transcriptome were downloaded from The Cancer Genome Atlas database. The different expression genes were compared by the absolute value and median ± standard deviation. Samples with complete information were randomly divided into a training dataset and a test dataset. The differential expression genes (DEGs) between ALKBH5-low and ALKBH5-high subgroups were identified in the training dataset and constructed a risk model by Cox and least absolute shrinkage and selection operator regression. The model was testified in test datasets, overall survival (OS) was compared with the Kaplan-Meier method, and immune cell infiltration was calculated by the CIBERSORT algorithm in the low-risk and high-risk subgroups based on the model. The protein levels of ALKBH5 were detected with immunohistochemistry. The relative expression of messenger-ribonucleic acid (mRNA) was detected with quantitative polymerase chain reaction. ALKBH5 was the only regulator whose expression was lower in tumor samples than that in normal samples. The low expression of ALKBH5 led to the poor OS of GC patients and seemed to be an independent protective factor. The model based on ALKBH5-regulated genes was validated in both datasets (training/test) and displayed a potential capacity to predict a clinical prognosis. Gene Ontology analysis implied that the DEGs were involved in the immune response; CIBERSORT results indicated that ALKBH5 and its related genes could alter the immune microenvironment of GC. The protein levels of ALKBH5 were verified as lowly expressed in GC tissues. SLC7A2 and CGB3 were downregulated with ALKBH5 knockdown. In this study, we found that ALKBH5 might be a suppressor of GC; ALKBH5 and its related genes were latent biomarkers and immunotherapy targets.

Adverse effects of low serum lipoprotein cholesterol on the immune microenvironment in gastric cancer: a case‒control study

BackgroundCholesterol is crucial for tumor immune microenvironment (TIME) remodeling. Serum lipoprotein cholesterol is closely associated with gastric cancer (GC) progression, but whether it affects TIME remodeling is unknown.MethodsGC patients with differential serum high-density lipoprotein (HDL) or low-density lipoprotein (LDL) cholesterol levels were collected. After balancing the baseline, immunohistochemical staining was performed on serial whole-tissue sections to detect B-cell and T-cell subsets, macrophages, and PD-L1. Features of tertiary lymphoid structures (TLSs) and the extra-TLS zone, including TLS distribution and maturation, immune cell density, and PD-L1 expression, were measured by annotating TLSs or regions of interest (ROIs) in the extra-TLS zone.ResultsA total of 9,192 TLSs and over 300 ROIs from 61 patients were measured. Compared to HDL-normal patients, HDL-low patients had a decreased secondary-TLS fraction or density but an elevated NK-cell density in the extra-TLS zone. Compared to LDL-normal patients, LDL-low patients had a higher ratio of PD-1 + T follicular helper cells to CD20 + B cells in TLSs, a higher ratio of PD-1 + T cells to CD8 + T cells and increased PD-1 + T-cell density in the extra-TLS zone. Different correlations were found in groups with differential HDL or LDL levels. Cell dynamics in the immune response were weaker in patients with low lipoprotein cholesterol. TLS parameters reached their peak earlier than those of the extra-TLS zone along with tumor progression.ConclusionLow serum lipoprotein cholesterol caused adverse effects on antitumor immunity in GC. Lipid management or immunometabolic drugs deserve more attention.

Correlation analysis of lipid metabolism genes with the immune microenvironment in gastric cancer and the construction of a novel gene signature.

Lipid metabolism reprogramming plays an important role in cell growth, proliferation, angiogenesis and invasion of cancer. However, the prognostic value of lipid metabolism during gastric cancer (GC) progression and the relationship with the immune microenvironment are still unclear. The aim of this study was to clarify the correlation between lipid metabolism genes and GC immunity. We obtained 350 patients from The Cancer Genome Atlas (TCGA) and 355 patients from Gene Expression Omnibus (GEO) databases. Lipid metabolism-related gene datasets were obtained from the Reactome and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Molecular subtypes were obtained by Consensus clustering, and subtype immune status was analyzed using ESTIMATE, TIMER and microenvironmental cell population counter (MCP Counter) algorithm for immune analysis. Functional analyses included the application of Gene Set Enrichment Analysis (GSEA), KEGG, gene ontology (GO), and Protein-Protein Interaction Networks (PPI) to evaluate the molecular mechanisms of different subtypes. Weighted gene co-expression network analysis (WGCNA) was used to identify genes associated with immunity. The LASSO algorithm and multivariate Cox regression analysis were used to construct prognostic risk models. Based on the lipid metabolism genes found in GC, patients with GC can be divided into two subgroups with significantly different survival. The subgroup with a better prognosis presented higher immune scores and immune infiltrating cell abundance. 1170 immune-related genes were screened by WGCNA, and further screening by PPI network analysis revealed that PTPRC, CD4, ITGB2 and LCP2 were closely associated with immune cells. Combined with the TIDE score results, it was found that the population with high expression of the above genes might be more sensitive to immunotherapy. In addition, a survival prediction model for GC was developed based on five survival-related lipid metabolism genes, PIAS4, PLA2R1, PRKACA, SLCO1A2 and STARD4. The ROC analysis over time showed that the risk prediction score model had good stability. Lipid metabolism gene expression is correlated with the immune microenvironment in GC patients and can accurately predict their prognosis. Studies on lipid metabolism and GC immunity can help to screen the population for immunotherapy benefits.

Role of non-coding RNA in immune microenvironment and anticancer therapy of gastric cancer.

Gastric cancer remains one of the cancers with the highest mortality in the world; therefore, it is very important to investigate its pathogenesis to improve the prognosis of gastric cancer patients. Recently, noncoding RNAs have become a research hotspot in the field of oncology. These RNA molecules play complex roles in the regulation of tumor cells, immune cells, and the tumor microenvironment. Therefore, studying their ability to regulate the gastric cancer immune microenvironment will provide us with a better perspective to understand their potential role in anticancer therapy. In this review, we discuss the regulatory effects of several common noncoding RNAs on the immune microenvironment of gastric cancer and their prospects in anticancer therapy to provide some novel insight into the identification of valuable diagnostic markers and improving the prognosis of gastric cancer patients.