Cell Infiltration In Gastric Cancer Research Articles

YTHDF1 regulates immune cell infiltration in gastric cancer via interaction with p53.

The N6-methyladenosine reader YTH N6-methyladenosine RNA binding protein 1 (YTHDF1) has been assessed in several tumor types and holds significance in the tumor microenvironment (TME). Furthermore, p53, an important tumor suppressor, is closely associated with the TME. The present study evaluated the roles of YTHDF1 and p53 in regulating the TME in gastric cancer (GC). Genetic alterations in the YTH domain family were analyzed using the cBioPortal database. Expression of YTHDF1 in GC cells and tissues was assessed using the Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham Cancer data analysis portal and Tumor-Immune System Interactions and Drug Bank (TISIDB) databases, along with reverse-transcription-quantitative PCR and western blotting in GC. The prognostic value of multiple tumors was determined using Kaplan-Meier analysis. Correlation analyses were performed using the TIMER, TISIDB and GEPIA databases. Protein-protein interactions of YTHDF1 were predicted using GeneMANIA and HitPredict, and confirmed using co-immunoprecipitation. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the YTHDF1 functional network in GC were performed using LinkedOmics. Genetic alterations revealed that, among the YTH domain family members, YTHDF1 had the highest alteration in GC and was associated with a shorter survival. Additionally, YTHDF1 was significantly negatively associated with the level of CD8+ T cells, B cells, macrophages, dendritic cells (DCs) and neutrophils in GC. Furthermore, tumor associate macrophage-related and DC markers were significantly negatively correlated with YTHDF1 expression, whilst regulatory T cells and T cell exhaustion markers were significantly negatively associated with YTHDF1 expression. In addition, compared with that in p53-nonmutant GC cells, YTHDF1 expression was significantly higher in p53-mutated GC cells, indicating a potential association between YTHDF1 and p53. Analyses using the GeneMANIA and HitPredict databases, and co-immunoprecipitation, demonstrated that YTHDF1 interacted with p53. In conclusion, the findings of the present study indicate that YTHDF1 is associated with a poor prognosis and serves an important role in the TME of GC. We hypothesize, for the first time to the best of our knowledge, that YTHDF1 regulates immune cell infiltration by interacting with p53 in GC, which provides a promising direction for future research.

GLT8D2 is a prognostic biomarker and regulator of immune cell infiltration in gastric cancer

GLT8D2 is a prognostic biomarker and regulator of immune cell infiltration in gastric cancer

Identification of Key lncRNAs Associated with Immune Infiltration and Prognosis in Gastric Cancer.

Long non-coding RNAs (lncRNAs), as promising novel biomarkers for cancer treatment and prognosis, can function as tumor suppressors and oncogenes in the occurrence and development of many types of cancer, including gastric cancer (GC). However, little is known about the complex regulatory system of lncRNAs in GC. In this study, we systematically analyzed lncRNA and miRNA transcriptomic profiles of GC based on bioinformatics methods and experimental validation. An lncRNA-miRNA interaction network related to GC was constructed, and the nine crucial lncRNAs were identified. These 9 lncRNAs were found to be associated with the prognosis of GC patients by Cox proportional hazards regression analysis. Among them, the expression of lncRNA SNHG14 can affect the survival of GC patients as a potential prognostic marker. Moreover, it was shown that SNHG14 was involved in immune-related pathways and significantly correlated with immune cell infiltration in GC. Meanwhile, we found that SNHG14 affected immune function in many cancers, such as breast cancer and esophageal carcinoma. Such information revealed that SNHG14 may serve as a potential target for cancer immunotherapy. As well, our study could provide practical and theoretical guiding significance for clinical application of non-coding RNAs.

TCHH as a Novel Prognostic Biomarker for Patients with Gastric Cancer by Bioinformatics Analysis.

This study aims to investigate the clinicopathological significance and prognostic value of Trichohyalin (TCHH) in gastric cancer patients through bioinformatics analysis. Data on TCHH expression and clinicopathological information were sourced from The Cancer Genome Atlas (TCGA). The Wilcoxon signed-rank test was used for evaluating the correlation between TCHH mRNA expression levels and clinicopathological features. The predictive significance of TCHH mRNA expression for overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in patients with gastric cancer was assessed using Cox regression models. Furthermore, measures of immune cell infiltration in gastric cancer were made, and studies of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were also carried out to investigate the possible roles of TCHH in patients with gastric cancer. Compared to normal tissues, gastric cancer had a considerably higher expression of TCHH mRNA (P < 0.05). Wilcoxon analysis revealed a significant association between TCHH mRNA expression and the pathologic M stage (P = 0.017). High TPMT mRNA levels were also correlated with worse OS, DFS, and PFI in gastric cancer patients (both P < 0.05). TCHH showed significant negative correlations with the levels of NK CD56dim infiltration (r = -0.157, p = 0.002), Th17 cells infiltration (r = -0.235, P < 0.001), and Th2 infiltration (r = -0.195, P < 0.001). Furthermore, enrichment analysis indicated potential involvement in intermediate filament cytoskeleton organization, DNA methylation in gamete generation, cell-cell recognition, and G protein-coupled peptide receptor (GPCRs) activity. The level of TCHH mRNA may serve as a novel prognostic biomarker for gastric cancer patients.

Retracted: Bioinformatic Analysis of PTTG Family and Prognosis and Immune Cell Infiltration in Gastric Cancer.

[This retracts the article DOI: 10.1155/2023/6905216.].

CPXM1 correlates to poor prognosis and immune cell infiltration in gastric cancer

BackgroundGastric cancer (GC) is the fourth most common cause of cancer-related death and the fifth most frequent malignant cancer, especially advanced GC. Carboxypeptidase X member 1 (CPXM1) is an epigenetic factor involved in many physiological processes, including osteoclast differentiation and adipogenesis. Several studies have shown the association of CPXM1 with multiple tumors; however, the mechanism of CPXM1 involvement in the progression of GC is yet to be characterized. MethodCPXM1 expression data were obtained from the Tumor Immune Estimation Resource. The Cancer Genome Atlas and the Gene Expression Omnibus databases were used to obtain patient-matched clinicopathological information, and the Kaplan–Meier plot database was utilized for the prognosis analysis of GC patients. The Catalog of Somatic Mutations in Cancer and cBioportal databases were adopted to study CPXM1 mutations in tumors. Next, we utilized the Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis for mechanism research. Furthermore, we performed tumor microenvironment and immune infiltration analysis based on CPXM1. Finally, we predicted sensitivity to several targeted drugs in GC patients based on CPXM1.CPXM1 is upregulated in GC and is correlated with poor prognosis, gender, and tumor stage in GC patients. Gene enrichment analysis suggested that CPXM1 may regulate the occurrence and progression of GC via the PI3K–AKT and TGF-β pathway. Moreover, CPXM1 expression results in an increase in the proportion of immune and stromal cells. Additionally, the proportion of plasma cells was inversely related to the expression of CPXM1, whereas macrophage M2 expression was proportionate to CPXM1 expression. Finally, six small-molecule drugs that showed notable variations in IC50 between two groups were screened. ConclusionThese results suggested that CPXM1 regulates the progression of GC and may represent a novel target for the detection and treatment of GC.

Bioinformatics analysis and experimental validation of tumorigenic role of PPIA in gastric cancer

Gastric cancer (GC) is a malignant tumor with high incidence rate and mortality. Due to the lack of effective diagnostic indicators, most patients are diagnosed in late stage and have a poor prognosis. An increasing number of studies have proved that Peptidylprolyl isomerase A (PPIA) can play an oncogene role in various cancer types. However, the precise mechanism of PPIA in GC is still unclear. Herein, we analyzed the mRNA levels of PPIA in pan-cancer. The prognostic value of PPIA on GC was also evaluated using multiple databases. Additionally, the relationship between PPIA expression and clinical factors in GC was also examined. We further confirmed that PPIA expression was not affected by genetic alteration and DNA methylation. Moreover, the upstream regulator miRNA and lncRNA of PPIA were identified, which suggested that LINC10232/miRNA-204-5p/PPIA axis might act as a potential biological pathway in GC. Finally, this study revealed that PPIA was negatively correlated with immune checkpoint expression, immune cell biomarkers, and immune cell infiltration in GC.

M6A reader YTHDF3 is associated with clinical prognosis, related RNA signatures and immunosuppression in gastric cancer

BackgroundYTHDF3 as a N6-methyladenosine (m6A) reader participates in the development and progression of multiple cancer types, however, the prognosis, molecular biology and immune infiltration of YTHDF3 in gastric cancer (GC) have not been investigated. MethodsThe YTHDF3 expression profile and clinicopathological parameters of stomach adenocarcinoma (STAD) were downloaded from TCGA. The online websites and databases such as GEPIA2, cBioPortal, UALCAN, ImmuCellAl, xCell, TISIDB, GSCA were utilized for analysis of the association of YTHDF3 with STAD, including clinical prognosis, WGCNA and LASSO Cox regression analysis. Further functional assays such as RT-qPCR, Western blot, immunohistochemistry (IHC), immunofluorescence (IF), CCK-8, colony formation, EdU and Transwell assays were performed to determine the role of YTHDF3 in GC. ResultsWe found that YTHDF3 was upregulated in STAD tissue samples ascribed to its copy number amplification and associated with poor prognosis in patients with STAD. GO and KEGG analyses showed that YTHDF3-related differential genes were predominantly enriched in the proliferation, metabolism and immune signaling pathways. Knockdown of YTHDF3 repressed the growth and invasion of GC cells by inhibition of PI3K/AKT signaling. We then identified YTHDF3-related lncRNAs, miRNAs and mRNAs, and constructed their prognostic signatures in patients with STAD. Moreover, YTHDF3 associated with tumor immune infiltration such as CD8+ T cells, macrophages, Tregs, MHC molecules and chemokines, upregulated PD-L1 and CXCL1 and exerted a response to the immunotherapy in GC. ConclusionsYTHDF3 upregulation indicates poor prognosis and promotes GC cell growth and invasion by activating PI3K/AKT pathway and regulating immune microenvironment. The established YTHDF3-related signatures highlight the association of YTHDF3 with the clinical prognosis and immune cell infiltration in GC.

Bioinformatic Analysis of PTTG Family and Prognosis and Immune Cell Infiltration in Gastric Cancer.

Gastric cancer is the sixth highest incidence rate in the world. Although treatment has made progress, the prospect of gastric cancer patients is bleak. Difficulties and future prospects of immunotherapy in cancer treatment. Adaptive cell therapy, cancer vaccines, gene therapy, and monoclonal antibody therapy have all been used in gastric cancer with some initial success. PTTGs (pituitary tumor-transforming genes) have been proven to be closely related to the prognosis of many malignant tumors. However, the prognosis and immune cell infiltration of gastric adenocarcinoma (STAD) remain unclear. We retrieved multiple databases to understand the possible activity of PTTGs and their expression in gastric cancer, as well as their relationship with clinical data, overall survival rate, first progression, and survival rate after progression. PTTGs are overexpressed in STAD tumor tissues. Many clinical variables are closely related to PTTGs. In addition, PTTG was associated with overall survival independent of disease. In addition, the expression of PTTG1/2 was positively correlated with the molecular status of the immune checkpoint and negatively correlated with the infiltration of various immune cells. Data research shows that PTTG and STAD are closely related. This paved the way for future research, revealed the complex pathophysiology of gastric cancer, and introduced an effective new treatment.

Lipid Metabolic-Related Signature CYP19A1 is a Potential Biomarker for Prognosis and Immune Cell Infiltration in Gastric Cancer.

BackgroundAltered lipid metabolism is associated with gastric cancer (GC) progression. Comprehensive analysis to identify critical lipid metabolic drivers for predicting overall survival (OS) is not fully elucidated in GC. Our study aim to explore a novel lipid metabolism-related prognostic marker for GC.MethodsTranscriptional status and clinical features were obtained from the TCGA-STAD database. The differentially expressed lipid metabolic genes and the risk prognostic model were developed by using bioinformatics and Cox regression analyses. ROC and Kaplan–Meier analysis were established to assess the performance of the risk predictive score model. GSE84437 dataset was used for external validation. Immunochemistry (IHC) was used to examine the expression of CYP19A1 in GC patients. Gene Set Enrichment Analysis (GSEA) was conducted to elucidate the underlying enriched mechanisms. TIMER and CIBERSORT analysis were performed to explore the relationship between CYP19A1 and immune microenvironment.ResultsA novel lipid metabolic gene signature (including MTTP, CYP19A1, MYB, SERPINE1), and specifically CYP19A1, might be a promising prognostic factor for GC. Using the validation cohort, ROC curves indicate a good showing of our risk model. Based on the signature yielded a significant difference OS time between the low- and high-risk groups. Cox regression indicates that the signature is an independent prognostic variable. ROC curves present better and reliability predictive accuracy. The IHC data validate that high expression of CYP19A1 was found in GC tissues. GSEA analysis reveals that higher expression of CYP19A1 may significantly up-regulate genes involved in fatty acid metabolism and glycerolipid metabolism. CIBERSORT analysis suggests that CYP19A1 is related to the infiltration of multiple immune cells.ConclusionCYP19A1 could be an independent prognostic factor and a novel metabolic-targeted treatment strategy for gastric cancer.

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.

Abstract 5013: Integrated analysis of intragastric microbiome and human gene expression uncovers genetic, microbial, and immunological associations in gastritis and gastric cancer

Abstract Background: Gastric carcinogenesis has been found to be associated with intragastric microbiome, gastric mucosal gene expression, and immune cells comprising the tumor microenvironment separately in independent studies. However, to date, there has been no multi-omic investigations analyzing these biological traits simultaneously. Thus, there is a paucity in our understanding of the intricate relationship between intragastric microbes and the host in gastric disease. To address this gap, we aimed to comprehensively investigate the microbiome, host gene expression, and immune cells in the stomach across a range of different states along the gastric carcinogenesis pathway. Methods: Gastric biopsy samples were obtained from healthy individuals or patients with gastritis or gastric cancer (biopsy cohort, n=30). Surgical samples (of cancer and adjacent severe gastritis tissues) were obtained from gastric cancer patients (surgery cohort, n=40). Using 16S rRNA gene sequencing, RNA-seq, and cell-type enrichment analysis of each participant’s biospecimens, we identified associations between the microbiome and host transcriptome or inferred immune cell types. Results: Microbiome composition and gene expression patterns showed significant differences between disease states (healthy, gastritis, or cancer). Expression of ‘Cell cycle’ pathway genes was enriched in gastric cancer in both biopsy and surgery cohorts. In the biopsy cohort, Helicobacteraceae, which was abundant in gastritis, was highly correlated with FAM3D, which was previously found to be involved in gastrointestinal inflammation. In the surgery cohort, Lachnospiraceae, which was abundant in gastric cancer, was highly correlated with UBD, which is known to regulate mitosis and reduce cell cycle time. Cell-type enrichment analysis revealed lower B cell infiltration in gastric cancer than in gastritis (both cohorts). Tissue-infiltrating B cells were associated with Helicobacteraceae. Conclusions: Associations between the intragastric microbiome, human gene expression, and tissue-infiltrating immune cells are unique to gastric disease state. The findings herein may aid the discovery of novel biomarkers or therapeutic targets of gastric cancer. Citation Format: Chan Hyuk Park, Changjin Hong, A-reum Lee, Jaeyun Sung, Tae Hyun Hwang. Integrated analysis of intragastric microbiome and human gene expression uncovers genetic, microbial, and immunological associations in gastritis and gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5013.

Relationship Between CNVs and Immune Cells Infiltration in Gastric Tumor Microenvironment

Gastric cancer (GC) is a highly fatal and common malignancy of the digestive system. Recent therapeutic advancements have significantly improved the clinical outcomes in GC, but due to the unavailability of suitable molecular targets, a large number of patients do not respond to the immune checkpoint inhibitors (ICI) therapy. To identify and validate potential therapeutic and prognostic targets of gastric cancer, we used the “inferCNV” R package for analyzing single-cell sequencing data (GSE112302) of GC and normal epithelial cells. First, by using LASSO, we screened genes that were highly correlated with copy number variations (CNVs). Therefrom, five gene signature (CPVL, DDC, GRTP1, ONECUT2, and PRSS21) was selected by cross-validating the prognosis and risk management with the GC RNA-seq data obtained from GEO and TCGA. Moreover, the correlation analyses between CNVs of these genes and immune cell infiltration in gastric cancer identified CPVL as a potential prognostic marker. Finally, CPVL showed high expression in gastric cancer samples and cell lines, then siRNA-mediated silencing of CPVL expression in gastric cancer cells showed significant proliferation arrest in MGC803 cells. Here, we conclude that CNVs are key regulators of the immune cells infiltration in gastric TME as well as cancer development, and CPVL could potentially be used as a prognostic and therapeutic marker in gastric cancer.

Prognostic biomarker HAMP and associates with immune infiltration in gastric cancer

BackgroundGastric cancer remains one of the most common malignant tumors and has high morbidity and mortality rates. Hepcidin, as a peptide hormone, plays a vital role in regulating systemic iron homeostasis. Nevertheless, the clinical predictive value of HAMP, especially its correlation with immune cell infiltration in gastric cancer, has not yet been elucidated. MethodsHAMP expression in gastric cancer cells and tissues was assessed using experiments and bioinformatics platforms. Clinical and pathologic information was collected to stratify patients with gastric cancer for comparison. We used Kaplan-Meier and Cox regression methods to explore the association between HAMP expression levels and overall survival. Based on “The Cancer Genome Atlas” datasets, we analyzed whether HAMP expression is associated with immune cell infiltration levels and evaluated the prognostic impact of HAMP on survival of patients with gastric cancer partially through immune cell infiltration. ResultsHAMP mRNA was more highly expressed in gastric cancer cells and tumor tissues than in normal tissues. Moreover, elevated HAMP expression was correlated with poor overall survival. In addition, HAMP expression was related to sex, tumor stage, node stage, metastasis stage, Lauren classification, and differentiation in stratified patients. Notably, HAMP gene expression was found to be significantly related to the infiltration levels of immune cells, and that HAMP affects the survival rate in gastric cancer through the immune pathway. ConclusionHigh HAMP expression may serve as an independent prognostic biomarker through the immune pathway in patients with gastric cancer.

Comprehensive Analysis of PDLIM3 Expression Profile, Prognostic Value, and Correlations with Immune Infiltrates in Gastric Cancer.

Protein PDZ and LIM domain 3 (PDLIM3) is a cytoskeletal protein, colocalizing with α-actinin on the Z line of mature muscle fibers. It plays a key role in dilated cardiomyopathy (DCM), muscular dystrophy, and tumor progression. However, correlations between PDLIM3 expression, prognosis, and tumor-infiltrating immune cells in gastric cancer are unknown. Therefore, we leveraged the Oncomine, GEPIA, GEO, and HPA databases to evaluate PDLIM3 expression in tumors. We also quantified PDLIM3 expression in 15 matched pairs of gastric tumor and nontumor tissues by immunohistochemistry. The Kaplan-Meier method was employed to determine the relationship between PDLIM3 expression and clinical outcomes. GO and KEGG analyses were performed to illuminate the molecular mechanisms of action of PDLIM3. TIMER2.0 and GEPIA were applied to investigate correlations between PDLIM3 expression and gene marker subsets signifying immune infiltration, with TIMER2.0 exploring the correlations between PDLIM3 and related signaling pathways. Gastric cancer tissues were found to express more PDLIM3 than nontumor tissues. PDLIM3 overexpression was associated with shorter OS and PFS of gastric cancer patients (OS HR = 2.02, P = 9.8e − 10; PFS HR = 1.77, P = 7.5e − 06). PDLIM3 was also positively correlated with worse OS and PFS according to gastric cancer staging, Her-2 overexpression, differentiation grade, and Lauren classification. PDLIM3 was shown to be associated with immunological responses by GO, while it was related to PI3K/Akt signal pathways by KEGG analysis. Furthermore, increased PDLIM3 expression was significantly correlated with greater infiltration of CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells. PDLIM3 expression had significant positive correlations with a variety of immune marker subsets. Finally, correlations were found between PDLIM3 and crucial markers of signaling pathways involving PI3K/Akt and p38 MAPK. Thus, upregulation of PDLIM3 was significantly associated with poor prognosis, immune cell infiltration, and activation of two key signal pathways in gastric cancer. We propose that PDLIM3 could be used as a biomarker to predict prognosis and immune cell infiltration in gastric cancer.

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.

Identification of GGT5 as a Novel Prognostic Biomarker for Gastric Cancer and its Correlation With Immune Cell Infiltration.

Gastric cancer (GC) is a common malignant tumor of the digestive system. Recent studies revealed that high gamma-glutamyl-transferase 5 (GGT5) expression was associated with a poor prognosis of gastric cancer patients. In the present study, we aimed to confirm the expression and prognostic value of GGT5 and its correlation with immune cell infiltration in gastric cancer. First, we compared the differential expression of GGT5 between gastric cancer tissues and normal gastric mucosa in the cancer genome atlas (TCGA) and GEO NCBI databases using the most widely available data. Then, the Kaplan-Meier method, Cox regression, and univariate logistic regression were applied to explore the relationships between GGT5 and clinical characteristics. We also investigated the correlation of GGT5 with immune cell infiltration, immune-related genes, and immune checkpoint genes. Finally, we estimated enrichment of gene ontologies categories and relevant signaling pathways using GO annotations, KEGG, and GSEA pathway data. The results showed that GGT5 was upregulated in gastric cancer tissues compared to normal tissues. High GGT5 expression was significantly associated with T stage, histological type, and histologic grade (p < 0.05). Moreover, gastric cancer patients with high GGT5 expression showed worse 10-years overall survival (p = 0.008) and progression-free intervals (p = 0.006) than those with low GGT5 expression. Multivariate analysis suggested that high expression of GGT5 was an independent risk factor related to the worse overall survival of gastric cancer patients. A nomogram model for predicting the overall survival of GC was constructed and computationally validated. GGT5 expression was positively correlated with the infiltration of natural killer cells, macrophages, and dendritic cells but negatively correlated with Th17 infiltration. Additionally, we found that GGT5 was positively co-expressed with immune-related genes and immune checkpoint genes. Functional analysis revealed that differentially expressed genes relative to GGT5 were mainly involved in the biological processes of immune and inflammatory responses. In conclusion, GGT5 may serve as a promising prognostic biomarker and a potential immunological therapeutic target for GC, since it is associated with immune cell infiltration in the tumor microenvironment.

Development and verification of a microsatellite instability-related risk signature for predicting survival and therapy effectiveness in gastric cancer.

Gastric cancer (GC) is one of is one of the most common malignancy among digestive system cancers worldwide. Increasing evidence has revealed that microsatellite instability (MSI) status can affect the survival in various cancers. However, the role of MSI status in GC remains uncertain. The RNA-seq and clinicopathological features and mutation data of GC was obtained from The Cancer Genome Atlas (TCGA). Different bioinformatic and statistical methods were combined to construct a robust MSI-related gene signature for prognosis. Gene set enrichment analysis was conducted to explore Kyoto Encyclopedia of Genes and Genomes pathways associated with the MSI-related risk signature. Moreover, Kaplan-Meier (K-M) survival and receiver operating characteristic (ROC) analyses evaluate that the MSI-related risk signature. Immune-associated miRNAs were identified using immune scores calculated by the ssGSEA. In addition, 'pRRophetic' R package was used to assess the chemotherapeutic response by the GDSC website. We firstly analyzed the influence of MSI status to GC survival based on the data from the TCGA database. GC patients in the TCGA database were divided into MSI-H and MSI-L/MSS groups. We counted the survival conditions of GC patients in these two groups. In addition, we also calculated the difference of TMB between these two groups and found that MSI-H group had a relatively high survival rate. Next, we identified 99 highly mutated genes in MSI-H group and constructed a MSI-related risk signature based on 10 robust genes for predicting the overall survival (OS) of GC patients. Moreover, analyses indicated that the MSI-related risk signature can accurately predict 1-, 3- and 5-year OS of GC patients. Furthermore, enrichment analysis suggested that genes between the high- and low-risk groups mainly involved in mutation and DNA repair related pathways. Finally, we also found that the MSI-related risk signature can affect the TME immune cell infiltration in GC and can be used to predict the clinical response to immunotherapy. In the present study, we develop a MSI-related risk signature for predicting the survival and therapy of GC, which may contribute to the clinical treatment of GC.

Progesterone receptor gene serves as a prognostic biomarker associated with immune infiltration in gastric cancer: a bioinformatics analysis.

BackgroundGastric cancer (GC) is one of the most prevalent cancers globally with a poor prognosis. The progesterone receptor gene (PGR), which encodes the progesterone receptor (PR), can modulate the immune response in many cancers, but its correlation with prognosis and immune infiltration in GC remains unclear. We aimed to investigate the relationship between PGR expression and prognosis in GC patients.MethodsThe expression profile was obtained and the relationship between PGR expression and cancer prognosis was analyzed by Oncomine, Tumor Immune Estimation Resource (TIMER), Kaplan-Meier plotter, the PrognoScan database and Gene Expression Profiling Interactive Analysis (GEPIA) database using the minimum P value approach and log-rank method for prognosis analysis. Next, the correlation between the expression level of PGR and immune cell infiltration by the Spearman method using TIMER and GEPIA.ResultsA correlation of elevated PGR expression with poorer prognosis in GC was observed, with overall survival (OS) hazard ratio (HR) was 1.74 [95% confidence interval (CI): 1.4–2.17, P value =6.2e-7] and progression-free survival (PFS) HR was 2.09 (95% CI: 1.58–2.78, P value =1.6e-7). Also, high expression of PGR was related to worse OS and PFS in patients of each N stage in GC, with the highest OS and PFS HR values in stage N1. PGR expression in stomach adenocarcinoma (STAD) was significantly correlated with levels of B cells, CD8+T cells, CD4+T cells, macrophages, neutrophils and dendritic cells. It was also observed that PGR expression was related to a variety of immune cell markers.ConclusionsPGR expression correlated with prognosis and immune cell infiltration in GC, indicating PGR is a potential prognostic biomarker in GC patients.

The Human Cytomegalovirus US31 Gene Predicts Favorable Survival and Regulates the Tumor Microenvironment in Gastric Cancer.

Human cytomegalovirus (HCMV) is an oncogenic virus associated with tumorigenesis. Our previous study revealed that the HCMV US31 gene interacted with NF-κB2 and mediated inflammation through macrophages. However, there are few reports on the role of US31 in gastric cancer (GC). The aim of this study was to investigate the expression of the US31 gene in GC tissue and assess its role in the occurrence and development of GC. US31 expression in 573 cancer tissues was analyzed using immunohistochemistry. Results showed that US31 was significantly associated with tumor size (P = 0.005) and distant metastasis (P < 0.001). Higher US31 expression indicated better overall survival in GC patients. Overexpression of US31 significantly inhibited the proliferation, migration, and invasion of GC cells in vitro (P < 0.05). Furthermore, expression levels of CD4, CD66b, and CD166 were positively correlated with US31, suggesting that it was involved in regulating the tumor immune microenvironment of GC. RNA sequencing, along with quantitative real-time polymerase chain reaction, confirmed that the expression of US31 promoted immune activation and secretion of inflammatory cytokines. Overall, US31 inhibited the malignant phenotype and regulated tumor immune cell infiltration in GC; these results suggest that US31 could be a potential prognostic factor for GC and may open the door for a new immunotherapy strategy.