Infiltration In Gastric Cancer Research Articles

Pan-cancer analysis of SERPINE1 with a concentration on immune therapeutic and prognostic in gastric cancer.

The serine protease inhibitor clade E member 1 (SERPINE1) is a key modulator of the plasminogen/plasminase system and has been demonstrated to promote tumor progression and metastasis in various tumours. However, although much literature has explored the cancer-promoting mechanism of SERPINE1, the pan-cancer analyses of its predictive value and immune response remain unexplored. The differential expression, and survival analysis of SERPINE1 expression in multiple cancers were analysed using The Cancer Genome Atlasand Genotype-Tissue Expression database. Kaplan-Meier (K-M) plotter and survival data analysis were used to analyze the prognostic value of SERPINE1 expression, including overall survival (OS), disease-specific survival, disease-free interval and progression-free interval and investigated the relationship of SERPINE1 expression with microsatellite instability. We further analysed the correlation between the expression of SERPINE1 and immune infiltration. The Kyoto Encyclopaedia of Genes and Genomes pathway was used for enrichment analysis, and the Gene Set Enrichment Analysis (GSEA) database was used to perform pathway analysis. Finally, invitro experiments demonstrated that knockdown or overexpression of SERPINE1 could alter the proliferation and migration of gastric cancer (GC) cells. The results indicated that SERPINE1 expression levels different significantly between cancer and normal tissues, meanwhile, it was highly expressed in various cancers. By analysing online data, it has been observed that the gene SERPINE1 exhibits heightened expression levels across a variety of human cancers, significantly impacting patient survival rates. Notably, the presence of SERPINE1 was strongly associated with decrease OS and disease-free survival in individuals diagnosed with GC. Furthermore, an observed link indicates that higher levels of SERPINE expression are associated with increased infiltration of immune cells in GC. Finally, invitro experiments showed that knockdown or overexpression of SERPINE1 inhibited the growth, and migration, of GC cells. SERPINE1expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in GC. This study shows that SERPINE1 is an oncogene that participates in regulating the immune infiltration and affecting the prognosis of patients in multiple cancers, especially in GC. These findings underscore the importance of further investigating the role of SERPINE1 in cancer progression and offer a promising direction for the development of new therapeutic strategies.

Glycolysis-related five-gene signature correlates with prognosis and immune infiltration in gastric cancer.

Gastric cancer (GC) is one of the most common malignancies worldwide. Glycolysis has been demonstrated to be pivotal for the carcinogenesis of GC. To develop a glycolysis-based gene signature for prognostic evaluation in GC patients. Differentially expressed genes correlated with glycolysis were identified in stomach adenocarcinoma data (STAD). A risk score was established through a univariate Cox and least absolute shrinkage and selection operator analysis. The model was evaluated using the area under the receiver operating characteristic curves. RNA-sequencing data from high- and low-glycolysis groups of STAD patients were analyzed using Cibersort algorithm and Spearman correlation to analyze the interaction of immune cell infiltration and glycolysis. Multiomics characteristics in different glycolysis status were also analyzed. A five-gene signature comprising syndecan 2, versican, malic enzyme 1, pyruvate carboxylase and SRY-box transcription factor 9 was constructed. Patients were separated to high- or low-glycolysis groups according to risk scores. Overall survival of patients with high glycolysis was poorer. The sensitivity and specificity of the model in prediction of survival of GC patients were also observed by receiver operating characteristic curves. A nomogram including clinicopathological characteristics and the risk score also showed good prediction for 3- and 5-year overall survival. Gene set variation analysis showed that high-glycolysis patients were related to dysregulation of pancreas beta cells and estrogen late pathways, and low-glycolysis patients were related to Myc targets, oxidative phosphorylation, mechanistic target of rapamycin complex 1 signaling and G2M checkpoint pathways. Tumor-infiltrating immune cells and multiomics analysis suggested that the different glycolysis status was significantly correlated with multiple immune cell infiltration. The patients with high glycolysis had lower tumor mutational burden and neoantigen load, higher incidence of microsatellite instability and lower chemosensitivity. High glycolysis status was often found among patients with grade 2/3 cancer or poor prognosis. The genetic characteristics revealed by glycolysis could predict the prognosis of GC. High glycolysis significantly affects GC phenotype, but the detailed mechanism needs to be further studied.

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

Because of the considerable tumor heterogeneity in gastric cancer (GC), only a limited group of patients experiences positive outcomes from immunotherapy. Herein, we aim to develop predictive models related to glycosylation genes to provide a more comprehensive understanding of immunotherapy for GC. RNA sequencing (RNA-seq) data and corresponding clinical outcomes were obtained from GEO and TCGA databases, and glycosylation-related genes were obtained from GlycoGene DataBase. We identified 48 differentially expressed glycosylation-related genes and established a prognostic model (seven prognosis genes including GLT8D2, GALNT6, ST3GAL6, GALNT15, GBGT1, FUT2, GXYLT2) based on these glycosylation-related genes using the results from Cox regression analysis. We found that these glycosylation-related genes revealed a robust correlation with the abundance of Tumor Infiltrating Lymphocytes (TILs), especially the GLT8D2 which is associated with many TILs. Finally, we employed immunohistochemistry and Multiplex Immunohistochemical to discover that GLT8D2 serves as a valuable prognostic biomarker in GC and is closely associated with macrophage-related markers. Collectively, we established a prognostic model based on glycosylation-related genes to provide a more comprehensive understanding of prediction for GC prognosis, and identified that GLT8D2 is closely correlated with adverse prognosis and may underscore its role in regulating immune cell infiltration in GC patients.

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.

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.

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.

Abstract 271: The effects of B-cell acute lymphoblastic leukemia cells on the adipose tissue microenvironment

Abstract Obesity increases the risk of developing many cancers, including breast, colon, kidney, and acute lymphoblastic leukemia (ALL). We have previously shown that ALL cells are recruited to migrate into adipose tissue, where they are protected from chemotherapy. In vitro, ALL cells induce significant changes in adipocytes which may contribute to these protective effects. However, how ALL cells affect the complex cell populations found in adipose tissue in vivo remains unknown. We therefore conducted single-cell RNA sequencing (scRNAseq) of the non-adipocyte stromal vascular fraction (SVF) from adipose tissue in obese mice with and without implanted syngeneic BCR-ABL positive ALL. Differential expression analysis was performed on individual SVF cell types to compare ALL vs. control adipose tissue and pathway enrichment analysis was used in identifying altered molecular processes between conditions. SVF from leukemic mice showed substantial differences in gene expression compared to control mice, suggesting that the ALL potentially induces changes in the microenvironment. Some of the largest differences were found in adipose tissue macrophages, and pathway enrichment analysis identified neutrophil recruitment and regulation as one of the top ten pathways upregulated in adipose macrophages from leukemic mice (4.10 fold enrichment, p&amp;lt;1 × 10-17 by Fisher’s exact test). Selected macrophage genes of interest in this pathway included CYBB (Cytochrome B-245 Beta), a neutrophil interaction gene that has been associated with macrophage infiltration in gastric cancer, was expressed 2.28 log2-fold higher in macrophages from leukemic compared to nonleukemic mice (p&amp;lt;1 × 10−99 by Wilcoxon test). ITGAL (Integrin subunit alpha L), which has been shown to be involved in neutrophil recruitment and implicated in cancer cell growth and transformation was expressed 2.85 log2-fold higher in macrophages from leukemic mice (p&amp;lt;1 × 10−99). Interestingly, adipose from leukemic mice showed a population of neutrophils (1.9% of SVF cells), while neutrophils were largely absent in adipose from nonleukemic mice (&amp;lt;0.1% of SVF cells), which is consistent with macrophage involvement in neutrophil recruitment. Our findings highlight the importance of adipose tissue in the leukemia microenvironment and show that ALL cells can influence this microenvironment in complex ways. Further work will confirm and investigate these cell-cell interactions, potentially improving our understanding of how adipose tissue contributes to cancer mortality. Citation Format: Jia Tan, Michael Cohen, Jessica Ding, In Sook Ahn, Xia Yang, Steven D. Mittelman. The effects of B-cell acute lymphoblastic leukemia cells on the adipose tissue microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 271.

Abstract 2570: Gastric cancer with high neuron infiltration was associated with enhanced epithelial-to-mesenchymal transition, angiogenesis and poor clinical outcomes

Abstract Introduction: Neurons within the tumor microenvironment of gastric cancer (GC), as identified through immunohistochemistry, have been reported to be associated with worse overall survival (OS) of GC patients. However, histology-based analyses have limitations in quantifying nerve cells and investigating the underlying biology. Thus, we aim to study the clinical significance of intratumoral nerve cells in GC using computational deconvolution of transcriptomes from bulk tumors. Methods: Total of 807 GC patients from two independent cohorts (TCGA; n = 375, GSE84437; n = 432) were included, encompassing both clinical and transcriptomic profiles. The neuron infiltration fraction was determined using the xCell algorithm. Results: GC with high neuron infiltration was associated with high expressions of neurotransmitter receptors; beta-adrenaline, dopamine, muscarinic acetylcholine, and neurokinin receptors in TCGA cohort (all p &amp;lt; 0.02). It was associated with reduced mutation rate and increased intratumoral heterogeneity (all p ≦ 0.002), as well as less immune response; interferon-alpha and interferon-gamma, and with low infiltration of immune cells; CD4 memory, T-helper 1, M1 and M2 macrophages, and NK cells (all p ≦ 0.02). Further, neuron highly infiltrated GC enriched Epithelial-to-Mesenchymal Transition and Angiogenesis gene sets and had higher lymphatic and microvessel endothelial cells and pericyte infiltrations (all p ≦ 0.001). Conversely, GC with high neuron infiltration showed an inverse relationship with cell proliferation-related gene sets; E2F Targets, G2M Checkpoint, and MYC Targets v1 and v2, and had lower Ki67 gene expression (FDR &amp;lt; 0.25 and p &amp;lt; 0.001, respectively). High neuron infiltration in GC was associated with worse patient OS in TCGA cohort, which was validated in GSE84437 cohort (both p &amp;lt; 0.05). It was an independent prognostic factor of OS in both univariate and multivariate Cox-regression analysis in the TCGA cohort (hazard ratio [HR]: 1.46; 95% confidence interval [CI]: 1.01 to 2.12; p = 0.045 and [HR]:1.54; 95% CI: 1.05 to 2.26; p = 0.026). Conclusion: Our research indicates that high infiltration of neurons in GC correlates with high expressions of neurotransmitter receptors, high intratumoral heterogeneity, less immune response and immune cell infiltrations, and less cell proliferation. It enriched EMT and angiogenesis which may explain its association with worse patient survival. Citation Format: Kohei Chida, Masanori Oshi, Arya Mariam Roy, Jun Arima, Pia Sharma, Gabriella Kim Mann, Itaru Endo, Kenichi Hakamada, Kazuaki Takabe. Gastric cancer with high neuron infiltration was associated with enhanced epithelial-to-mesenchymal transition, angiogenesis and poor clinical outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2570.

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.

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.].

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.

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.

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.