Chemokine receptor 4 expression is correlated with the occurrence and prognosis of gastric cancer

Immunology and immunotherapy in gastric cancer

Gastric cancer is the fifth leading cause of cancer-related deaths worldwide. As the diagnosis of early gastric cancer is difficult, most patients are at a late stage of cancer progression when diagnosed. The current therapeutic approaches based on surgical or endoscopic resection and chemotherapy indeed improve patients' outcomes. Immunotherapy based on immune checkpoint inhibitors has opened a new era for cancer treatment, and the immune system of the host is reshaped to combat tumor cells and the strategy differs according to the patient's immune system. Thus, an in-depth understanding of the roles of various immune cells in the progression of gastric cancer is beneficial to application for immunotherapy and the discovery of new therapeutic targets. This review describes the functions of different immune cells in gastric cancer development, mainly focusing on T cells, B cells, macrophages, natural killer cells, dendritic cells, neutrophils as well as chemokines or cytokines secreted by tumor cells. And this review also discusses the latest advances in immune-related therapeutic approaches such as immune checkpoint inhibitors, CAR-T or vaccine, to reveal potential and promising strategies for gastric cancer treatment.

Bioinformatic analysis of hub markers and immune cell infiltration characteristics of gastric cancer

Background

Gastric cancer (GC) is the fifth most common cancer and the second leading cause of cancer-related deaths worldwide. Due to the lack of specific markers, the early diagnosis of gastric cancer is very low, and most patients with gastric cancer are diagnosed at advanced stages. The aim of this study was to identify key biomarkers of GC and to elucidate GC-associated immune cell infiltration and related pathways.

Methods

Gene microarray data associated with GC were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were analyzed using Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia, Gene Set Enrichment Analysis (GSEA) and Protein-Protein Interaction (PPI) networks. Weighted gene coexpression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to identify pivotal genes for GC and to assess the diagnostic accuracy of GC hub markers using the subjects' working characteristic curves. In addition, the infiltration levels of 28 immune cells in GC and their interrelationship with hub markers were analyzed using ssGSEA. And further validated by RT-qPCR.

Results

A total of 133 DEGs were identified. The biological functions and signaling pathways closely associated with GC were inflammatory and immune processes. Nine expression modules were obtained by WGCNA, with the pink module having the highest correlation with GC; 13 crossover genes were obtained by combining DEGs. Subsequently, the LASSO algorithm and validation set verification analysis were used to finally identify three hub genes as potential biomarkers of GC. In the immune cell infiltration analysis, infiltration of activated CD4 T cell, macrophages, regulatory T cells and plasmacytoid dendritic cells was more significant in GC. The validation part demonstrated that three hub genes were expressed at lower levels in the gastric cancer cells.

Conclusion

The use of WGCNA combined with the LASSO algorithm to identify hub biomarkers closely related to GC can help to elucidate the molecular mechanism of GC development and is important for finding new immunotherapeutic targets and disease prevention.

The predictive effect of immune therapy and chemotherapy under T cell-related gene prognostic index for Gastric cancer

Background: Gastric cancer (GC) is one of the most common malignancies in the human digestive tract. CD4+T cells can eliminate tumor cells directly through the mechanism of cytolysis, they can also indirectly attack tumor cells by regulating the tumor TME. A prognostic model of CD4+T cells is urgently needed to improve treatment strategies and explore the specifics of this interaction between CD4+T cells and gastric cancer cells. Methods: The detailed data of GC samples were downloaded from the Cancer Genome Atlas (TCGA), GSE66229, and GSE84437 datasets. CD4⁺ T cell-related genes were identified to construct a risk-score model by using the Cox regression method and validated with the Gene Expression Omnibus (GEO) dataset. In addition, postoperative pathological tissues of 139 gastric cancer patients were randomly selected for immunohistochemical staining, and their prognostic information were collected for external verification. Immune and molecular characteristics of these samples and their predictive efficacy in immunotherapy and chemotherapy were analysed. Results: The training set and validation set had consistent results, with GC patients of high PROC and SERPINE1 expression having poorer prognosis. In order to improve their clinical application value, we constructed a risk scoring model and established a high-precision nomogram. Low-risk patients had a better overall survival (OS) than high-risk patients, consistent with the results from the GEO cohort. Furthermore, the risk-score model can predict infiltration of immune cells in the tumor microenvironment of GC, as well as the response of immunotherapy. Correlations between the abundance of immune cells with PROC and SERPINE1 genes were shown in the prognostic model according to the training cohort. Finally, sensitive drugs were identified for patients in different risk subgroup. Conclusion: The risk model not only provides a basis for better prognosis in GC patients, but also is a potential prognostic indicator to distinguish the molecular and immune characteristics of the tumor, and its response to immune checkpoint inhibitor (ICI) therapy and chemotherapy.

KDM6B promotes gastric carcinogenesis and metastasis via upregulation of CXCR4 expression

KDM6B (Lysine-specific demethylase 6B) is a histone lysine demethyltransferase that plays a key role in many types of cancers. However, its potential role in gastric cancer (GC) remains unclear. Here, we focused on the clinical significance and potential role of KDM6B in GC. We found that the KDM6B expression is upregulated in GC tissues and that its high expression in patients is related to poor prognosis. KDM6B ectopic expression promotes GC cells' proliferation and metastasis, while its inhibition has opposite effects in vitro and in vivo. Mechanistically, KDM6B promotes GC cells proliferation and metastasis through its enzymatic activity through the induction of H3K27me3 demethylation near the CXCR4 (C-X-C chemokine receptor type 4) promoter region, resulting in the upregulation of CXCR4 expression. Furthermore, H. pylori was found to induce KDM6B expression. In conclusion, our results suggest that KDM6B is aberrantly expressed in GC and plays a key role in gastric carcinogenesis and metastasis through CXCR4 upregulation. Our work also suggests that KDM6B may be a potential oncogenic factor and a therapeutic target for GC.

Identification and validation of prognostic autophagy-related genes associated with immune microenvironment in human gastric cancer

Autophagy-related genes (ATGs) play critical roles in tumorigenesis and progression in gastric cancer (GC). The present study aimed to identify immune-based prognostic ATGs and verify their functions in tumor immune microenvironment (TIME) in GC. Macrophage infiltration was found to negatively correlate with prognosis in GC patients. After stratifying by infiltration levels of macrophages, we screened The Cancer Genome Atlas and Human Autophagy Database to identify the differentially expressed ATGs (DE-ATGs). Of 1,433 differentially expressed genes between the two groups, seven genes qualified as DE-ATGs. Of these, CXCR4, DLC1, and MAP1LC3C, exhibited strong prognostic prediction ability in Kaplan-Meier survival–log-rank test. High expression of these genes correlated with increased occurrence of advanced grade 3 tumors and poor prognoses. Furthermore, GSEA indicated that they were significantly associated with oncogenic and immune-related pathways. The comprehensive evaluation of TIME via GEPIA, ESTIMATE, CIBERSORT, and TIMER suggested that the three DE-ATGs were closely associated with immune condition, both in terms of immune cells and immune scores. Thus, the outcome of this study may aid in better understanding of the ATGs and their interaction with the immune microenvironment, which would allow the development of novel inhibitors, personalized treatment, and immunotherapy in gastric cancer.

Development of Tumor Mutation Burden-Related Prognostic Model and Novel Biomarker Identification in Stomach Adenocarcinoma

Background: Stomach adenocarcinoma (STAD) is one of the most common tumors. Tumor mutation burden (TMB) has been linked to immunotherapy response. We wanted to see if there was any link between TMB and cancer prognosis.

Methods: The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to obtain mutation data, gene expression profiles, and clinical data. We looked at the differences in gene expression and immune markers between low and high TMB groups, built an immune prognostic model, and created a dynamic nomograph App that may be used in the clinic. Simultaneously, We ran the immunotherapy prediction and model comparison at the same time. Finally, model gene mutation and copy number variation (CNV) were displayed. The cellular functional experiments were used to investigate the potential role of GLP2R in gastric cancer.

Results: Firstly, basic mutation information and differences in immune infiltration in STAD are revealed. Secondly, the prognostic model developed by us has good accuracy, and the corresponding dynamic nomograph Apps online and immunotherapy prediction facilitate clinical transformation. Furthermore, GLP2R knockdown significantly inhibited the proliferation, migration of gastric cancer cells in vitro.

Conclusion: Our findings imply that TMB plays a significant role in the prognosis of STAD patients from a biological perspective. GLP2R may serve as a potential target for gastric cancer.

Chemokine-targeted therapies: An opportunity to remodel immune profiles in gastro-oesophageal tumours

Immunotherapies are transforming outcomes for many cancer patients and are quickly becoming the fourth pillar of cancer therapy. However, their efficacy of only ∼25% in gastro-oesophageal cancer has been disappointing. This is attributed to factors such as insufficient patient stratification and the pro-tumourigenic immune landscape of gastro-oesophageal tumours. The chemokine profiles of solid tumours and the availability of effector immune cells greatly influence the immune infiltrate, producing 'cold' or 'immune-excluded' tumours in which immunotherapies are unable to reinvigorate the immune response. Other biological functions for chemokines have emerged, such as promoting cell survival, polarising T cell responses, and supporting several hallmarks of cancer. Therefore, chemokine networks may be exploited with therapeutic intent to mobilise and polarise anti-tumour immune cells, with further utility as combination treatments to augment the efficacy of current cancer immunotherapies. Few studies have demonstrated the clinical benefit of chemokine-targeted therapies as monotherapies, and this review proposes their consideration as combination treatments. Herein, we explore the anti-tumour and pro-tumour implications of chemokine signalling in gastro-oesophageal cancer and discuss their value as prognostic and predictive biomarkers in response to treatment.

High expression of TREM2 promotes EMT via the PI3K/AKT pathway in gastric cancer: bioinformatics analysis and experimental verification

Background: To date, the pathogenesis of gastric cancer (GC) remains unclear. We combined public database resources and bioinformatics analysis methods, explored some novel genes and verified the experiments to further understand the pathogenesis of GC and to provide a promising target for anti-tumor therapy. Methods: We downloaded the chip data related to GC from the Gene Expression Omnibus (GEO) database, extracted differentially expressed genes (DEGs), and then determined the key genes in the development of GC via PPI networks and model analysis. Functional annotation via GO and KEGG enrichment of DEGs was used to understand the latent roles of DEGs. The expression of the triggering receptor expressed on myeloid cells 2 (TREM2) gene in GC cell lines was verified via RT-PCR and western blotting. Moreover, the CCK-8, wound healing assay, and transwell migration and invasion assays were used to understand the changes in the proliferation, migration, and invasion abilities of GC cells after silencing TREM2. Western blotting verified the interaction between TREM2 and PI3K predict of the string website, as well as the effect of TREM2 on EMT. Finally, a lung metastasis model was used to explore the relationship between TREM2 and metastasis. Results: Our study identified 16 key genes, namely BGN, COL1A1, COL4A1, COL5A2, NOX4, SPARC, HEYL, SPP1, TIMP1, CTHRC1, TREM2, SFRP4, FBXO32, GPX3, KIF4A, and MMP9 genes associated with GC. The EMT-related pathway was the most significantly altered pathway. TREM2 expression was higher in GC cell lines and was remarkably associated with tumor invasion depth, TNM stage, histological grade, histological type, anatomic subdivision, and Helicobacter pylori state. Knockdown of TREM2 expression inhibited the proliferation, migration, and invasion of GC cells as well as the progression of EMT by PI3K/AKT signaling in vitro. In addition, lung metastasis were decreased in vivo. Conclusions: We identified some important genes associated with the progression of GC via public database analysis, explored and verified the effects of proto-oncogene TREM2 on EMT via the PI3K/AKT pathway. TREM2 may be a novel target in the GC therapy.

The Role of Chemokines in the Development of Gastric Cancer - Diagnostic and Therapeutic Implications

Gastric cancer (GC) is the fifth most common cancer worldwide and the second leading cause of cancer-related death. GC is usually diagnosed at an advanced stage due to late presentation of symptoms. Therefore, there is a need for establishing more sensitive and specific markers useful in early detection of the disease when a cancer is asymptomatic to improve the diagnostic and clinical decision-making process. Some researchers suggest that chemokines and their specific receptors play an important role in GC initiation and progression via promotion of angiogenesis, tumor transformation, invasion, survival and metastasis as well as protection from host response and inter-cell communication. Chemokines are small proteins produced by various cells such as endothelial cells, fibroblasts, leukocytes, and epithelial and tumor cells. According to our knowledge, the significance of chemokines and their specific receptors in diagnosing GC and evaluating its progression has not been fully elucidated. The present article offers a review of current knowledge on general characteristics of chemokines, specific receptors and their role in GC pathogenesis as well as their potential usefulness as novel biomarkers for GC.

Three Genes Predict Prognosis in Microenvironment of Ovarian Cancer

Ovarian cancer (OC) is the deadliest gynecological cancer in women. Immune cell infiltration has a critical role in regulating carcinogenesis and prognosis in OC. To identify prognostic genes relevant to the tumor microenvironment in OC, we investigated the association between OC and gene expression profiles. Results obtained with the ESTIMATE R tool showed that immune score and stromal score were correlated with lymphatic invasion, and high immune score predicted a favorable prognosis. A total of 342 common differentially expressed genes were identified according to the two scores; these genes were mainly involved in immune response, extracellular region, and serine-type endopeptidase activity. Three immune-related prognostic genes were selected by univariate and multivariate Cox regression analysis. We further established a prognostic model and validated the prognostic value of three hub genes in different databases; our results showed that this model could accurately predict survival and evaluate prognosis independent of clinical characteristics. Three hub genes have prognostic value in OC. TIMER analysis revealed that the three genes were correlated with different immune cells. Low levels of macrophage infiltration and high levels of CD4+ T cell infiltration were associated with favorable survival outcomes. Arm-level gain of GYPC was correlated with neutrophils and dendritic cells. These findings indicate that CXCR4, GYPC, and MMP12 modulate prognosis via effects on the infiltration of immune cells. Thus, these genes represent potential targets for immune therapy in OC.