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

Current understanding on TREM-2 molecular biology and physiopathological functions

Triggering receptor expressed on myeloid cells 2 (TREM-2), a glycosylated receptor belonging to the immunoglobin superfamily and especially expressed in the myeloid cell lineage, is frequently explained as a reminiscent receptor for both adaptive and innate immunity regulation. TREM-2 is also acknowledged to influence NK cell differentiation via the PI3K and PLCγ signaling pathways, as well as the partial activation or direct inhibition of T cells. Additionally, TREM-2 overexpression is substantially linked to cell-specific functions, such as enhanced phagocytosis, reduced toll-like receptor (TLR)-mediated inflammatory cytokine production, increased transcription of anti-inflammatory cytokines, and reshaped T cell function. Whereas TREM-2-deficient cells exhibit diminished phagocytic function and enhanced proinflammatory cytokines production, proceeding to inflammatory injuries and an immunosuppressive environment for disease progression. Despite the growing literature supporting TREM-2+ cells in various diseases, such as neurodegenerative disorders and cancer, substantial facets of TREM-2-mediated signaling remain inadequately understood relevant to pathophysiology conditions. In this direction, herein, we have summarized the current knowledge on TREM-2 biology and cell-specific TREM-2 expression, particularly in the modulation of pivotal TREM-2-dependent functions under physiopathological conditions. Furthermore, molecular regulation and generic biological relevance of TREM-2 are also discussed, which might provide an alternative approach for preventing or reducing TREM-2-associated deformities. At last, we discussed the TREM-2 function in supporting an immunosuppressive cancer environment and as a potential drug target for cancer immunotherapy. Hence, summarized knowledge of TREM-2 might provide a window to overcome challenges in clinically effective therapies for TREM-2-induced diseases in humans.

SCG5 and MITF may be novel markers of copper metabolism immunorelevance in Alzheimer's disease

The slow-developing neurological disorder Alzheimer's disease (AD) has no recognized etiology. A bioinformatics investigation verified copper metabolism indicators for AD development. GEO contributed AD-related datasets GSE1297 and GSE5281. Differential expression analysis and WGCNA confirmed biomarker candidate genes. Each immune cell type in AD and control samples was scored using single sample gene set enrichment analysis. Receiver Operating Characteristic (ROC) analysis, short Time-series Expression Miner (STEM) grouping, and expression analysis between control and AD samples discovered copper metabolism indicators that impacted AD progression. We test clinical samples and cellular function to ensure study correctness. Biomarker-targeting miRNAs and lncRNAs were predicted by starBase. Trust website anticipated biomarker-targeting transcription factors. In the end, Cytoscape constructed the TF/miRNA-mRNA and lncRNA-miRNA networks. The DGIdb database predicted biomarker-targeted drugs. We identified 57 differentially expressed copper metabolism-related genes (DE-CMRGs). Next, fourteen copper metabolism indicators impacting AD progression were identified: CCK, ATP6V1E1, SYT1, LDHA, PAM, HPRT1, SCG5, ATP6V1D, GOT1, NFKBIA, SPHK1, MITF, BRCA1, and CD38. A TF/miRNA-mRNA regulation network was then established with two miRNAs (hsa-miR-34a-5p and 34c-5p), six TFs (NFKB1, RELA, MYC, HIF1A, JUN, and SP1), and four biomarkers. The DGIdb database contained 171 drugs targeting ten copper metabolism-relevant biomarkers (BRCA1, MITF, NFKBIA, CD38, CCK2, HPRT1, SPHK1, LDHA, SCG5, and SYT1). Copper metabolism biomarkers CCK, ATP6V1E1, SYT1, LDHA, PAM, HPRT1, SCG5, ATP6V1D, GOT1, NFKBIA, SPHK1, MITF, BRCA1, and CD38 alter AD progression, laying the groundwork for disease pathophysiology and novel AD diagnostic and treatment.

The nanobody targeting PD-L1 and CXCR4 counteracts pancreatic stellate cell-mediated tumour progression by disrupting tumour microenvironment

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal malignancy worldwide owing to its complex tumour microenvironment and dense physical barriers. Stromal-derived factor-1 (SDF-1), which is abundantly secreted by tumour stromal cells, plays a pivotal role in promoting PDAC growth and metastasis. In this study, we investigated the impact and molecular mechanisms of the anti-PD-L1&CXCR4 bispecific nanobody on the TME and their consequent interference with PDAC progression. We found that blocking the SDF-1/CXCR4 signalling pathway delayed the epithelial-mesenchymal transition in pancreatic cancer cells. Anti-PD-L1&CXCR4 bispecific nanobody effectively suppress the secretion of SDF-1 by pancreatic stellate cells and downregulate the expression of smooth muscle actin alpha(α-SMA), thereby preventing the activation of cancer-associated fibroblasts by downregulating the PI3K/AKT signaling pathway. This improves the pancreatic tumour microenvironment, favouring the infiltration of T cells into the tumour tissue. In conclusion, our results suggest that the anti-PD-L1&CXCR4 bispecific nanobody exerts an antitumor immune response by changing the pancreatic tumour microenvironment. Hence, the anti-PD-L1&CXCR4 bispecific nanobody is a potential candidate for pancreatic cancer treatment.

Mechanisms of TREM2 mediated immunosuppression and regulation of cancer progression

Cancer immunotherapy has recently emerged as a key strategy for cancer treatment. TREM2, a key target for regulating the tumor immune microenvironment, is important in cancer treatment and progression. TREM2 is an immune signaling hub that regulates multiple pathological pathways. It not only suppresses anti-tumor immune responses by inhibiting T cell-mediated immune responses, but it also influences tumorigenesis by affecting NK cell-mediated anti-tumor immunity. Noticeably, TREM2 expression levels also vary significantly among different tumor cells, and it can regulate tumor progression by modulating various signaling pathways. Above all, by summarizing the role of TREM2 in cancer immunotherapy and the mechanism by which TREM2 regulates tumor progression, this paper clarifies TREM2's role in both tumor progression and cancer therapy, identifying a new therapeutic target for oncology diseases.

Progress in research of tumor biomarkers and molecular imaging probes for gastric cancer

Gastric cancer is a malignant tumor still associated with high morbidity and mortality worldwide. Its onset is relatively insidious, and when detected, it is already at an advanced stage, lacks effective individualized treatments, and has a poor prognosis. If gastric cancer can be diagnosed at an early stage, the survival rate of patients can be greatly improved. However, traditional imaging modalities lack specificity and sensitivity. In recent years, molecular imaging technology is booming, which can non-invasively and dynamically monitor gastric cancer at the cellular and molecular levels, and provide more reference information for clinical selection of treatment options and assessment of efficacy and prognosis. This article reviews the biomarkers of gastric cancer and molecular probes in various imaging modalities.

Tumor-related exosomal circ_0001715 promotes lung adenocarcinoma cell proliferation and metastasis via enhancing M2 macrophage polarization by regulating triggering receptor expressed on myeloid cells-2

BACKGROUND

Circular RNAs (circRNAs) have been shown to mediate tumor-associated macrophages (TAMs) to regulate the development of many cancers, including lung adenocarcinoma (LUAD). However, whether circ_0001715 regulates LUAD progression by mediating TAMs polarization remains uncertain.

METHODS

Monocytes (THP-1) were treated with PMA to induce M0 macrophages. M0 macrophages were incubated with LUAD cells-derived exosomes and then cocultured with LUAD cells. The levels of circ_0001715, M2 macrophage markers, microRNA (miR)-205-5p, and triggering receptor expressed on myeloid cells-2 (TREM2) were examined using quantitative real-time PCR. Flow cytometry was performed to assess M2 macrophage surface marker CD206. Cell proliferation, migration and invasion were determined using cell counting kit 8, EdU, colony formation and transwell assays. Dual-luciferase reporter assay was used to investigate the interactions between miR-205-5p and circ_0001715 or TREM2.

RESULTS

Circ_0001715 knockdown inhibited M2 macrophage polarization and its overexpression had an opposite effect. After M0 macrophages transfected with si-circ_0001715 were cocultured with LUAD cells, the proliferation and metastasis of LUAD cells were markedly reduced. Exosomes transferred circ_0001715 between M0 macrophages and LUAD cells. Exosomal circ_0001715 promoted M2 macrophage polarization to increase LUAD cell proliferation and metastasis. In terms of mechanism, circ_0001715 sponged miR-205-5p to positively regulate TREM2. TREM2 upregulation also could promote LUAD cell proliferation and metastasis via increasing M2 macrophage polarization. In addition, TREM2 knockdown reversed the effect of exosomal circ_0001715 on M2 macrophage polarization and LUAD cell progression.

CONCLUSION

Exosomal circ_0001715 led to LUAD cell proliferation and metastasis by promoting M2 macrophage polarization via the miR-205-5p/TREM2 axis.

Construction of 11 metabolic-related lncRNAs to predict the prognosis in lung adenocarcinoma

OBJECTIVE

To explore the metabolism-related lncRNAs in the tumorigenesis of lung adenocarcinoma.

METHODS

The transcriptome data and clinical information about lung adenocarcinoma patients were acquired in TCGA (The Cancer Genome Atlas). Metabolism-related genes were from the GSEA (Gene Set Enrichment Analysis) database. Through differential expression analysis and Pearson correlation analysis, lncRNAs about lung adenocarcinoma metabolism were identified. The samples were separated into the training and validation sets in the proportion of 2:1. The prognostic lncRNAs were determined by univariate Cox regression analysis and LASSO (Least absolute shrinkage and selection operator) regression. A risk model was built using Multivariate Cox regression analysis, evaluated by the internal validation data. The model prediction ability was assessed by subgroup analysis. The Nomogram was constructed by combining clinical indicators with independent prognostic significance and risk scores. C-index, calibration curve, DCA (Decision Curve Analysis) clinical decision and ROC (Receiver Operating Characteristic Curve) curves were obtained to assess the prediction ability of the model. Based on the CIBERSORT analysis, the correlation between lncRNAs and tumor infiltrating lymphocytes was obtained.

RESULTS

From 497 lung adenocarcinoma and 54 paracancerous samples, 233 metabolic-related and 11 prognostic-related lncRNAs were further screened. According to the findings of the survival study, the low-risk group had a greater OS (Overall survival) than the high-risk group. ROC analysis indicated AUC (Area Under Curve) value was 0.726. Then, a nomogram with T, N stage and risk ratings was developed according to COX regression analysis. The C-index was 0.743, and the AUC values of 3- and 5-year survival were 0.741 and 0.775, respectively. The above results suggested the nomogram had a good prediction ability. The results based on the CIBERSORT algorithm demonstrated the lncRNAs used to construct the model had a strong correlation with the polarization of immune cells.

CONCLUSIONS

The study identified 11 metabolic-related lncRNAs for lung adenocarcinoma prognosis, on which basis a prognostic risk scoring model was created. This model may have a good predictive potential for lung adenocarcinoma.

Oncogenic transmembrane protein 158 drives the PI3K/Akt signaling pathway to accelerate gastric cancer cell growth

Gastric cancer (GC) is a serious threat to human health and an important cause of cancer-related death. Herein, we evaluated the influence of transmembrane protein 158 (TMEM158) on GC cell growth. According to Genomic Spatial Event (GSE) and The Cancer Genome Atlas (TCGA) databases, TMEM158 content is amplified in GC tissues. The diagnostic value of TMEM158 expression in GC is huge. GC sufferers with high expression of TMEM158 were associated with poor overall survival. In addition, TMEM158 content was increased in GC cells. TMEM158 promoted GC cell proliferation by modulating the PI3K/Akt signaling pathway. Lack of TMEM158 reduced GC tumor growth. Collectively, TMEM158 accelerated GC cell proliferation by modulating the PI3K/Akt signaling pathway, making it a prospective biomarker for survival in GC patients.

TREM2: A new player in the tumor microenvironment

TREM2 is a myeloid cell receptor that has been extensively described in the context of neuroinflammation and neurodegenerative diseases. Recently, TREM2 emerged as a crucial regulator of macrophage function in tumors. TREM2-deficiency or blockade provide protection and promote the response to anti-PD1 in different murine models. In human tumors, TREM2-expressing macrophages are present in numerous cohorts and tumor types and are generally associated with immunosuppression and poor prognosis. Here, we provide an overview of the impact of TREM2 in tumors considering current literature, with a focus on both murine models and human cancer.

TREM2 as a Potential Immune-Related Biomarker of Prognosis in Patients with Skin Cutaneous Melanoma Microenvironment

Background

The skin cutaneous melanoma (SKCM) is a devastating form of skin cancer triggered by genetic and environmental factors, and the incidence of SKCM has rapidly increased in recent years. Immune infiltration of the tumor microenvironment is positively associated with overall survival in many tumors. Triggering receptor expressed on myeloid cells 2 (TREM2) is a transmembrane receptor of the immunoglobulin superfamily and a crucial signaling hub for multiple pathological pathways that mediate immunity. Although numerous evidences suggest a crucial role for TREM2 in tumorigenesis of some tumors, no systematic SKCM analysis of TREM2 is available. Mehods. The relationship between TREM2 expression and diagnostic and prognostic value of SKCM patients via using The Cancer Genome Atlas (TCGA) data. The expression level of TREM2 and clinical characteristic correlation in SKCM patients were assessed by the Wilcoxon rank sum test. The cox regression methods, Kaplan-Meier (KM), and log-rank test were used to assess the impact of TREM2 expression on the overall survival (OS). Furthermore, the Gene Set Enrichment Analysis (GSEA) and TIMER were performed to evaluate the enrichment pathways and potential functions and quantify the immune cell infiltration level for TREM2 expression.

Results

The TREM2 in SKCM sample expression levels was significantly higher than in normal tissues. Moreover, this expression level of TREM2 was also associated with the BMI of SKCM patients. KM overall survival analysis and OS curve displayed that a high-level TREM2 expression was significantly correlated with a better SKCM prognosis of patients as compared with a low level of TREM2 expression. The GSEA analysis also revealed that TREM2 was associated with immune functions, such as neutrophil activation.

Conclusion

TREM2 played a crucial role in SKCM, which might be a prognostic biomarker and correlated with immune infifiltrates in SKCM patients.

Gastric cancer-derived mesenchymal stem cells promote gastric cancer cell lines migration by modulating CD276 expression

CD276 has been studied in a variety of cancers and diseases, but its regulatory mechanisms in gastric cancer is still unclear. Mesenchymal stem cells (MSCs), one of the important members of tumor microenvironment, play an important role in the occurrence, development and metastasis of tumor, but the relationship between gastric cancer mesenchymal stem cells (GCMSCs) and CD276 in gastric cancer needs to be further explored. The differential expression of CD276 was identified via UCLAN and GEPIA databases. Then, the impacts of CD276 were calculated on clinical prognosis using the Kaplan-Meier plotter and Cox analysis. GO, KEGG and GSEA analysis were used to explore potential mechanism under CD276. Next, the expression of CD276 in gastric cell lines were detected by Western blot. Immunocoprecipitation was used to explore the association between CD276 and COL1A1. And the effect of condition medium (CM) from GCMSCs on gastric cell lines migration analyzed. GC-MSCs activated the AKT/c-Myc/mTOR pathway of gastric cell lines and upregulated CD276 expression. Moreover, the upregulation of CD276 promoted the migration of gastric cancer cells. Taken together, this study shown that GCMSCs could up-regulate the expression of CD276 of gastric cell lines to promote tumor migration. Our results provide a new basis for the treatment of gastric cancer.

TREM2 as an independent predictor of poor prognosis promotes the migration via the PI3K/AKT axis in prostate cancer

OBJECTIVE

Prostate adenocarcinoma (PRAD) is one of the most common cancers, with high morbidity and mortality. Triggering receptors expressed on myeloid cells 2 (TREM2) is upregulated in various malignancies, however its effect on PRAD remains unknown. This study aimed to investigate the prognostic value of TREM2 in PRAD.

METHODS

PRAD samples were collected from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), Oncomine, and the Human Protein Atlas (HPA) to analyze the differences in TREM2 expression between normal and tumor tissues. The influence of TREM2 on the clinicopathological characteristics and its prognostic value were evaluated using the Kaplan-Meier curve, Cox regression analysis, ROC (receiver operating characteristic) plot, and nomogram. Gene Ontology (GO), gene set enrichment analysis (GSEA), and protein-protein interaction (PPI) were conducted to screen biological functions and pathways. The relationship between TREM2 and tumor microenvironment (TME) characteristics was explored. The TREM2 expression in PRAD specimens and cell lines was assessed by immunohistochemistry staining and western blot. TREM2-specific siRNAs were used to evaluate the effects of TREM2 on cell function.

RESULTS

TREM2 was upregulated and positively associated with poor clinicopathologic characteristics. Overexpression of TREM2 is an independent biomarker for the prognosis of PFI (progression-free interval). Moreover, TREM2 expression was positively correlated with various TME characteristics. Knockdown of TREM2 inhibited the migration of PRAD cell lines via the PI3K/AKT axis.

CONCLUSION

High TREM2 expression may represent a novel diagnostic and prognostic biomarker and serve as a potential target gene for PRAD therapy.

Combined single-cell RNA-seq and bulk RNA-seq to analyze the expression and role of TREM2 in bladder cancer

Currently, reprogramming macrophages has emerged as one of the most promising therapeutic strategies in cancer treatment. Many studies have found that myeloid trigger receptor-2 (TREM2) is mainly expressed on tumor-associated macrophages (TAMs), and targeting TREM2 promotes reprogramming of TAMs and enhances the immunotherapeutic effect of tumors. Nevertheless, the expression and role of TREM2 in different tumor tissues are still controversial. For example, some studies have found that TREM2 can also be expressed on tumor cells and exert pro-tumor functions. It has also been found that TREM2 expression can inhibit tumorigenesis and progression. In fact, there are still no relevant studies on the expression and role of TREM2 in bladder cancer (BLCA). Therefore, the present study combined single-cell RNA-seq and bulk RNA-seq to analyze the expression, role, and molecular mechanism of TREM2 in BLCA. We found that TREM2 was predominantly expressed on TAMs in BLCA, followed by tumor epithelial cells. This finding could be useful for further exploration of the role and mechanism of TREM2. Moreover, TREM2 expression correlates with clinical progression and immunotherapy efficacy, and is an important predictor of prognosis for BLCA patients. Not only that, we also found that TREM2 may exert its effects by promoting epithelial mesenchymal transition (EMT) and T-cell exhaustion. TREM2⁺ TAMs may play an important pro-tumor role through PTN, ANGPTL, and VISFATIN pathways. In conclusion, our study found that TREM2 is not only a predictor of BLCA prognosis, but also a potential therapeutic target for BLCA.

ESRRG, ATP4A, and ATP4B as Diagnostic Biomarkers for Gastric Cancer: A Bioinformatic Analysis Based on Machine Learning

Based on multiple bioinformatics methods and machine learning techniques, this study was designed to explore potential hub genes of gastric cancer with a diagnostic value. The novel biomarkers were detected through multiple databases of gastric cancer–related genes. The NCBI Gene Expression Omnibus (GEO) database was used to obtain gene expression files. Three hub genes (ESRRG, ATP4A, and ATP4B) were detected through a combination of weighted gene co-expression network analysis (WGCNA), gene–gene interaction network analysis, and supervised feature selection method. GEPIA2 was used to verify the differences in the expression levels of the hub genes in normal and cancer tissues in the RNA-seq levels of Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases. The objectivity of potential hub genes was also verified by immunohistochemistry in the Human Protein Atlas (HPA) database and transcription factor–hub gene regulatory network. Machine learning (ML) methods including data pre-processing, model selection and cross-validation, and performance evaluation were examined on the hub-gene expression profiles in five Gene Expression Omnibus datasets and verified on a GEO external validation (EV) dataset. Six supervised learning models (support vector machine, random forest, k-nearest neighbors, neural network, decision tree, and eXtreme Gradient Boosting) and one semi-supervised learning model (label spreading) were established to evaluate the diagnostic value of biomarkers. Among the six supervised models, the support vector machine (SVM) algorithm was the most effective one according to calculated performance metrics, including 0.93 and 0.99 area under the curve (AUC) scores on the test and external validation datasets, respectively. Furthermore, the semi-supervised model could also successfully learn and predict sample types, achieving a 0.986 AUC score on the EV dataset, even when 10% samples in the five GEO datasets were labeled. In conclusion, three hub genes (ATP4A, ATP4B, and ESRRG) closely related to gastric cancer were mined, based on which the ML diagnostic model of gastric cancer was conducted.

Helicobacter pylori promotes gastric cancer progression through the tumor microenvironment

Gastric cancer (GC) is a leading type of cancer. Although immunotherapy has yielded important recent progress in the treatment of GC, the prognosis remains poor due to drug resistance and frequent recurrence and metastasis. There are multiple known risk factors for GC, and infection with Helicobacter pylori is one of the most significant. The mechanisms underlying the associations of H. pylori and GC remain unclear, but it is well known that infection can alter the tumor microenvironment (TME). The TME and the tumor itself constitute a complete ecosystem, and the TME plays critical roles in tumor progression, metastasis, and drug resistance. H. pylori infection can act synergistically with the TME to cause DNA damage and abnormal expression of multiple genes and activation of signaling pathways. It also modulates the host immune system in ways that enhance the proliferation and metastasis of tumor cells, promote epithelial-mesenchymal transition, inhibit apoptosis, and provide energy support for tumor growth. This review elaborates myriad ways that H. pylori infections promote the occurrence and progression of GC by influencing the TME, providing new directions for immunotherapy treatments for this important disease. KEY POINTS: • H. pylori infections cause DNA damage and affect the repair of the TME to DNA damage. • H. pylori infections regulate oncogenes or activate the oncogenic signaling pathways. • H. pylori infections modulate the immune system within the TME.

The emerging role of triggering receptor expressed on myeloid cell-2 in malignant tumor

Triggering receptor expressed on myeloid cell-2 (TREM2) is a transmembrane receptor which is specifically expressed on myeloid cells. To date, TREM2 has been confirmed as a key factor in many pathologies, such as Alzheimer's disease, obesity-related metabolic syndrome, fatty liver and atherosclerosis. However, the role of TREM2 in tumors remains poorly understood. TREM2 is highly expressed in more than 200 primary and metastatic tumors, a feature that makes TREM2 a potential clinical target for tumor immunotherapy. The tumor microenvironment (TME) is the "soil" which tumors survive on and exhibits immunosuppressive characteristics. During the development of a tumor, TME will secrete various chemotactic factors to recruit myeloid cells. It is clear now that cancer progression and metastasis depend on the interactions between cancer cells and myeloid cell infiltration in TME. As an important receptor involved in inflammatory suppression signaling pathways, TREM2 may play an important role in immune escape by the tumor. Recently, several studies have illustrated that TREM2 expressed on tumor infiltrated myeloid cells acts as a crucial regulator of the antitumor immune response. In this review, we systematically summarize recent publications about the latest advances in knowledge of TREM2 in cancer, especially focusing on its role in tumor associated myeloid cells and tumor immunotherapy.

Identification of KIF4A as a prognostic biomarker for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is the most common and aggressive tumor worldwide, and the long-term survival of these patients remains poor. Three databases (GSE17351, GSE20347, and GSE100942) were obtained from Gene Expression Omnibus, and 193 differentially expressed genes including 56 upregulated and 137 downregulated genes were identified by paired test using limma R package. Then, functional enrichments by gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed these genes were mainly related protein digestion and absorption, and IL-17 signaling pathway. We then constructed a protein-protein interaction network and cytoHubba module to determine the six hub genes and overall survival analysis of the six hub genes were evaluated by UALCAN and GEPIA2 analysis. Ultimately, the experimental results confirmed the KIF4A was overexpressed in the ESCC tissues and cell lines compared with the normal esophageal mucosal tissues and was linked to poor prognosis. Moreover, we also revealed that KIF4A facilitates proliferation, cell cycle, migration, and invasion of ESCC in vivo and in vitro. Overall, these findings demonstrated that KIF4A could serve as diagnostic and prognostic biomarkers and may help facilitate therapeutic targets in ESCC patients.