Identification and Validation of ATF3 Serving as a Potential Biomarker and Correlating With Pharmacotherapy Response and Immune Infiltration Characteristics in Rheumatoid Arthritis

Background: Although disease-modifying antirheumatic drugs (DMARDs) have significantly improved the prognosis of patients with rheumatoid arthritis (RA), approximately 40% of RA patients have limited response. Therefore, it was essential to explore new biomarkers to improve the therapeutic effects on RA. This study aimed to develop a new biomarker and validate it by an in vitro study.Methods: The RNA-seq and the clinicopathologic data of RA patients were downloaded from Gene Expression Omnibus (GEO) databases. Differentially expressed genes were screened in the GPL96 and GPL570 databases. Then, weighted gene co-expression network analysis (WGCNA) was used to explore the most correlated gene modules to normal and RA synovium in the GPL96 and GPL570 databases. After that, the differentially expressed genes were intersected with the correlated gene modules to find the potential biomarkers. The CIBERSORT tool was applied to investigate the relationship between activated transcription factor 3 (ATF3) expression and the immune cell infiltration, and Gene Set Enrichment Analysis (GSEA) was used to investigate the related signaling pathways of differentially expressed genes in the high and low ATF3 groups. Furthermore, the relationships between ATF3 expression and clinical parameters were also explored in the GEO database. Finally, the role of ATF3 was verified by in vitro cell experiments.Results: We intersected the differentially expressed genes and the most correlated gene modules in the GPL570 and GPL96 databases and identified that ATF3 is a significant potential biomarker and correlates with some clinical–pharmacological variables. Immune infiltration analysis showed that activated mast cells had a significant infiltration in the high ATF3 group in the two databases. GSEA showed that metabolism-associated pathways belonged to the high ATF3 groups and that inflammation and immunoregulation pathways were enriched in the low ATF3 group. Finally, we validated that ATF3 could promote the proliferation, migration, and invasion of RA fibroblast-like synoviocyte (FLS) and MH7A. Flow cytometry showed that ATF3 expression could decrease the proportion of apoptotic cells and increase the proportion of S and G2/M phase cells.Conclusion: We successfully identified and validated that ATF3 could serve as a novel biomarker in RA, which correlated with pharmacotherapy response and immune cell infiltration.

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The tumor immune microenvironment and immune-related signature predict the chemotherapy response in patients with osteosarcoma

BMC Cancer ◽

10.1186/s12885-021-08328-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Lijiang He ◽

Hainan Yang ◽

Jingshan Huang

Keyword(s):

Differentially Expressed Genes ◽

Immune Cell ◽

Validation Cohort ◽

Expression Profiles ◽

Differentially Expressed ◽

Poor Responders ◽

Chemotherapy Response ◽

Immune Cell Infiltration ◽

Training Cohort ◽

Immune Infiltration

Abstract Background Genome-wide expression profiles have been shown to predict the response to chemotherapy. The purpose of this study was to develop a novel predictive signature for chemotherapy in patients with osteosarcoma. Methods We analysed the relevance of immune cell infiltration and gene expression profiles of the tumor samples of good responders with those of poor responders from the TARGET and GEO databases. Immune cell infiltration was evaluated using a single-sample gene set enrichment analysis (ssGSEA) and the CIBERSORT algorithm between good and poor chemotherapy responders. Differentially expressed genes were identified based on the chemotherapy response. LASSO regression and binary logistic regression analyses were applied to select the differentially expressed immune-related genes (IRGs) and developed a predictive signature in the training cohort. A receiver operating characteristic (ROC) curve analysis was employed to assess and validate the predictive accuracy of the predictive signature in the validation cohort. Results The analysis of immune infiltration showed a positive relationship between high-level immune infiltration and good responders, and T follicular helper cells and CD8 T cells were significantly more abundant in good responders with osteosarcoma. Two hundred eighteen differentially expressed genes were detected between good and poor responders, and a five IRGs panel comprising TNFRSF9, CD70, EGFR, PDGFD and S100A6 was determined to show predictive power for the chemotherapy response. A chemotherapy-associated predictive signature was developed based on these five IRGs. The accuracy of the predictive signature was 0.832 for the training cohort and 0.720 for the validation cohort according to ROC analysis. Conclusions The novel predictive signature constructed with five IRGs can be effectively utilized to predict chemotherapy responsiveness and help improve the efficacy of chemotherapy in patients with osteosarcoma.

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Immune Infiltration Subtypes Characterization and Identification of Prognosis-Related lncRNAs in Adenocarcinoma of the Esophagogastric Junction

Frontiers in Immunology ◽

10.3389/fimmu.2021.651056 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xin Hu ◽

Liuxing Wu ◽

Ben Liu ◽

Kexin Chen

Keyword(s):

Predictive Value ◽

Esophagogastric Junction ◽

Immune Cell ◽

Differentially Expressed ◽

Enrichment Score ◽

High Survival ◽

Cox Regression Analysis ◽

Immune Infiltration ◽

Related Risk ◽

Potential Biomarker

The incidence of adenocarcinoma of the esophagogastric junction (AEG) has markedly increased worldwide. However, the precise etiology of AEG is still unclear, and the therapeutic options thus remain limited. Growing evidence has implicated long non-coding RNAs (lncRNAs) in cancer immunomodulation. This study aimed to examine the tumor immune infiltration status and assess the prognostic value of immune-related lncRNAs in AEG. Using the ESTIMATE method and single-sample GSEA, we first evaluated the infiltration level of 28 immune cell types in AEG samples obtained from the TCGA dataset (N=201). Patients were assigned into high- and low-immune infiltration subtypes based on the immune cell infiltration’s enrichment score. GSEA and mutation pattern analysis revealed that these two immune infiltration subtypes had distinct phenotypes. We identified 1470 differentially expressed lncRNAs in two immune infiltration subtypes. From these differentially expressed lncRNAs, six prognosis-related lncRNAs were selected using the Cox regression analysis. Subsequently, an immune risk signature was constructed based on combining the values of the six prognosis-associated lncRNAs expression levels and multiple regression coefficients. To determine the risk model’s prognostic capability, we performed a series of survival analyses with Kaplan–Meier methods, Cox proportional hazards regression models, and the area under receiver operating characteristic (ROC) curve. The results indicated that the immune-related risk signature could be an independent prognostic factor with a significant predictive value in patients with AEG. Furthermore, the immune-related risk signature can effectively predict the response to immunotherapy and chemotherapy in AEG patients. In conclusion, the proposed immune-related lncRNA prognostic signature is reliable and has high survival predictive value for patients with AEG and is a promising potential biomarker for immunotherapy.

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Down-Regulated CLDN10 Predicts Favorable Prognosis and Correlates With Immune Infiltration in Gastric Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.747581 ◽

2021 ◽

Vol 12 ◽

Author(s):

XiongHui Rao ◽

JianLong Jiang ◽

ZhiHao Liang ◽

JianBao Zhang ◽

ZheHong Zhuang ◽

...

Keyword(s):

Gastric Cancer ◽

T Cell ◽

Immune Cell ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Her2 Status ◽

Immune Cell Infiltration ◽

Cell Markers ◽

Immune Infiltration

Background: CLDN10, an important component of the tight junctions of epithelial cells, plays a crucial role in a variety of tumors. The effect of CLDN10 expression in gastric cancer, however, has yet to be elucidated.Methods: Differential expression of CLDN10 at the mRNA and protein levels was evaluated using Oncomine, ULCAN, HPA and TIMER2.0 databases. Real-time polymerase chain reaction (RT-PCR) was utilized to further verify the expression of CLDN10 in vitro. Correlations between CLDN10 expression and clinical outcomes of gastric cancer were explored by Kaplan-Meier Plotter. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) were performed via LinkedOmics and GeneMANIA. The correlations between CLDN10 expression and immune cell infiltration and somatic copy number alternations (SCNA) in gastric cancer were explored by TIMER2.0 and GEPIA2.0.Results: CLDN10 expression was lower in gastric cancer compared to adjacent normal tissues, and associated with better prognosis. CLDN10 also showed significant differences at different T stages, Lauren classification, treatments and HER2 status. PPI and GSEA analysis showed that CLDN10 might be involved in signal transmission, transmembrane transport and metabolism. In some major immune cells, low expression of CLDN10 was associated with increased levels of immune cell infiltration. In addition, it was found that different SCNA status in CLDN10 might affect the level of immune cell infiltration. Furthermore, the expression of CLDN10 was significantly associated with the expression of several immune cell markers, especially B cell markers, follicular helper T cell (Tfh) markers and T cell exhaustion markers.Conclusion: Down-regulated CLDN10 was associated with better overall survival (OS) in gastric cancer. And CLDN10 may serve as a potential prognostic biomarker and correlate to immune infiltration levels in gastric cancer.

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C3aR1 Correlates With Immune Cell Infiltration and Serves as Prognostic and Therapeutic Biomarker in Gastric Cancer

10.21203/rs.3.rs-1163983/v1 ◽

2021 ◽

Author(s):

weifeng liu ◽

Zhijie Chu ◽

Cheng Yang ◽

Tianbao Yang ◽

Yanhui Yang ◽

...

Keyword(s):

Gastric Cancer ◽

T Cell ◽

Differentially Expressed Genes ◽

Tumor Tissue ◽

Immune Cell ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Expression Levels

Abstract As the fourth most common malignancy worldwide, gastric cancer can lead more than 720 000 patient death every year. Precisely therapeutic intervention can significantly improve patients’ survival status underlying the precise clarification by molecular indexes. Identifying the biomarkers highly associated with disease prognosis will be helpful to guide the clinical therapy. C3ar1 is an essential receptor in the complement system, and participates in various biological processes associated with immunological responses. To identify the crucial roles of C3AR1 in gastric cancer tmorigenesis, we determined the mRNA profile, protein expression levels and the clinicopathological indexes using cBioportal, Kaplan-Meier plotter and the Human Protein Atlas databases. To identify the molecular network in C3AR1-expressed gastric cancer, we obtained the differentially expressed genes using the GEPIA database compared with normal stomach tissues. Furthermore, we analyzed the biological impact of these differentially expressed genes using protein-protein interaction network and gene set enrichment analysis, in which we identified the hub genes and critical pathways influenced by over-expressed C3AR1 in gastric cancer. Finally, we evaluated the correlation between the C3AR1 expression levels and immune cell infiltration levels utilizing the Tumor Immunoassay Resource database. Our results revealed that the higher expression level of C3AR1 can lead higher infiltration of T cell CD8+, T cell CD4+, macrophage, neutrophil, B cell and myeloid dendritic cells into tumor tissue. Moreover, we also found that higher infiltration of macrophage cells into tumor tissue can worsen the survival of patients with gastric cancer, which may be highly associated with the polarization states of macrophages (TAM and M2 status). Our investigation suggest that C3AR1 can be as an efficient diagnostic biomarkers for gastric cancer therapy.

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Identification of differentially expressed genes, signaling pathways and immune infiltration in rheumatoid arthritis by integrated bioinformatics analysis

10.21203/rs.3.rs-38219/v2 ◽

2020 ◽

Author(s):

Yanzhi Ge ◽

Li Zhou ◽

Zuxiang Chen ◽

Yingying Mao ◽

Ting Li ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Signaling Pathways ◽

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Bioinformatics Analysis ◽

Kegg Pathway ◽

Differentially Expressed ◽

Ppi Network ◽

Immune Infiltration ◽

Significant Difference

Abstract Background: The disability rate associated with rheumatoid arthritis (RA) ranks high among inflammatory joint diseases. However, the cause and potential molecular events are as yet not clear. Here, we aimed to identify differentially expressed genes (DEGs), pathways and immune infiltration involved in RA utilizing integrated bioinformatics analysis and investigating potential molecular mechanisms. Materials and methods: The expression profiles of GSE55235, GSE55457, GSE55584 and GSE77298 were downloaded from the Gene Expression Omnibus database, which contained 76 synovial membrane samples, including 49 RA samples and 27 normal controls. The microarray datasets were consolidated and DEGs were acquired and further analyzed by bioinformatics techniques. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were performed using R (version 3.6.1) software, respectively. The protein-protein interaction (PPI) network of DEGs were developed utilizing the STRING database. Finally, the CIBERSORT was used to evaluate the infiltration of immune cells in RA. Results: A total of 828 DEGs were recognized, with 758 up-regulated and 70 down-regulated. GO and KEGG pathway analyses demonstrated that these DEGs focused primarily on cytokine receptor activity and relevant signaling pathways. The 30 most firmly related genes among DEGs were identified from the PPI network. The principal component analysis showed that there was a significant difference between the two tissues in infiltration immune. Conclusion: This study shows that screening for DEGs, pathways and immune infiltration utilizing integrated bioinformatics analyses could aid in the comprehension of the molecular mechanisms involved in RA development. Besides, our study provides valuable data related to DEGs, pathways and immune infiltration of RA and may provide new insight into the understanding of molecular mechanisms.

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Identification of Differentially Expressed Genes Reveals BGN Predicting Overall Survival and Tumor Immune Infiltration of Gastric Cancer

Computational and Mathematical Methods in Medicine ◽

10.1155/2021/5494840 ◽

2021 ◽

Vol 2021 ◽

pp. 1-21

Author(s):

Weizhi Chen ◽

Zhongheng Yang

Keyword(s):

Gastric Cancer ◽

T Cells ◽

Differentially Expressed Genes ◽

Treatment Strategies ◽

Differentially Expressed ◽

Hub Genes ◽

Immune Infiltration ◽

Potential Biomarker ◽

Positive Correlations ◽

First Time

Gastric cancer (GC) is one of the most widely occurring malignancies worldwide. Although the diagnosis and treatment strategies of GC have been greatly improved in the past few decades, the morbidity and lethality rates of GC are still rising due to lacking early diagnosis strategies and powerful treatments. In this study, a total of 37 differentially expressed genes were identified in GC by analyzing TCGA, GSE118897, GSE19826, and GSE54129. Using the PPI database, we identified 17 hub genes in GC. By analyzing the expression of hub genes and OS, MFAP2, BGN, and TREM1 were related to the prognosis of GC. In addition, our results showed that higher levels of BGN exhibited a significant correlation with shorter OS time in GC. Nomogram analysis showed that the dysregulation of BGN could predict the prognosis of GC. Moreover, we revealed that BGN had a markedly negative correlation with B cells but had positive correlations with CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells in GC samples. The pan-cancer analysis demonstrated that BGN was differentially expressed and related to tumor-infiltrating immune cells across human cancers. This study for the first time comprehensively revealed that BGN was a potential biomarker for the prediction of GC prognosis and tumor immune infiltration.

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ZBTB7A, a potential biomarker for prognosis and immune infiltrates, inhibits progression of endometrial cancer based on bioinformatics analysis and experiments

Cancer Cell International ◽

10.1186/s12935-020-01600-5 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Rong Geng ◽

Yuhua Zheng ◽

Donghua zhou ◽

Qingdong Li ◽

Ruiman Li ◽

...

Keyword(s):

Cell Proliferation ◽

Endometrial Cancer ◽

Zinc Finger Protein ◽

Immune Cell ◽

Vital Role ◽

Cell Infiltration ◽

Marker Genes ◽

Immune Cell Infiltration ◽

Potential Biomarker

Abstract Backgroud ZBTB protein is an important member of the C2H2 zinc finger protein family. As a transcription factor, it is widely involved in the transcriptional regulation of genes, cell proliferation, differentiation, and apoptosis. The ZBTB7A has been largely linked to different kinds of tumors due to its diverse function. However, the value for ZBTB7A in uterine corpus endometrial carcinoma (UCEC) is unclear. Methods In our work, we assessed the importance of ZBTB7A in UCEC. Firstly, Using Oncomine and Tumor Immunoassay Resource (TIMER) databases to evaluate the expression of ZBTB7A. Secondly, we explored the co-expression network of ZBTB7A through the cBioPortal online tool, Metascape, and LinkedOmics. TIMER was also used to explore the relationship between ZBTB7A and tumor immune invasion, and to detect the correlation between the ZBTB7A and the marker genes related to immune infiltration. Finally, CCK8, migration, ChIP assays were introduced to partly validate ZBTB7A function in endometrial cancer cells. Results We found the ZBTB7A expression in TIMER was associated with various cancers, especially UCEC. The decreased expression of ZBTB7A was markedly related to the stage and prognosis of UCEC. Furthermore, ZBTB7A was also related to the expression of various immune markers such as Neutrophils, Dendritic cell, T cell (general), Th1, Th2, and Treg. Finally, we verified that ZBTB7A repressed E2F4 transcription and inhibited cells proliferation and migration. These results indicate that ZBTB7A may play a vital role in regulating immune cell infiltration in UCEC, and is a valuable prognostic marker. Conclusions In summary, we demonstrate that ZBTB7A is notably downregulated in UCEC, plays a vital role in regulating immune cell infiltration, possesses diagnostic and prognostic values and attenuates E2F4 transcription and cell proliferation, migration in vitro.

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Identification and validation of hub genes of synovial tissue for patients with osteoarthritis and rheumatoid arthritis

10.21203/rs.3.rs-564869/v1 ◽

2021 ◽

Author(s):

Yanzhi Ge ◽

Zuxiang Chen ◽

Yanbin Fu ◽

Li Zhou ◽

Haipeng Xu ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

Differentially Expressed Genes ◽

Large Scale ◽

Molecular Mechanisms ◽

Immune Cell ◽

Interaction Network ◽

Differentially Expressed ◽

Specific Gene ◽

Hub Genes

Abstract Osteoarthritis (OA) and rheumatoid arthritis (RA) were two major joint diseases with partially common phenotypes and genotypes. This study aimed to determine the mechanistic similarities and differences between osteoarthritis and rheumatoid arthritis by analyzing the differentially expressed genes and signaling pathways. Microarray data of osteoarthritis and rheumatoid arthritis were obtained from the Gene Expression Omnibus. By integrating multiple gene data sets, specific differentially expressed genes (DEGs) were identified in synovial membrane samples from patients and healthy donations. Then, the Gene ontology significant functions annotation, Kyoto Encyclopedia of Genes and Genomes pathways and protein-protein interaction network analysis were conducted. Moreover, CIBERSORT was used to further distinguish OA and RA in immune infiltration. Finally, animal experimentation was conducted and the establishment of model, which was verified using PCR in the mouse. As an overlapping process, we identified 1116 DEGs between OA and RA. It was indicated that specific gene signatures differed significantly between OA and RA connected with the distinct pathways. Of identified DEGs, 9 immune cell types among 22 were identified to distinguish from each other. The qRT-PCR result showed that the eight-tenths expression levels of the hub genes were significantly increased in OA samples (P < 0.05). This large-scale gene expression study provided new insights for disease-associated genes and molecular mechanisms as well as their associated function in osteoarthritis and rheumatoid arthritis, which simultaneously offer a new direction for biomarker development and the distinguishment of gene-level mechanisms between osteoarthritis and rheumatoid arthritis.

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AHR Signaling Dampens Inflammatory Signature in Neonatal Skin γδ T Cells

International Journal of Molecular Sciences ◽

10.3390/ijms21062249 ◽

2020 ◽

Vol 21 (6) ◽

pp. 2249 ◽

Cited By ~ 3

Author(s):

Katja Merches ◽

Alfonso Schiavi ◽

Heike Weighardt ◽

Swantje Steinwachs ◽

Nadine Teichweyde ◽

...

Keyword(s):

T Cells ◽

Differentially Expressed Genes ◽

Immune Cell ◽

Ion Homeostasis ◽

Γδ T Cells ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Immune Cell Population ◽

Deficient Mice

Background Aryl hydrocarbon receptor (AHR)-deficient mice do not support the expansion of dendritic epidermal T cells (DETC), a resident immune cell population in the murine epidermis, which immigrates from the fetal thymus to the skin around birth. Material and Methods In order to identify the gene expression changes underlying the DETC disappearance in AHR-deficient mice, we analyzed microarray RNA-profiles of DETC, sorted from the skin of two-week-old AHR-deficient mice and their heterozygous littermates. In vitro studies were done for verification, and IL-10, AHR repressor (AHRR), and c-Kit deficient mice analyzed for DETC frequency. Results We identified 434 annotated differentially expressed genes. Gene set enrichment analysis demonstrated that the expression of genes related to proliferation, ion homeostasis and morphology differed between the two mouse genotypes. Importantly, with 1767 pathways the cluster-group “inflammation” contained the majority of AHR-dependently regulated pathways. The most abundant cluster of differentially expressed genes was “inflammation.” DETC of AHR-deficient mice were inflammatory active and had altered calcium and F-actin levels. Extending the study to the AHRR, an enigmatic modulator of AHR-activity, we found approximately 50% less DETC in AHRR-deficient mice than in wild-type-littermates. Conclusion AHR-signaling in DETC dampens their inflammatory default potential and supports their homeostasis in the skin.

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Identification of VCAM1 as a Novel Biomarker in the Immune Microenvironment of Gastric Cancer by Comprehensive Bioinformatics Analysis

10.21203/rs.3.rs-1213974/v1 ◽

2022 ◽

Author(s):

Xin Jiang ◽

Di Chen ◽

Mengmeng Wang ◽

Yushuang Xu ◽

Mengjun Qiu ◽

...

Keyword(s):

Gastric Cancer ◽

Differentially Expressed Genes ◽

Immune Cell ◽

Interaction Network ◽

Differentially Expressed ◽

Cell Infiltration ◽

High Morbidity ◽

Immune Cell Infiltration ◽

Immune Microenvironment ◽

Cox Analysis

Abstract Background and Purpose Gastric cancer (GC) is a common malignant tumor of the digestive tract worldwide and has high morbidity and mortality. The tumor immune microenvironment (TIME), especially the immune cell infiltration, plays an important role in the progression and prognosis of GC. In this study, we investigated the TIME-related genes and explored their role in the GC immune microenvironment. Method We used ssGSEA to assess the immune cell infiltration in 375 patients with GC downloaded from TCGA. Then GC samples were divided into high-, medium-, and low-immune cell infiltration groups by hierarchical clustering. Differentially expressed genes analysis were further proceed between groups to determine TIME-related differentially expressed genes (DEGs). By protein interaction network and Cox analysis, the angiogenesis gene was intersected. The results showed that vascular cell adhesion molecular 1 (VCAM1) was the most critical gene. We further analyze the importance of VCAM1 in the progression of GC and its role in the GC microenvironment. Results We identified 463 TIME-associated DEGs and found that VCAM1 was involved in development and prognosis of GC. Further analysis revealed that VCAM1 was involved in the regulation of immune, vascular, and metastasis-related signaling pathways. Immuno-correlation analysis showed that VCAM1 expression was associated with various immune infiltrating cells, including macrophages and T cells. In addition, combined with online database prediction analysis, we speculated that VCAM1 expression in GC could be enhanced by AC104211.1 sponge Has-mir-183-5p. Conclusion VCAM1 may be involved in the regulation of immune state and angiogenesis in the TIME in GC. This protein could be a promising therapeutic target and prognostic biomarker for GC.

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