Retracted : Targeting of SPP1 by microRNA‐340 inhibits gastric cancer cell epithelial–mesenchymal transition through inhibition of the PI3K/AKT signaling pathway

Secreted phosphoprotein 1 regulates natural compound 3',4',5,7-tetrahydroxyflavone to inhibit mast cell-mediated allergic inflammation

BACKGROUND

Mast cells (MCs) are important effector cells in anaphylaxis and anaphylactic disease. 3',4',5,7-tetrahydroxyflavone (THF) presents in many medicinal plants and exerts a variety of pharmacological effects. In this study, we evaluated the effect of THF on C48/80-induced anaphylaxis and the mechanisms underlying its effects, including the role of secreted phosphoprotein 1 (SPP1), which has not been reported to IgE-independent MC activation.

RESULTS

THF inhibited C48/80-induced Ca2+ flow and degranulation via the PLCγ/PKC/IP3 pathway in vitro. RNA-seq showed that THF inhibited the expression of SPP1 and downstream molecules. SPP1 is involved in pseudo-anaphylaxis reactions. Silencing SPP1 affects the phosphorylation of AKT and P38. THF suppressed C48/80-induced paw edema, hypothermia and serum histamine, and chemokines release in vivo.

CONCLUSIONS

Our results validated SPP1 is involved in IgE-independent MC activation anaphylactoid reactions. THF inhibited C48/80-mediated anaphylactoid reactions both in vivo and in vitro, suppressed calcium mobilization and inhibited SPP1-related pathways.

Identification of four metabolic subtypes and key prognostic markers in lung adenocarcinoma based on glycolytic and glutaminolytic pathways

BACKGROUND

Glucose and glutamine are the main energy sources for tumor cells. Whether glycolysis and glutaminolysis play a critical role in driving the molecular subtypes of lung adenocarcinoma (LUAD) is unknown. This study attempts to identify LUAD metabolic subtypes with different characteristics and key genes based on gene transcription profiling data related to glycolysis and glutaminolysis, and to construct prognostic models to facilitate patient outcome prediction.

METHODS

LUAD related data were obtained from the Cancer Genome Atlas and Gene Expression Omnibus, including TCGA-LUAD, GSE42127, GSE68465, GSE72094, GSE29013, GSE31210, GSE30219, GSE37745, GSE50081. Unsupervised consensus clustering was used for the identification of LUAD subtypes. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and CytoNCA App in Cytoscape 3.9.0 were used for the screening of key genes. The Cox proportional hazards model was used for the construction of the prognostic risk model. Finally, qPCR analysis, immunohistochemistry and immunofluorescence colocalization were used to validate the core genes of the model.

RESULT

This study identified four distinct characterized LUAD metabolic subtypes, glycolytic, glutaminolytic, mixed and quiescent types. The glycolytic type had a worse prognosis than the glutaminolytic type. Nine genes (CXCL8, CNR1, AGER, ALB, S100A7, SLC2A1, TH, SPP1, LEP) were identified as hub genes driving the glycolytic/glutaminolytic LUAD. In addition, the risk assessment model constructed based on three genes (SPP1, SLC2A1 and AGER) had good predictive performance and could be validated in multiple independent external LUAD cohorts. These three genes were differentially expressed in LUAD and lung normal tissues, and might be potential prognostic markers for LUAD.

CONCLUSION

LUAD can be classified into four different characteristic metabolic subtypes based on the glycolysis- and glutaminolysis-related genes. Nine genes (CXCL8, CNR1, AGER, ALB, S100A7, SLC2A1, TH, SPP1, LEP) may play an important role in the subtype-intrinsic drive. This metabolic subtype classification, provides new biological insights into the previously established LUAD subtypes.

Gene Regulatory Network-Classifier: Gene Regulatory Network-Based Classifier and Its Applications to Gastric Cancer Drug (5-Fluorouracil) Marker Identification

The complex mechanisms of diseases involve the disturbance of the molecular network, rather than disorder in a single gene, implying that single gene-based analysis is insufficient to understand these mechanisms. Gene regulatory networks (GRNs) have attracted a lot of interest and various approaches have been developed for their statistical inference and gene network-based analysis. Although various computational methods have been developed, relatively little attention has been paid to incorporation of biological knowledge into the computational approaches. Furthermore, existing studies on network-based analysis perform prediction/classification of status of cell lines based on preconstructed GRNs, implying that we cannot extract prediction/classification-specific gene networks, leading to difficulty in interpretation of biological mechanisms and marker identification related to the status of cancer cell lines. We developed a novel strategy to build a GRN-based classifier, called a GRN-classifier. The proposed GRN-classifier estimates GRNs and classifies cell lines simultaneously, where the gene network is estimated to minimize error in gene network estimation and the negative log-likelihood for classifying cell lines. Thus, we can identify biological status-specific gene regulatory systems, enabling us to achieve biologically reliable interpretation of the classification. We also propose an algorithm to implement the GRN-classifier based on coordinate descent update. Monte Carlo simulations were conducted to examine performance of the GRN-classifier. Results: Our strategy provides effective results in feature selection in the classification model and edge selection in gene network estimation. The GRN-classifier also shows outstanding classification accuracy. We apply the GRN-classifier to classify cancer cell lines into anticancer drug-related status, that is, 5-fluorouracil (5-FU)-sensitive/resistant and 5-FU target/nontarget cancer cell lines. We then identified 5-FU markers based on 5-FU-related status classification-specific gene networks. The mechanisms of the identified markers were verified through literature survey. Our results suggest that the molecular interplay between MYOF and AHNAK2 may play a crucial role in drug resistance and can provide information on the chemotherapy efficiency of 5-FU. It is also suggested that suppression of the identified 5-FU markers, including MYOF/AHNAK2 and AKR1C1/AKR1C3 may improve 5-FU resistance of cancer cell lines.

Identification of Key Biomarkers and Candidate Molecules in Non-Small-Cell Lung Cancer by Integrated Bioinformatics Analysis

Background

Non-small cell lung cancer (NSCLC) is the most prevalent malignant tumor of the lung cancer, for which the molecular mechanisms remain unknown. In this study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC by bioinformatics analysis.

Methods

From the Gene Expression Omnibus database, GSE118370 and GSE10072 microarray datasets were obtained. Identifying the differentially expressed genes (DEGs) between lung adenocarcinoma and normal samples was done. By using bioinformatics tools, a protein-protein interaction (PPI) network was constructed, modules were analyzed, and enrichment analyses were performed. The expression and prognostic values of 14 hub genes were validated by the GEPIA database, and the correlation between hub genes and survival in lung adenocarcinoma was assessed by UALCAN, cBioPortal, String and Cytoscape, and Timer tools.

Results

We found three genes (PIK3R1, SPP1, and PECAM1) that have a clear correlation with OS in the lung adenocarcinoma patient. It has been found that lung adenocarcinoma exhibits high expression of SPP1 and that this has been associated with poor prognosis, while low expression of PECAM1 and PIK3R1 is associated with poor prognosis (P < 0.05). We also found that the expression of SPP1 was associated with miR-146a-5p, while the high expression of miR-146a-5p was related to good prognosis (P < 0.05). On the contrary, the lower miR-21-5p on upstream of PIK3R1 is associated with a higher surviving rate in cancer patients (P < 0.05). Finally, we found that the immune checkpoint genes CD274(PD-L1) and PDCD1LG2(PD-1) were also related to SPP1 in lung adenocarcinoma.

Conclusions

The results indicated that SPP1 is a cancer promoter (oncogene), while PECAM1 and PIK3R1 are cancer suppressor genes. These genes take part in the regulation of biological activities in lung adenocarcinoma, which provides a basis for improving detection and immunotherapeutic targets for lung adenocarcinoma.

IGFBP5 is Upregulated and Associated with Poor Prognosis in Colorectal Cancer

Purpose

This study aimed to investigate the role of IGFBP5 in colorectal cancer (CRC) and the relationship between the expression of IGFBP5 and clinicopathological parameters in CRC patients.

Patients and Methods

Immunohistochemical analysis was used to detect the expression of IGFBP5 and its correlation with clinicopathological parameters of CRC patients. Prognosis analysis, gene set enrichment analysis, and protein interaction network analysis were performed using bioinformatics analysis. The Genomics of Drug Sensitivity in Cancer (GDSC) dataset was used to analyze the correlation between the expression of IGFBP5 and drug resistance.

Results

Immunohistochemical analysis revealed that the expression of IGFBP5 was significantly higher in CRC tissues than in para-cancerous tissues (P < 0.05). High expression of IGFBP5 was associated with tumor differentiation and the N stage of CRC (P < 0.05). Moreover, high expression of IGFBP5 predicted worse overall survival and disease-free survival in CRC patients (P < 0.05). The expression of IGFBP5 was associated with cell–matrix adhesion, extracellular matrix binding, and collagen binding (P < 0.05). Furthermore, IGFBP5 was involved in the Hedgehog signaling pathway and PI3K-Akt signaling pathway (P < 0.05). IGF1, IGF2, SPP1, LTBP1, and FAM20C were most closely related to IGFBP5.

Conclusion

The expression of IGFBP5 is upregulated and associated with tumor differentiation, lymph node metastasis, drug resistance, and prognosis in CRC patients.

Metformin suppresses lung adenocarcinoma by downregulating long non-coding RNA (lncRNA) AFAP1-AS1 and secreted phosphoprotein 1 (SPP1) while upregulating miR-3163

AFAP1-AS1 plays a pro-tumor role in lung cancer. However, no investigation has focused on whether it is involved in the anticancer activity of metformin (Met) in the treatment of lung adenocarcinoma (LUAD). Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed to detect the expression of long non-coding (lnc)RNA AFAP1-AS1, the microRNA (miR)-3163, and secreted phosphoprotein 1 (SPP1) in LUAD tissues, or of A549 and H3122 cells. Cell Counting Kit-8, wound scratch, and cell invasion assays were performed to evaluate the effect of the overexpression of lncRNA AFAP1-AS1, miR-3163, and SPP1 on the malignant behaviors of A549 and H3122 cells. Phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) signaling pathway-related proteins were detected by Western blot analysis. Dual luciferase reporter or RIP assays were used to determine the interplay between AFAP1-AS1 and miR-3163, or of miR-3163 and SPP1. Met inhibits the malignant characteristics of A549 and H3122 cells in vitro. GEPIA database analysis showed that AFAP1-AS1 is a highly expressed lncRNA in LUAD tissues, which was validated by RT-qPCR. Overexpression of AFAP1-AS1 suppressed the met-mediated anti-tumor activity in A549 and H3122 cells, while AFAP1-AS1 silencing promoted it. Met inhibited AFAP1-AS1 expression, which resulted in reduced proliferation, migration, and invasion in A549 and H3122 cells. This led to AFAP1-AS1-mediated suppression of miR-3163 and, subsequently, the upregulation of SPP1. Met exerts its antitumor activities by regulating the AFAP1-AS1/miR-3163/SPP1/PI3K/Akt/mTOR axis. Our findings deepen our understanding of mechanisms underlying anti-tumor effect of Met in LUAD.

Bioinformatics Analysis and Identification of Potential Genes Associated with Pathogenesis and Prognosis of Gastric Cancer

OBJECTIVE

Gastric cancer (GC) is a deadly cancer and a challenging public health problem globally. This study aimed to analyze potential genes associated with pathogenesis and prognosis of gastric cancer.

METHODS

This work selected the overlapping differentially expressed genes (DEGs) in GC from four datasets, the GSE29272, GSE29998, GSE54129 and GSE118916 Gene Expression Omnibus databases. These DEGs were used to carry out comprehensive bioinformatic analysis to analyze the related functions and pathways enriched, the relative expression levels and immune infiltrates, the prognostic characteristics and the interaction network.

RESULTS

In total, 55 DEGs increased while 98 decreased in their expression levels. For those DEGs with increased expression, they were mostly concentrated on "focal adhesion" and "ECM-receptor interaction", whereas DEGs with decreased expression were mostly associated with "gastric acid secretion" and "drug metabolism cytochrome P450". MCODE and ClueGO results were then integrated to screen 10 hub genes, which were FN1, COL1A1, COL3A1, BGN, TIMP1, COL1A2, LUM, VCAN, COL5A2 and SPP1. Survival analysis revealed that higher expression of the ten hub genes significantly predicted lower overall survival of GC patients. TIMP1 was most significantly related to neutrophils, CD8⁺ T cells, as well as dendritic cells, while LUM was most significantly related to macrophages.

CONCLUSION

Immunohistochemistry results and functional testing showed that the expression of COL5A2 was elevated in GC and that it might be a key gene in GC tumorigenesis.

miR-153-3p Attenuates the Development of Gastric Cancer by Suppressing SphK2

Gastric cancer (GC) is the second leading cause of cancer-related mortality worldwide. MicroRNAs (miRNAs) have been extensively reported to play a role in GC development; however, it remains unknown whether miR-153-3p participates in the nosogenesis of GC. GC tissues along with the adjacent nontumor tissues were obtained from 50 patients with GC. Moreover, we incubated human GC cell lines (SGC7901, AGS, MGC803, and BGC823) and a gastric epithelial cell line (GES-1) and then transfected BGC823 cells with miR-153-3p and DNA/SphK2 vector to determine the action of miR-153-3p and SphK2 on GC. RT-qPCR was performed to determine the levels of miR-153-3p and sphingosine kinase 2 (SphK2). The viability of BGC823 cells was measured by the CCK-8 assay, while wound healing assays and transwell assays were used to measure the migration and invasion ability of BGC823 cells. Western blotting analysis and immunohistochemistry (IHC) were conducted to evaluate the level of SphK2. The binding ability of miR-153-3p and SphK2 was determined by dual-luciferase reporter assays. The expression level of miR-153-3p was reduced in GC tissues and cells, while the SphK2 was enhanced. An increase in miR-153-3p level led to a decline in the growth and metastasis of GC cells and increased their apoptosis. Moreover, a decrease in miR-153-3p level elevated GC cells growth and metastasis, and attenuated their apoptosis. SphK2 was also corroborated as a downstream gene of miR-153-3p. Here, SphK2 expression was elevated in GC tissues and cells, indicating SphK2 might be involved in the development of GC. Rescue assays showed that miR-153-3p could reverse the effect of SphK2 on the cell growth, metastasis, and the apoptosis of GC cells. In conclusion, this study showed that miR-153-3p suppressed the growth and metastasis in GC cells by regulating SphK2, which might facilitate the search for novel biomarkers to treat GC.

Comprehensive Analysis to Identify SPP1 as a Prognostic Biomarker in Cervical Cancer

Background: SPP1, secreted phosphoprotein 1, is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family. Previous studies have proven SPP1 overexpressed in a variety of cancers and can be identified as a prognostic factor, while no study has explored the function and carcinogenic mechanism of SPP1 in cervical cancer. Methods: We aimed to demonstrate the relationship between SPP1 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated SPP1 expression of cervical cancer in the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of SPP1 as a differentiating factor by the area under curve (AUC) score. Cox regression and logistic regression were performed to evaluate factors associated with prognosis. The SPP1-binding protein network was built by the STRING tool. Enrichment analysis by the R package clusterProfiler was used to explore potential function of SPP1. The single-sample GSEA (ssGSEA) method from the R package GSVA and TIMER database were used to investigate the association between the immune infiltration level and SPP1 expression in cervical cancer. Results: Pan-cancer data analysis showed that SPP1 expression was higher in most cancer types, including cervical cancer, and we got the same result in the GEO database. The ROC curve suggested that SPP1 could be a potential diagnostic biomarker (AUC = 0.877). High SPP1 expression was associated with poorer overall survival (OS) (P = 0.032). Further enrichment and immune infiltration analysis revealed that high SPP1 expression was correlated with regulating the infiltration level of neutrophil cells and some immune cell types, including macrophage and DC. Conclusion: SPP1 expression was higher in cervical cancer tissues than in normal cervical epithelial tissues. It was significantly associated with poor prognosis and immune cell infiltration. Thus, SPP1 may become a promising prognostic biomarker for cervical cancer patients.

EMT-related genes are unlikely to be involved in extracapsular growth of lymph node metastases in gastric cancer

BACKGROUND

In gastric cancer (GC), extracapsular growth (ECG) pattern of lymph node metastases is associated with decreased overall survival rates compared to intracapsular lymph node metastases (ICG). Epithelial-to-mesenchymal transition (EMT) plays a pivotal role in hematogenous metastatic spread. Aim of the present study was to analyze if EMT related genes are involved in the growth pattern of lymph node metastases in GC.

METHODS

Out of our prospective database with 529 patients who underwent surgical resection for GC between 2002 and 2014 forty lymph node positive patients were identified (20 ECG, 20 ICG). The expression of 84 EMT-associated genes were analyzed by RT2 Profiler PCR Array (n = 20). Results were validated by Real-Time PCR (n = 20).

RESULTS

GC with ECG showed differently expressed EMT related genes. GC leading to ECG showed an upregulation of three and downregulation of eleven genes. Those differences, however, could not be confirmed in PCR analysis.

CONCLUSIONS

This study demonstrates that EMT related genes are not responsible for the different growth patterns of lymph node metastases in GC. Further studies are required to evaluate the underlying mechanisms of ECG in GC as it might provide a potential therapeutic target for this subgroup of more aggressive tumors in the future.

The lncRNA-miRNA-mRNA ceRNA network in mural granulosa cells of patients with polycystic ovary syndrome: an analysis of Gene Expression Omnibus data

Background

Polycystic ovary syndrome (PCOS) is one of the most common endocrine abnormalities in women of reproductive age. In this study, we set out to construct a molecular long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) network according to the competitive endogenous RNA (ceRNA) theory and obtain insights into the related biological characteristics and pathways.

Methods

We downloaded two gene expression profile datasets of mural granulosa cells (MGCs) of women with PCOS and healthy women without PCOS (GSE84376 and GSE106724) from Gene Expression Omnibus (GEO) DataSets. Using GEO2R, we identified the mRNAs and non-coding RNAs with differential expression. The DIANA-microT-CDS algorithm was applied to predict the genes targeted by the differentially expressed miRNAs. The lncRNA-miRNA interactions were predicted using DIANA-LncBase v2. Then, we constructed the lncRNA-miRNA-mRNA network. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed to identify the functions and enriched pathways of the genes. Subsequently, STRING was used to construct the protein-protein interaction (PPI) network. cytoHubba in Cytoscape was used to rank the hub genes, and finally, PPI modules were screened with Cytoscape MCODE.

Results

There were 462 mRNAs, 2,464 lncRNAs, and 55 miRNAs which showed differential expression between the MGCs of patients with PCOS and those of healthy controls. Based on the PPI analysis, differentially expressed genes (DEGs) were significantly enriched in retinol metabolism, drug metabolism—cytochrome P450, malaria, the Hippo signaling pathway, and glycine, serine, and threonine metabolism. The ceRNA network contained 71 lncRNA nodes, 14 miRNA nodes, and 69 mRNA nodes, as well as 167 edges. We identified some novel genes and non-coding RNAs that might be involved in PCOS, including CD163, MRC1, VSIG4, CCL2, CCR2, SPP1, hsa-miR-3135b, hsa-miR-4649-3p, hsa-miR-1231, hsa-miR-3609, and hsa-miR-4433b-3p.

Conclusions

This study identified a novel lncRNA-miRNA-mRNA network based on the ceRNA mechanism in PCOS. Some novel genes and non-coding RNAs that may be involved in the occurrence and development of PCOS were excavated, including CD163, MRC1, VSIG4, CCL2, CCR2, SPP1, hsa-miR-3135b, hsa-miR-4649-3p, hsa-miR-1231, hsa-miR-3609, and hsa-miR-4433b-3p. However, our findings need to be validated by in vivo and in vitro experiments.

Overview on the Role of E-Cadherin in Gastric Cancer: Dysregulation and Clinical Implications

Gastric cancer is the fifth most common cancer and the third most common cause of cancer death all over the world. E-cadherin encoded by human CDH1 gene plays important roles in tumorigenesis as well as in tumor progression, invasion and metastasis. Full-length E-cadhrin tethered on the cell membrane mainly mediates adherens junctions between cells and is involved in maintaining the normal structure of epithelial tissues. After proteolysis, the extracellular fragment of the full-length E-cadhein is released into the extracellular environment and the blood, which is called soluble E-cadherin (sE-cadherin). sE-cadherin promots invasion and metastasis as a paracrine/autocrine signaling molecule in the progression of various types of cancer including gastric cancer. This review mainly summarizes the dysregulation of E-cadherin and the regulatory roles in the progression, invasion, metastasis, and drug-resistance, as well as its clinical applications in diagnosis, prognosis, and therapeutics of gastric cancer.

Integrated bioinformatics analysis of differentially expressed genes and immune cell infiltration characteristics in Esophageal Squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a life-threatening thoracic tumor with a poor prognosis. The role of molecular alterations and the immune microenvironment in ESCC development has not been fully elucidated. The present study aimed to elucidate key candidate genes and immune cell infiltration characteristics in ESCC by integrated bioinformatics analysis. Nine gene expression datasets from the Gene Expression Omnibus (GEO) database were analysed to identify robust differentially expressed genes (DEGs) using the robust rank aggregation (RRA) algorithm. Functional enrichment analyses showed that the 152 robust DEGs are involved in multiple processes in the tumor microenvironment (TME). Immune cell infiltration analysis based on the 9 normalized GEO microarray datasets was conducted with the CIBERSORT algorithm. The changes in macrophages between ESCC and normal tissues were particularly obvious. In ESCC tissues, M0 and M1 macrophages were increased dramatically, while M2 macrophages were decreased. A robust DEG-based protein–protein interaction (PPI) network was used for hub gene selection with the CytoHubba plugin in Cytoscape. Nine hub genes (CDA, CXCL1, IGFBP3, MMP3, MMP11, PLAU, SERPINE1, SPP1 and VCAN) had high diagnostic efficiency for ESCC according to receiver operating characteristic (ROC) curve analysis. The expression of all hub genes except MMP3 and PLAU was significantly related to macrophage infiltration. Univariate and multivariate regression analyses showed that a 7-gene signature constructed from the robust DEGs was useful for predicting ESCC prognosis. Our results might facilitate the exploration of potential targeted TME therapies and prognostic evaluation in ESCC.

Plastin-3 is a diagnostic and prognostic marker for pancreatic adenocarcinoma and distinguishes from diffuse large B-cell lymphoma

BACKGROUND

Altered Plastin-3 (PLS3; an actin-binding protein) expression was associated with human carcinogenesis, including pancreatic ductal adenocarcinoma (PDA). This study first assessed differentially expressed genes (DEGs) and then bioinformatically and experimentally confirmed PLS3 to be able to predict PDA prognosis and distinguish PDA from diffuse large B-cell lymphoma.

METHODS

This study screened multiple online databases and revealed DEGs among PDA, normal pancreas, diffuse large B-cell lymphoma (DLBCL), and normal lymph node tissues and then focused on PLS3. These DEGs were analyzed for Gene Ontology (GO) terms, Kaplan-Meier curves, and the log-rank test to characterize their association with PDA prognosis. The receiver operating characteristic curve (ROC) was plotted, and Spearman's tests were performed. Differential PLS3 expression in different tissue specimens (n = 30) was evaluated by reverse transcription quantitative polymerase chain reaction (RT-qPCR).

RESULTS

There were a great number of DEGs between PDA and lymph node, between PDA and DLBCL, and between PDA and normal pancreatic tissues. Five DEGs (NET1, KCNK1, MAL2, PLS1, and PLS3) were associated with poor overall survival of PDA patients, but only PLS3 was further verified by the R2 and ICGC datasets. The ROC analysis showed a high PLS3 AUC (area under the curve) value for PDA diagnosis, while PLS3 was able to distinguish PDA from DLBCL. The results of Spearman's analysis showed that PLS3 expression was associated with levels of KRT7, SPP1, and SPARC. Differential PLS3 expression in different tissue specimens was further validated by RT-qPCR.

CONCLUSIONS

Altered PLS3 expression was useful in diagnosis and prognosis of PDA as well as to distinguish PDA from DLBCL.

Regulatory roles of osteopontin in human lung cancer cell epithelial-to-mesenchymal transitions and responses

BACKGROUND

Lung cancer is still the main cause of death in patients with cancer, due to poor understanding of intracellular regulations. Of those, osteopontin (OPN) may induce the epithelial-to-mesenchymal transition (EMT) to promote tumor cell metastasis. The present study aims to evaluate the regulatory mechanism of internal and external OPN in the development of lung cancer.

METHODS

We evaluated genetic variations and different bioinformatics of genes in chromosome 4 among subtypes of lung cancer using global databases. We validated the expression of OPN and EMT-related proteins (e.g., E-cadherin, vimentin) in 208 non-small-cell lung cancer (NSCLC) tumors and the adjacent nontumorous tissues, further to explore the function of OPN in the progression of lung cancer, with a focus on a potential communication between OPN and EMT in the lung cancer.

RESULTS

We found that OPN might act as a target molecule in lung cancer, which is associated with lymph node metastasis, postresection recurrence/metastasis, and prognosis of patients with lung cancer. Biological behaviors and pathological responses of OPN varied among diseases, challenges, and severities. Overexpression of OPN was correlated with the existence of EMT in lung cancer tissues. Internal and external OPN plays the decisive roles in lung cancer cell movement, proliferation, and EMT formation, through the upregulation of OPN-PI3K and OPN-MEK pathways. PI3K and MEK inhibitors downregulated the process of EMT and biological behaviors of lung cancer cells, probably through altering vimentin-associated cytoskeletons.

CONCLUSION

OPN can be a metastasis-associated or specific biomarker for lung cancer and a potential target for antimetastatic treatment.

Relationship between miRNA-433 and SPP1 in the presence of fracture and traumatic brain injury

Limb fracture combined with traumatic brain injury (TBI) is one of the most common multiple injuries and patients often suffer from severe craniocerebral injury combined with long bone fracture of the limbs. The present study examined the expression of osteopontin (SPP1) in the tibial fracture callus and heterotopic ossification tissues in craniocerebral injury and investigated its relationship with miR-433. A total of 26 patients with tibial fracture combined with brain injury were included in the TBI group, and 26 patients with simple tibial fracture were included in the control group. The patients received immobilization treatment and callus was collected during the operation. At the time of steel plate removal tissue ossification samples from patients with heterotopic ossification were collected. Peripheral blood was collected from all patients on the morning of the operation day. Expression of miR-433 and SPP1 mRNA was determined by reverse transcription-quantitative PCR and SPP1 protein expression was measured by western blotting. Dual luciferase reporter assay was used to identify the direct interaction between miR-433 and SPP1 mRNA. The human osteoblast line hFOB1.19 was transfected with agomiR-433 to overexpress miR-433 and expression of SPP1 was also examined. TBI enhanced the incidence of callus formation and heterotopic ossification in patients with fracture but did not alter fracture healing time. SPP1 mRNA and protein expression was elevated in patients who had tibial fracture in combination with craniocerebral injury in comparison with controls By contrast, expression of miR-433 was decreased in patients who had tibial fracture in combination with craniocerebral injury in comparison with controls. miR-433 regulated the expression of SPP1 mRNA and protein by directly binding to the 3'-untranslated region of SPP1 mRNA. The present study suggests that SPP1 mRNA and protein levels are increased in the callus, heterotopic ossification tissues and plasma from patients with tibial fracture combined with brain injury in comparison with controls. This elevation may be due to the reduced expression of miR-433.

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.

Identification of core genes and clinical outcomes in tumors originated from endoderm (gastric cancer and lung carcinoma) via bioinformatics analysis

ABSTRACT

During last decade, bioinformatics analysis has provided an effective way to study the relationship between various genes and biological processes. In this study, we aimed to identify potential core candidate genes and underlying mechanisms of progression of lung and gastric carcinomas which both originated from endoderm. The expression profiles, GSE54129 (gastric carcinoma) and GSE27262 (lung carcinoma), were collected from GEO database. One hundred eleven patients with gastric carcinoma and 21 health people were included in this research. Meanwhile, there were 25 lung carcinoma patients. Then, 75 differentially expressed genes were selected via GEO2R online tool and Venn software, including 31 up-regulated genes and 44 down-regulated genes. Next, we used Database for Annotation, Visualization, and Integrated Discovery and Metascpe software to analyze Kyoto Encyclopedia of Gene and Genome pathway and gene ontology. Furthermore, Cytoscape software and MCODE App were performed to construct complex of these differentially expressed genes . Twenty core genes were identified, which mainly enriched in extracellular matrix-receptor interaction, focal adhesion, and PI3K-Akt pathway (P < .01). Finally, the significant difference of gene expression between cancer tissues and normal tissues in both lung and gastric carcinomas was examined by Gene Expression Profiling Interactive Analysis database. Twelve candidate genes with positive statistical significance (P < .01), COMP CTHRC1 COL1A1 SPP1 COL11A1 COL10A1 CXCL13 CLDN3 CLDN1 matrix metalloproteinases 7 ADAM12 PLAU, were picked out to further analysis. The Kaplan-Meier plotter website was applied to examine relationship among these genes and clinical outcomes. We found 4 genes (ADAM12, SPP1, COL1A1, COL11A1) were significantly associated with poor prognosis in both lung and gastric carcinoma patients (P  < .05). In conclusion, these candidate genes may be potential therapeutic targets for cancer treatment.

Bioinformatics analysis identifies COL1A1, THBS2 and SPP1 as potential predictors of patient prognosis and immunotherapy response in gastric cancer

Background: The present study aimed to use bioinformatics tools to explore pivotal genes associated with the occurrence of gastric cancer (GC) and assess their prognostic significance, and link with clinicopathological parameters. We also investigated the predictive role of COL1A1, THBS2, and SPP1 in immunotherapy.

Materials and methods: We identified differential genes (DEGs) that were up- and down-regulated in the three datasets (GSE26942, GSE13911, and GSE118916) and created protein–protein interaction (PPI) networks from the overlapping DEGs. We then investigated the potential functions of the hub genes in cancer prognosis using PPI networks, and explored the influence of such genes in the immune environment.

Results: Overall, 268 overlapping DEGs were identified, of which 230 were up-regulated and 38 were down-regulated. CytoHubba selected the top ten hub genes, which included SPP1, TIMP1, SERPINE1, MMP3, COL1A1, BGN, THBS2, CDH2, CXCL8, and THY1. With the exception of SPP1, survival analysis using the Kaplan–Meier database showed that the levels of expression of these genes were associated with overall survival. Genes in the most dominant module explored by MCODE, COL1A1, THBS2, and SPP1, were primarily enriched for two KEGG pathways. Further analysis showed that all three genes could influence clinicopathological parameters and immune microenvironment, and there was a significant correlation between COL1A1, THBS2, SPP1, and PD-L1 expression, thus indicating a potential predictive role for GC response to immunotherapy.

Conclusion: ECM–receptor interactions and focal adhesion pathways are of great significance in the progression of GC. COL1A1, THBS2, and SPP1 may help predict immunotherapy response in GC patients.

miR-340: A multifunctional role in human malignant diseases

MicroRNAs (miRNAs) are a class of short non-coding RNAs of approximately 22 nucleotides in length, which function by binding to the 3' UTR sequences of their target mRNAs. It has been reported that dysregulated miRNAs play pivotal roles in numerous diseases, including cancers, such as gastric, breast, colorectal, ovarian, and other cancers. Recent research efforts have been devoted to translating these basic discoveries into clinical applications that could improve the therapeutic outcome in patients with cancer. Early studies have shown that miR-340 may act either as an oncogene or a tumor suppressor by targeting genes related to proliferation, apoptosis, and metastasis, as well as those associated with diagnosis, treatment, chemoresistance, and prognosis. miR-340 has been shown to have a role in other diseases, such as autoimmune diseases, acute stroke, and alcoholic steatohepatitis. Nevertheless, the roles of miR-340 in human malignancies are still unclear, and the associated mechanisms are complex, involving a variety of signaling pathways, such as Wnt/β-catenin and the JAK-STAT pathways. Herein, we review the crucial roles of miR-340 in human cancers through the analysis of the latest research studies, with the aim of clarifying miR-340 function in malignant disease diagnosis, treatment, and prognosis, and to propose further investigations.

Silencing of SPP1 Suppresses Progression of Tongue Cancer by Mediating the PI3K/Akt Signaling Pathway

Background:

In the present study, we aimed to find an effective target for the treatment of tongue cancer using gene chip screening and signal pathway research.

Methods:

We used microarray screening and gene expression profile analyses to find important differentially expressed genes in tongue cancer. We constructed a protein-protein interaction network, and used enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes to screen for important genes. We then silenced the genes of interest in SCC154 cells to study the relationship with the Phosphatidylinositol 3-kinase/Akt signal pathway. Western blot analyses, the 3-(4,5Dimethylthiazol-yl)-2,5Dimethylthiazol-2-yl)-2,5diphenyltetrazolium bromide (MTT) test, and immunofluorescence assays were used to compare the expression levels of Phosphatidylinositol 3-kinase/Akt signal pathway-related proteins, cell viability, and cell proliferation ability in normal SCC154 cells, Si-RNA SCC154 cells, and gene-silenced SCC154 cells. The scratch test, Transwell test, and western blotting were used to determine migration, invasion, and carcinogenesis.

Results:

Using GSE9844, GSE13601, and GSE31056 gene chips, we identified 93 upregulated genes and 76 downregulated genes in tongue cancer. Using the protein-protein interaction network and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we further identified 47 differentially expressed genes. Using Kaplan-Meier plotter online tools, we also identified 3 genes (SPP1, Recombinant Human Secreted Phosphoprotein 1; PLAU, plasminogen activator urinary; and APP, amyloid precursor protein). Compared with normal SCC154 cells and Si-RNA control SCC154 cells, the expressions of Phosphatidylinositol 3-kinase/Akt pathway proteins in si-SPP1 SCC154 cells were significantly decreased (*P < 0.05), and the protein activities and proliferation abilities were also significantly decreased (*P < 0.05), while the migration ability, invasion ability, and cancer forming ability were significantly increased (*P < 0.05).

Conclusion:

Inhibition of the SPP1 gene may have a therapeutic effect on tongue cancer, and could be an effective target for the treatment of this disorder.

MicroRNA in Gastric Cancer Development: Mechanisms and Biomarkers

Gastric cancer (GC) is one of the most common and difficult diseases to treat. The study of signaling pathway regulation by microRNA provides information on the mechanisms of GC development and is the basis for biomarker creation. In this study, a circuit of microRNA interactions with signaling pathways was constructed. The microRNAs, associated with metastasis and chemoresistance, are described. In most cases, microRNAs in GC regulate the Wnt/β-catenin, PI3K/AKT/mTOR, RAS/RAF/ERK/MAPK, NF-kB, TGF-β, and JAK/STAT pathways. Part of the microRNA acts on several target genes that function in different pathways. This often leads to an intensification of the induced processes. MicroRNAs have also been described that have the opposite effect on different pathways, causing different functional consequences. By acting on several target genes, or genes associated with several pathways, microRNAs can function in a signaling network. MicroRNAs associated with metastasis most often interact with the Wnt/β-catenin pathway. MicroRNAs affecting chemoresistance, in most cases, affect the regulators of apoptosis and are associated with the PI3K/AKT/mTOR pathway. The characteristics of microRNAs proposed as candidates for GC biomarkers were analyzed. The currently developed diagnostic and prognostic panels of microRNAs are also considered.

A Novel Four-Gene Signature Associated With Immune Checkpoint for Predicting Prognosis in Lower-Grade Glioma

The overall survival of patients with lower grade glioma (LGG) varies greatly, but the current histopathological classification has limitations in predicting patients’ prognosis. Therefore, this study aims to find potential therapeutic target genes and establish a gene signature for predicting the prognosis of LGG. CD44 is a marker of tumor stem cells and has prognostic value in various tumors, but its role in LGG is unclear. By analyzing three glioma datasets from Gene Expression Omnibus (GEO) database, CD44 was upregulated in LGG. We screened 10 CD44-related genes via protein–protein interaction (PPI) network; function enrichment analysis demonstrated that these genes were associated with biological processes and signaling pathways of the tumor; survival analysis showed that four genes (CD44, HYAL2, SPP1, MMP2) were associated with the overall survival (OS) and disease-free survival (DFS)of LGG; a novel four-gene signature was constructed. The prediction model showed good predictive value over 2-, 5-, 8-, and 10-year survival probability in both the development and validation sets. The risk score effectively divided patients into high- and low- risk groups with a distinct outcome. Multivariate analysis confirmed that the risk score and status of IDH were independent prognostic predictors of LGG. Among three LGG subgroups based on the presence of molecular parameters, IDH-mutant gliomas have a favorable OS, especially if combined with 1p/19q codeletion, which further confirmed the distinct biological pattern between three LGG subgroups, and the gene signature is able to divide LGG patients with the same IDH status into high- and low- risk groups. The high-risk group possessed a higher expression of immune checkpoints and was related to the activation of immunosuppressive pathways. Finally, this study provided a convenient tool for predicting patient survival. In summary, the four prognostic genes may be therapeutic targets and prognostic predictors for LGG; this four-gene signature has good prognostic prediction ability and can effectively distinguish high- and low-risk patients. High-risk patients are associated with higher immune checkpoint expression and activation of the immunosuppressive pathway, providing help for screening immunotherapy-sensitive patients.

Loss of ARID1A induces a stemness gene ALDH1A1 expression with histone acetylation in the malignant subtype of cholangiocarcinoma

Genomic analyses have recently discovered the malignant subtype of human intrahepatic cholangiocarcinoma (ICC) characterized by frequent mutations of chromatin remodeling gene ARID1A; however, the biological and molecular functions still remain obscure. We here examined the clinical and biological significances of ARID1A deficiency in human ICC. Immunohistochemical analysis demonstrated that the loss of ARID1A was an independent prognostic factor for overall survival of ICC patients (P = 0.023). We established ARID1A-knockout (KO) cells by using the CRISPR/Cas9 system from two human cholangiocarcinoma cell lines. ARID1A-KO cells exhibited significantly enhanced migration, invasion, and sphere formation activity. Microarray analysis revealed that ALDH1A1, a stemness gene, was the most significantly elevated genes in ARID1A-KO cells. In addition, ALDH enzymatic activity as a hallmark of cancer stem cells was markedly high in the KO cells. ARID1A and histone deacetylase 1 were directly recruited to the ALDH1A1 promoter region in cholangiocarcinoma cells with undetectable ALDH1A1 expression by chromatin immunoprecipitation assay. The histone H3K27 acetylation level at the ALDH1A1 promoter region was increased in cells when ARID1A was disrupted (P < 0.01). Clinically, inverse correlation between ARID1A and ALDH1A1 expression was also identified in primary ICC (P = 0.018), and ARID1A-negative and ALDH1A1-positve ICCs showed worse prognosis than only ARID1A-negative cases (P = 0.002). In conclusion, ARID1A may function as a tumor suppressor in ICC through transcriptional downregulation of ALDH1A1 expression with decreasing histone H3K27 acetylation. Our studies provide the basis for the development of new epigenetic approaches to ARID1A-negative ICC. Immunohistochemical loss of ARID1A is an independent prognostic factor in intrahepatic cholangiocarcinoma patients. ARID1A recruits HDAC1 to the promoter region of ALDH1A1, a stemness gene, and epigenetically suppresses ALDH1A1 expression with decreasing histone H3K27 acetylation in cholangiocarcinoma cells.

A Network Pharmacology Analysis of the Active Components of the Traditional Chinese Medicine Zuojinwan in Patients with Gastric Cancer

BACKGROUND Zuojinwan (ZJW) is a traditional Chinese prescription normally used for gastritis. Several studies indicated that it could fight against gastric cancer. This study was designed to determine the potential pharmacological mechanism of ZJW in the treatment of gastric cancer. MATERIAL AND METHODS Bioactive compounds and potential targets of ZJW and related genes of gastric cancer were retrieved from public databases. Pharmacological mechanisms including crucial ingredients, potential targets, and signaling pathways were determined using protein-protein interaction (PPI) and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Virtual docking was performed to validate the findings. RESULTS Network analysis identified 47 active ZJW compounds, and 48 potential ZJW target genes linked to gastric cancer. Quercetin, beta-sitosterol, isorhamnetin, wogonin, and baicalein were identified as potential candidate agents. Our PPI analysis results combined with previously published results indicated that matrix metalloproteinases family members MMP9, MMP1, and MMP3 may play key roles in the anti-gastric cancer effect of ZJW. Molecular docking analysis showed that these crucial targets had good affinity for the representative components in ZJW. GO and KEGG enrichment analysis showed that ZJW target genes functioned in multiple pathways for treating gastric cancer, including interleukin-17 signaling and platinum drug resistance. CONCLUSIONS Our results illuminate the active ingredients, associated targets, biological processes, and signaling pathways of ZJW in the treatment of gastric cancer. This study enhances our understanding of the potential effects of ZJW in gastric cancer and demonstrates a feasible method for discovering potential drugs from Chinese medicinal formulas.

Integrated Bioinformatics Analysis Reveals Key Candidate Genes and Pathways Associated With Clinical Outcome in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for approximately 85-90% of all liver cancer cases and has poor relapse-free survival. There are many gene expression studies that have been performed to elucidate the genetic landscape and driver pathways leading to HCC. However, existing studies have been limited by the sample size and thus the pathogenesis of HCC is still unclear. In this study, we performed an integrated characterization using four independent datasets including 320 HCC samples and 270 normal liver tissues to identify the candidate genes and pathways in the progression of HCC. A total of 89 consistent differentially expression genes (DEGs) were identified. Gene-set enrichment analysis revealed that these genes were significantly enriched for cellular response to zinc ion in biological process group, collagen trimer in the cellular component group, extracellular matrix (ECM) structural constituent conferring tensile strength in the molecular function group, protein digestion and absorption, mineral absorption and ECM-receptor interaction. Network system biology based on the protein-protein interaction (PPI) network was also performed to identify the most connected and important genes based on our DEGs. The top five hub genes including osteopontin (SPP1), Collagen alpha-2(I) chain (COL1A2), Insulin-like growth factor I (IGF1), lipoprotein A (LPA), and Galectin-3 (LGALS3) were identified. Western blot and immunohistochemistry analysis were employed to verify the differential protein expression of hub genes in HCC patients. More importantly, we identified that these five hub genes were significantly associated with poor disease-free survival and overall survival. In summary, we have identified a potential clinical significance of these genes as prognostic biomarkers for HCC patients who would benefit from experimental approaches to obtain optimal outcome.

Identification of hub genes and discovery of promising compounds in gastric cancer based on bioinformatics analysis

Aim: To explore the mechanism of gastric carcinogenesis by mining potential hub genes and to search for promising small-molecular compounds for gastric cancer (GC). Materials & methods: The microarray datasets were downloaded from Gene Expression Omnibus database and the genes and compounds were analyzed by bioinformatics-related tools and software. Results: Six hub genes (MKI67, PLK1, COL1A1, TPX2, COL1A2 and SPP1) related to the prognosis of GC were confirmed to be upregulated in GC and their high expression was correlated with poor overall survival rate in GC patients. In addition, eight candidate compounds with potential anti-GC activity were identified, among which resveratrol was closely correlated with six hub genes. Conclusion: Six hub genes identified in the present study may contribute to a more comprehensive understanding of the mechanism of gastric carcinogenesis and the predicted potential of resveratrol may provide valuable clues for the future development of targeted anti-GC inhibitors.

Role of PI3K/AKT pathway in cancer: the framework of malignant behavior

Given that the PI3K/AKT pathway has manifested its compelling influence on multiple cellular process, we further review the roles of hyperactivation of PI3K/AKT pathway in various human cancers. We state the abnormalities of PI3K/AKT pathway in different cancers, which are closely related with tumorigenesis, proliferation, growth, apoptosis, invasion, metastasis, epithelial-mesenchymal transition, stem-like phenotype, immune microenvironment and drug resistance of cancer cells. In addition, we investigated the current clinical trials of inhibitors against PI3K/AKT pathway in cancers and found that the clinical efficacy of these inhibitors as monotherapy has so far been limited despite of the promising preclinical activity, which means combinations of targeted therapy may achieve better efficacies in cancers. In short, we hope to feature PI3K/AKT pathway in cancers to the clinic and bring the new promising to patients for targeted therapies.

The comprehensive upstream transcription and downstream targeting regulation network of miRNAs reveal potential diagnostic roles in gastric cancer

Evidence has shown that miRNAs can be regulated by multiple mechanisms and can participate in tumorigenesis and progression through binding to 3'-UTRs of target mRNAs. The present study identified differentially expressed miRNAs, mRNAs, and TFs by analyzing miRNA-Seq and mRNA-Seq data to construct a TFs/miRNAs/mRNAs regulation network for GC. We found five miRNAs (miR-18a-5p, miR-21-5p, miR-96-5p, miR-182-5p, and miR-196b-5p) that were significantly overexpressed in GC tissues. Clinical analyses indicated that higher miR-21-5p expression was associated with T3 + T4 and stage III + IV. The expression of miR-96-5p, miR-182-5p, and miR-196b-5p were positively correlated with the patients' ages. The five miRNAs had diagnostic efficacy in distinguishing GC from normal tissues. The gene interaction network showed that the five miRNAs were transcriptionally regulated by 11 TFs and negatively regulated 53 mRNA expressions through binding to the 3'-UTRs. Biological pathway analysis suggested that these TFs and target genes were involved in the p53 pathway, epithelial-to-mesenchymal transition, ErbB receptor, mTOR, VEGF, and VEGFR signaling networks. KEGG pathway analysis indicated that these genes were enriched in some cancer-associated pathways, including in GC. The five miRNAs may act as potential diagnostic markers and the TFs/miRNAs/mRNAs network could suggest a regulation mechanism of miRNAs.

Identification of hub genes correlated with the pathogenesis and prognosis of gastric cancer via bioinformatics methods

BACKGROUND

Gastric cancer (GC) is the fourth most common cause of cancer-related deaths in the world and 5-year overall survival (OS) rate is less than 10%. So, it is urgent to identified novel diagnostic and prognostic biomarkers.

METHODS

Twelve GEO (gene expression omnibus) datasets were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between GC and normal tissues were screened and integrated using limma and RobustRankAggreg (RRA) packages in R software. Protein-protein interaction (PPI) network, GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses for DEGs were conducted via STRING and DAVID, respectively. Moreover, Cox regression model was used to construct a gene prognosis signature.

RESULTS

Ten genes (COL1A1, CXCL8, COL3A1, SPP1, COL1A2, TIMP1, CXCL1, BGN, MMP3 and SERPINE1) were identified and might be highly related to GC. Further analysis showed high expression of CXCL8, COL3A1, CXCL1, MMP3 and SERPINE1, were significantly associated with late stage of GC. Lastly, we build a seven-gene prognosis signature (CYP19A1, SERPINE1, CGB5, CALCR, ASGR2, CYTL1 and ABCB5), which can give a good prediction of OS.

CONCLUSIONS

Our article screened out key genes highly associating with GC's developments and prognosis, and it is useful for researcher to further understand GC's molecular basis and direct the synthesis medicine of GC.