Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gastric cancer

Background and objective

The underlying molecular mechanisms of gastric cancer (GC) have yet not been investigated clearly. In this study, we aimed to identify hub genes involved in the pathogenesis and prognosis of GC.

Identification of key genes and pathways in castrate-resistant prostate cancer by integrated bioinformatics analysis

ObjectiveTo identify hub genes and pathways involved in castrate-resistant prostate cancer (CRPC).MethodsThe gene expression profiles of GSE70768 were downloaded from Gene Expression Omnibus (GEO) datasets. A total of 13 CRPC samples and 110 tumor samples were identified. The differentially expressed genes (DEGs) were identified, and the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was performed. Protein-protein interaction (PPI) network module analysis was constructed and performed in Cytoscape software. Weighted correlation network analysis (WGCNA) was conducted to determine hub genes involved in the development and progression of CRPC. The gene expression profiles of GSE80609 were used for validation.ResultsA total of 1738 DEGs were identified, consisting of 962 significantly down-regulated DEGs and 776 significantly upregulated DEGs for the subsequent analysis. GO term enrichment analysis suggested that DEGs were mainly enriched in the extracellular matrix organization, extracellular exosome, extracellular matrix, and extracellular space. KEGG pathway analysis found DEGs significantly enriched in the focal adhesion pathway. PPI network demonstrated that the top 10 hub genes were ALB, ACACB, KLK3, CDH1, IL10, ALDH1A3, KLK2, ALDH3B2, HBA1, COL1A1. Also, WGCNA identified the top 5 hub genes in the turquoise module, including MBD4, BLZF1, PIP5K2B, ZNF486, LRRC37B2. Plus, the Venn diagram demonstrated that HBA1 was the key gene in both GSE70768 and GSE80609 datasets.ConclusionsThese newly identified genes and pathways could help urologists understand the differences in the mechanism between CRPC and PCa. Besides, it might be promising targets for the treatment of CRPC.     

Identification of four novel prognosis biomarkers and potential therapeutic drugs for human colorectal cancer by bioinformatics analysis

Colorectal cancer(CRC)is one of the most deadly cancers in the world with few reliable biomarkers that have been selected into clinical guidelines for prognosis of CRC patients.In this study,mRNA microarray datasets GSE113513,GSE21510,GSE44076,and GSE32323 were obtained from the Gene Expression Omnibus(GEO)and analyzed with bioinformatics to identify hub genes in CRC development.Differentially expressed genes(DEGs)were analyzed using the GEO2 R tool.Gene ontology(GO)and KEGG analyses were performed through the DAVID database.STRING database and Cytoscape software were used to construct a protein-protein interaction(PPI)network and identify key modules and hub genes.Survival analyses of the DEGs were performed on GEPIA database.The Connectivity Map database was used to screen potential drugs.A total of 865 DEGs were identified,including 374 upregulated and 491 downregulated genes.These DEGs were mainly associated with metabolic pathways,pathways in cancer,cell cycle and so on.The PPI network was identified with 863 nodes and 5817 edges.Survival analysis revealed that HMMR,PAICS,ETFDH,and SCG2 were significantly associated with overall survival of CRC patients.And blebbistatin and sulconazole were identified as candidate drugs.In conclusion,our study found four hub genes involved in CRC,which may provide novel potential biomarkers for CRC prognosis,and two potential candidate drugs for CRC.     

The clinical significance and potential molecular mechanism of integrin subunit beta 4 in laryngeal squamous cell carcinoma

The relationship between integrin beta 4 (ITGB4) expression and laryngeal squamous cell carcinoma (LSCC) remains unclarified. The object of the present study was to explore the clinical significance and potential molecular mechanism of ITGB4 in LSCC. The protein level of ITGB4 was significantly higher in 46 LSCC patients than in 26 non-LSCC tissues detected by in-house immunohistochemistry. Consistently, ITGB4 mRNA level was also greatly upregulated based on microarray and RNA-seq data (standard mean difference, SMD = 1.62, 95 % CI: 1.23–2.00). And the area under curves (AUC) of summary receiver operator characteristic (SROC) was 0.87 (95 % CI: 0.84–0.90) based on 172 cases of LSCC and 59 cases of non-cancerous controls. Ninety genes were intersected by the ITGB4 related genes and LSCC differential expressed genes (DEGs) from all available microarray and RNA-seq datasets. Based on Gene Ontology (GO) analysis, the top terms of biological process (BP), cellular component (CC) and molecular function (MF) for the 90 ITGB4 related DEGs were extracellular matrix organization, basement membrane and extracellular matrix structural constituent, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that ITGB4 related DEGs mainly participated in the pathways of ECM-receptor interaction, Focal adhesion and Small cell lung cancer. Moreover, the Protein-Protein Interaction (PPI) network indicated that ITGA3, ITGA5, ITGB4, MET, LAMA3, and COL4A1 might be the core genes of LSCC development related to ITGB4. In conclusion, high ITGB4 expression may lead to the occurrence and development of LSCC via various signaling pathways.     

Differences in key genes in human alveolar macrophages between phenotypically normal smokers and nonsmokers: diagnostic and prognostic value in lung cancer

Objective: To explore the effect of smoking on gene expression in human alveolar macrophages and the value of identified key genes in the early diagnosis and prognosis of lung cancers. Methods: We downloaded three data sets ({"type":"entrez-geo","attrs":{"text":"GSE8823","term_id":"8823"}}GSE8823, {"type":"entrez-geo","attrs":{"text":"GSE2125","term_id":"2125"}}GSE2125, and {"type":"entrez-geo","attrs":{"text":"GSE3212","term_id":"3212"}}GSE3212) from the Gene Expression Omnibus (GEO) database, including 31 non-smoking and 33 smoking human alveolar macrophage samples. We identified common differentially expressed genes (DEGs), from which we obtained module genes and hub genes by using STRING and Cytoscape. Then we analyzed the protein-protein interaction (PPI) network of DEGs, hub genes, and module genes and used David online analysis tool to carry out functional enrichment analysis of DEGs and module genes. Results: A total of 85 differentially expressed genes was obtained, including 42 up-regulated genes and 43 down-regulated genes. The Human Protein Atlas and Survival analysis showed that GBP1, ITGAM, CSF1, SPP1, COL1A1, LAMB1 and THBS1 may be closely associated with the carcinogenesis and prognosis of lung cancer. Conclusion: DEGs, module, and hub genes identified in the present study help explain the effects of smoking on human alveolar macrophages and provide candidate targets for diagnosis and treatment of smoking-related lung cancer.     

Hemizygous deletion of COL3A1, COL5A2, and MSTN causes a complex phenotype with aortic dissection: a lesson for and from true haploinsufficiency

Aortic dilatation/dissection (AD) can occur spontaneously or in association with genetic syndromes, such as Marfan syndrome (MFS; caused by FBN1 mutations), MFS type 2 and Loeys–Dietz syndrome (associated with TGFBR1/TGFBR2 mutations), and Ehlers–Danlos syndrome (EDS) vascular type (caused by COL3A1 mutations). Although mutations in FBN1 and TGFBR1/TGFBR2 account for the majority of AD cases referred to us for molecular genetic testing, we have obtained negative results for these genes in a large cohort of AD patients, suggesting the involvement of additional genes or acquired factors. In this study we assessed the effect of COL3A1 deletions/duplications in this cohort. Multiplex ligation-dependent probe amplification (MLPA) analysis of 100 unrelated patients identified one hemizygous deletion of the entire COL3A1 gene. Subsequent microarray analyses and sequencing of breakpoints revealed the deletion size of 3 408 306 bp at 2q32.1q32.3. This deletion affects not only COL3A1 but also 21 other known genes (GULP1, DIRC1, COL5A2, WDR75, SLC40A1, ASNSD1, ANKAR, OSGEPL1, ORMDL1, LOC100129592, PMS1, MSTN, C2orf88, HIBCH, INPP1, MFSD6, TMEM194B, NAB1, GLS, STAT1, and STAT4), mutations in three of which (COL5A2, SLC40A1, and MSTN) have also been associated with an autosomal dominant disorder (EDS classical type, hemochromatosis type 4, and muscle hypertrophy). Physical and laboratory examinations revealed that true haploinsufficiency of COL3A1, COL5A2, and MSTN, but not that of SLC40A1, leads to a clinical phenotype. Our data not only emphasize the impact/role of COL3A1 in AD patients but also extend the molecular etiology of several disorders by providing hitherto unreported evidence for true haploinsufficiency of the underlying gene.     

Dysregulation of the epigenome in triple-negative breast cancers: Basal-like and claudin-low breast cancers express aberrant DNA hypermethylation

A subset of human breast cancer cell lines exhibits aberrant DNA hypermethylation that is characterized by hyperactivity of the DNA methyltransferase enzymes, overexpression of DNMT3b, and concurrent methylation-dependent silencing of numerous epigenetic biomarker genes. The objective of this study was to determine if this aberrant DNA hypermethylation (i) is found in primary breast cancers, (ii) is associated with specific breast cancer molecular subtypes, and (iii) influences patient outcomes. Analysis of epigenetic biomarker genes (CDH1, CEACAM6, CST6, ESR1, GNA11, MUC1, MYB, SCNN1A, and TFF3) identified a gene expression signature characterized by reduced expression levels or loss of expression among a cohort of primary breast cancers. The breast cancers that express this gene expression signature are enriched for triple-negative subtypes — basal-like and claudin-low breast cancers. Methylation analysis of primary breast cancers showed extensive promoter hypermethylation of epigenetic biomarker genes among triple-negative breast cancers, compared to other breast cancer subclasses where promoter hypermethylation events were less frequent. Furthermore, triple-negative breast cancers either did not express or expressed significantly reduced levels of protein corresponding to methylation-sensitive biomarker gene products. Together, these findings suggest strongly that loss of epigenetic biomarker gene expression is frequently associated with gene promoter hypermethylation events. We propose that aberrant DNA hypermethylation is a common characteristic of triple-negative breast cancers and may represent a fundamental biological property of basal-like and claudin-low breast cancers. Kaplan–Meier analysis of relapse-free survival revealed a survival disadvantage for patients with breast cancers that exhibit aberrant DNA hypermethylation. Identification of this distinguishing trait among triple-negative breast cancers forms the basis for development of new rational therapies that target the epigenome in patients with basal-like and claudin-low breast cancers.     

NLRP3 inflammasome blockade reduces adipose tissue inflammation and extracellular matrix remodeling

The NLRP3-IL-1β pathway plays an important role in adipose tissue (AT)-induced inflammation and the development of obesity-associated comorbidities. We aimed to determine the impact of NLRP3 on obesity and its associated metabolic alterations as well as its role in adipocyte inflammation and extracellular matrix (ECM) remodeling. Samples obtained from 98 subjects were used in a case−control study. The expression of different components of the inflammasome as well as their main effectors and inflammation- and ECM remodeling-related genes were analyzed. The impact of blocking NLRP3 using siRNA in lipopolysaccharide (LPS)-mediated inflammation and ECM remodeling signaling pathways was evaluated. We demonstrated that obesity (P < 0.01), obesity-associated T2D (P < 0.01) and NAFLD (P < 0.05) increased the expression of different components of the inflammasome as well as the expression and release of IL-1β and IL-18 in AT. We also found that obese patients with T2D exhibited increased (P < 0.05) hepatic gene expression levels of NLRP3, IL1B and IL18. We showed that NLRP3, but not NLRP1, is regulated by inflammation and hypoxia in visceral adipocytes. We revealed that the inhibition of NLRP3 in human visceral adipocytes significantly blocked (P < 0.01) LPS-induced inflammation by downregulating the mRNA levels of CCL2, IL1B, IL6, IL8, S100A8, S100A9, TLR4 and TNF as well as inhibiting (P < 0.01) the secretion of IL1-β into the culture medium. Furthermore, blocking NLRP3 attenuated (P < 0.01) the LPS-induced expression of important molecules involved in AT fibrosis (COL1A1, COL4A3, COL6A3 and MMP2). These novel findings provide evidence that blocking the expression of NLRP3 reduces AT inflammation with significant fibrosis attenuation.     

Automated genomic sequence analysis of the three collagen VI genes: applications to Ullrich congenital muscular dystrophy and Bethlem myopathy

Introduction: Mutations in the genes encoding collagen VI (COL6A1, COL6A2, and COL6A3) cause Bethlem myopathy (BM) and Ullrich congenital muscular dystrophy (UCMD). BM is a relatively mild dominantly inherited disorder with proximal weakness and distal joint contractures. UCMD is an autosomal recessive condition causing severe muscle weakness with proximal joint contractures and distal hyperlaxity. Methods: We developed a method for rapid direct sequence analysis of all 107 coding exons of the COL6 genes using single condition amplification/internal primer (SCAIP) sequencing. We have sequenced all three COL6 genes from genomic DNA in 79 patients with UCMD or BM. Results: We found putative mutations in one of the COL6 genes in 62% of patients. This more than doubles the number of identified COL6 mutations. Most of these changes are consistent with straightforward autosomal dominant or recessive inheritance. However, some patients showed changes in more than one of the COL6 genes, and our results suggest that some UCMD patients may have dominantly acting mutations rather than recessive disease. Discussion: Our findings may explain some or all of the cases of UCMD that are unlinked to the COL6 loci under a recessive model. The large number of single nucleotide polymorphisms which we generated in the course of this work may be of importance in determining the major phenotypic variability seen in this group of disorders.     

RNA-seq analysis identified hormone-related genes associated with prognosis of triple negative breast cancer

Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer that currently lacks effective biomarkers and therapeutic targets required to investigate the diagnosis and treatment of TNBC. Here we performed a comprehensive differential analysis of 165 TNBC samples by integrating RNA-seq data of breast tumor tissues and adjacent normal tissues from both our cohort and The Cancer Genome Atlas (TCGA). Pathway enrichment analysis was conducted to evaluate the biological function of TNBC-specific expressed genes. Further multivariate Cox proportional hazard regression was performed to evaluate the effect of these genes on TNBC prognosis. In this report, we identified a total of 148 TNBC-specific expressed genes that were primarily enriched in mammary gland morphogenesis and hormone levels related pathways, suggesting that mammary gland morphogenesis might play a unique role in TNBC patients differing from other breast cancer types. Further survival analysis revealed that nine genes (FSIP1, ADCY5, FSD1, HMSD, CMTM5, AFF3, CYP2A7, ATP1A2, and C11orf86) were significantly associated with the prognosis of TNBC patients, while three of them (ADCY5, CYP2A7, and ATP1A2) were involved in the hormone-related pathways. These findings indicated the vital role of the hormone-related genes in TNBC tumorigenesis and may provide some independent prognostic markers as well as novel therapeutic targets for TNBC.     

Whole-exome sequencing of Finnish patients with vascular cognitive impairment

Cerebral small vessel disease (CSVD) is the most important cause of vascular cognitive impairment (VCI). Most CSVD cases are sporadic but familial monogenic forms of the disorder have also been described. Despite the variants identified, many CSVD cases remain unexplained genetically. We used whole-exome sequencing in an attempt to identify novel gene variants underlying CSVD. A cohort of 35 Finnish patients with suspected CSVD was analyzed. Patients were screened negative for the most common variants affecting function in NOTCH3 in Finland (p.Arg133Cys and p.Arg182Cys). Whole-exome sequencing was performed to search for a genetic cause of CSVD. Our study resulted in the detection of possibly pathogenic variants or variants of unknown significance in genes known to associate with CSVD in six patients, accounting for 17% of cases. Those genes included NOTCH3, HTRA1, COL4A1, and COL4A2. We also identified variants with predicted pathogenic effect in genes associated with other neurological or stroke-related conditions in seven patients, accounting for 20% of cases. This study supports pathogenic roles of variants in COL4A1, COL4A2, and HTRA1 in CSVD and VCI. Our results also suggest that vascular pathogenic mechanisms are linked to neurodegenerative conditions and provide novel insights into the molecular basis of VCI.Subject terms: Stroke, Sequencing, Genetics research, Dementia     

Consensus statement on standards and guidelines for the molecular diagnostics of Alport syndrome: refining the ACMG criteria

The recent Chandos House meeting of the Alport Variant Collaborative extended the indications for screening for pathogenic variants in the COL4A5, COL4A3 and COL4A4 genes beyond the classical Alport phenotype (haematuria, renal failure; family history of haematuria or renal failure) to include persistent proteinuria, steroid-resistant nephrotic syndrome, focal and segmental glomerulosclerosis (FSGS), familial IgA glomerulonephritis and end-stage kidney failure without an obvious cause. The meeting refined the ACMG criteria for variant assessment for the Alport genes (COL4A3–5). It identified ‘mutational hotspots’ (PM1) in the collagen IV α5, α3 and α4 chains including position 1 Glycine residues in the Gly-X-Y repeats in the intermediate collagenous domains; and Cysteine residues in the carboxy non-collagenous domain (PP3). It considered that ‘well-established’ functional assays (PS3, BS3) were still mainly research tools but sequencing and minigene assays were commonly used to confirm splicing variants. It was not possible to define the Minor Allele Frequency (MAF) threshold above which variants were considered Benign (BA1, BS1), because of the different modes of inheritances of Alport syndrome, and the occurrence of hypomorphic variants (often Glycine adjacent to a non-collagenous interruption) and local founder effects. Heterozygous COL4A3 and COL4A4 variants were common ‘incidental’ findings also present in normal reference databases. The recognition and interpretation of hypomorphic variants in the COL4A3–COL4A5 genes remains a challenge.Subject terms: Diseases, Alport syndrome     

Cytokine gene polymorphisms in Iraqi Arabs

In this report, 224 unrelated healthy Iraqi Arabs (102 males and 122 females) were genotyped for 22 SNPs (single nucleotide polymorphisms) belong to 13 cytokine genes (IL1A, IL1B, IL1RA, IL1R, IL2, IL4, IL4R, IL6, IL10, IL12, IFNG, TNFA and TGFB1). The method of detection was PCR-SSP (polymerase chain reaction-sequence specific primer). The data were presented in terms of allele and genotype frequencies. Two-locus haplotype frequencies were also estimated for some SNPs. Genotype frequencies of detected cytokine gene polymorphisms are available in the Database of Allele Frequencies Net under the AFND number 3422 and the population name “Iraq Arab Cytokine”.     

Targeted next-generation sequencing in steroid-resistant nephrotic syndrome: mutations in multiple glomerular genes may influence disease severity

Genetic diagnosis of steroid-resistant nephrotic syndrome (SRNS) using Sanger sequencing is complicated by the high genetic heterogeneity and phenotypic variability of this disease. We aimed to improve the genetic diagnosis of SRNS by simultaneously sequencing 26 glomerular genes using massive parallel sequencing and to study whether mutations in multiple genes increase disease severity. High-throughput mutation analysis was performed in 50 SRNS and/or focal segmental glomerulosclerosis (FSGS) patients, a validation cohort of 25 patients with known pathogenic mutations, and a discovery cohort of 25 uncharacterized patients with probable genetic etiology. In the validation cohort, we identified the 42 previously known pathogenic mutations across NPHS1, NPHS2, WT1, TRPC6, and INF2 genes. In the discovery cohort, disease-causing mutations in SRNS/FSGS genes were found in nine patients. We detected three patients with mutations in an SRNS/FSGS gene and COL4A3. Two of them were familial cases and presented a more severe phenotype than family members with mutation in only one gene. In conclusion, our results show that massive parallel sequencing is feasible and robust for genetic diagnosis of SRNS/FSGS. Our results indicate that patients carrying mutations in an SRNS/FSGS gene and also in COL4A3 gene have increased disease severity.     

Novel defects in collagen XII and VI expand the mixed myopathy/Ehlers–Danlos syndrome spectrum and lead to variant-specific alterations in the extracellular matrix

PurposeTo date, heterozygous or homozygous COL12A1 variants have been reported in 13 patients presenting with a clinical phenotype overlapping with collagen VI–related myopathies and Ehlers–Danlos syndrome (EDS). The small number of reported patients limits thorough investigation of this newly identified syndrome, currently coined as myopathic EDS.MethodsDNA from 78 genetically unresolved patients fulfilling the clinical criteria for myopathic EDS was sequenced using a next-generation panel of COL12A1, COL6A1, COL6A2, and COL6A3.ResultsAmong this cohort, we identified four pathogenic heterozygous in-frame exon skipping (∆) defects in COL12A1, clustering to the thrombospondin N-terminal region and the adjacent collagenous domain (Δ52, Δ53, Δ54, and Δ56 respectively), one heterozygous COL12A1 arginine-to-cysteine substitution of unclear significance (p.(Arg1863Cys)), and compound heterozygous pathogenic COL6A1 variants (c.[98–6G>A];[301C>T]) in one proband. Variant-specific intracellular accumulation of collagen XII chains, extracellular overmodification of the long isoform and near-absence of the short isoform of collagen XII, and extracellular decrease of decorin and tenascin-X were observed for the COL12A1 variants. In contrast, the COL6A1 variants abolished collagen VI and V deposition and increased tenascin-X levels.ConclusionOur data further support the significant clinical overlap between myopathic EDS and collagen VI–related myopathies, and emphasize the variant-specific consequences of collagen XII defects.     

Integrated regulatory mechanisms of miRNAs and targeted genes involved in colorectal cancer

Purpose: CRC (Colorectal cancer) is a lethal cancer for death worldwide and the underlying pathological mechanisms for CRC progression remain unclear. We aimed to explore the regulatory mechanism of CRC and provide novel biomarkers for CRC screening. Methods: Downloading from GEO (Gene Expression Omnibus) database, Microarray data {"type":"entrez-geo","attrs":{"text":"GSE44861","term_id":"44861"}}GSE44861 were consisted of 111 colon tissues samples including 55 from adjacent noncancerous tissues and 56 from tumors tissues. After data pre-processing, up- and down regulated DEGs (differentially expressed genes) were identified using Bayes moderated t-test. Then DIVAD (Database for Annotation, Visualization and Integrated Discovery) was recruited to perform functional analysis for DEGs. Thereafter, PPI (protein-protein interaction) network was constructed by mapping DEGs into STRING (Search Tool for the Retrieval of Interacting Genes) database. Further, PPI modules were constructed and the protein domains of DEGs in the modules were analyzed. Moreover, miRNA regulatory network was established through GSEA (gene set enrichment analysis) method. Results: In summary, 96 up- and 212 down-regulated DEGs were identified. Totally, ten DEGs with high degrees in the constructed PPI network were selected, in which COLL1A1, PTGS2 and ASPN were also identified as crucial genes in PPI modules. Furthermore, COLL1A1 was predicted to be targeted by miR-29, while PTGS2 and ASPN were both predicted to be regulated by miR-101 and miR-26. Conclusion: COL11A1 might involve in the progression of CRC via being targeted by miR-29, whereas PTGS2 and ASPN were both regulated by miR-101 and miR-26. Moreover, ASPN may be supposed as a novel biomarker for CRC detection and prevention.     

Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer

Background: Gastric cancer (GC) has a high mortality rate in cancer-related deaths worldwide. Currently, the pathogenesis of gastric cancer progression remains unclear. Here, we identified several vital candidate genes related to gastric cancer development and revealed the potential pathogenic mechanisms using integrated bioinformatics analysis.Methods: Two microarray datasets from Gene Expression Omnibus (GEO) database integrated. Limma package was used to analyze differentially expressed genes (DEGs) between GC and matched normal specimens. DAVID was utilized to conduct Gene ontology (GO) and KEGG enrichment analysis. The relative expression of OLFM4, IGF2BP3, CLDN1 and MMP1were analyzed based on TCGA database provided by UALCAN. Western blot and quantitative real time PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines, respectively.Results: We downloaded the expression profiles of {"type":"entrez-geo","attrs":{"text":"GSE103236","term_id":"103236"}}GSE103236 and {"type":"entrez-geo","attrs":{"text":"GSE118897","term_id":"118897"}}GSE118897 from the Gene Expression Omnibus (GEO) database. Two integrated microarray datasets were used to obtain differentially expressed genes (DEGs), and bioinformatics methods were used for in-depth analysis. After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analysis, we identified 61 DEGs in common, of which the expression of 34 genes were elevated and 27 genes were decreased. GO analysis displayed that the biological functions of DEGs mainly focused on negative regulation of growth, fatty acid binding, cellular response to zinc ion and calcium-independent cell-cell adhesion. KEGG pathway analysis demonstrated that these DEGs mainly related to the Wnt and tumor signaling pathway. Interestingly, we found 4 genes were most significantly upregulated in the DEGs, which were OLFM4, IGF2BP3, CLDN1 and MMP1. Then, we confirmed the upregulation of these genes in STAD based on sample types. In the final, western blot and qRT-PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines.Conclusion: In our study, using integrated bioinformatics to screen DEGs in gastric cancer could benefit us for understanding the pathogenic mechanism underlying gastric cancer progression. Meanwhile, we also identified four significantly upregulated genes in DEGs from both two datasets, which might be used as the biomarkers for early diagnosis and prevention of gastric cancer.