Identification of genes universally differentially expressed in gastric cancer

Abstract Background Due to the remarkable heterogeneity of gastric cancer (GC), differentially expressed genes (DEGs) identified at the population-level by case-control comparison cannot afford dysregulation frequency of each DEG in GC. Methods Firstly, the individual-level DEGs were identified for 1,090 GC tissues without paired normal tissues by the RankComp method. Secondly, we directly compared the gene expression in a cancer tissue with its paired normal tissue to identify individual-level DEGs for 448 paired cancer-normal gastric tissues. Results We found 25 DEGs dysregulated not only in more than 90% of 1,090 GC tissues, but also in more than 90% of 448 GC tissues with paired normal tissues. The 25 genes were defined as universal DEGs for GC which were further validated in our additionally measured 24 paired cancer-normal gastric tissues. Among the universal DEGs, four up-regulation genes ( BGN , E2F3 , PLAU and SPP1 ) and one down-regulation gene ( UBL3 ) were found to be cancer genes documented in the COSMIC or F-Census database. By analyzing protein-protein interaction network, we found 12 universal up-regulation genes and their 284 direct neighbor genes were significantly enriched with cancer genes and key biological pathways related to cancer, such as MAPK signaling pathway, Cell cycle and Focal adhesion. The 13 universal down-regulation genes and 16 direct neighbor genes were also significantly enriched with cancer genes and gastric acid secretion related pathway. Conclusion These universal DEGs may be of special importance for GC diagnosis and treatment targets, and can help to study the molecular mechanism of GC.

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Identification of Genes Universally Differentially Expressed in Gastric Cancer

BioMed Research International ◽

10.1155/2021/7326853 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Yidan Shi ◽

Lishuang Qi ◽

Haifeng Chen ◽

Jiahui Zhang ◽

Qingzhou Guan ◽

...

Keyword(s):

Gastric Cancer ◽

Mapk Signaling ◽

Differentially Expressed ◽

Cancer Tissue ◽

Special Importance ◽

Cancer Genes ◽

Individual Level ◽

Normal Tissues ◽

Direct Neighbor ◽

Upregulated Genes

Owing to the remarkable heterogeneity of gastric cancer (GC), population-level differentially expressed genes (DEGs) identified using case-control comparison cannot indicate the dysregulated frequency of each DEG in GC. In this work, first, the individual-level DEGs were identified for 1,090 GC tissues without paired normal tissues using the RankComp method. Second, we directly compared the gene expression in a cancer tissue to that in paired normal tissue to identify individual-level DEGs among 448 paired cancer-normal gastric tissues. We found 25 DEGs to be dysregulated in more than 90% of 1,090 GC tissues and also in more than 90% of 448 GC tissues with paired normal tissues. The 25 genes were defined as universal DEGs for GC. Then, we measured 24 paired cancer-normal gastric tissues by RNA-seq to validate them further. Among the universal DEGs, 4 upregulated genes (BGN, E2F3, PLAU, and SPP1) and 1 downregulated gene (UBL3) were found to be cancer genes already documented in the COSMIC or F-Census databases. By analyzing protein-protein interaction networks, we found 12 universally upregulated genes, and we found that their 284 direct neighbor genes were significantly enriched with cancer genes and key biological pathways related to cancer, such as the MAPK signaling pathway, cell cycle, and focal adhesion. The 13 universally downregulated genes and 16 direct neighbor genes were also significantly enriched with cancer genes and pathways related to gastric acid secretion. These universal DEGs may be of special importance to GC diagnosis and treatment targets, and they may make it easier to study the molecular mechanisms underlying GC.

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Identification and Verification of the Main Differentially Expressed Proteins in Gastric Cancer via iTRAQ Combined with Liquid Chromatography-Mass Spectrometry

Analytical Cellular Pathology ◽

10.1155/2019/5310684 ◽

2019 ◽

Vol 2019 ◽

pp. 1-14

Author(s):

Zhihua Gao ◽

Jiabao Wang ◽

Yuru Bai ◽

Jun Bao ◽

Erqing Dai

Keyword(s):

Gastric Cancer ◽

Western Blotting ◽

Normal Mucosa ◽

Gastric Cancer Tissue ◽

Differentially Expressed ◽

Cancer Tissue ◽

Exploratory Research ◽

Differentially Expressed Proteins ◽

Normal Tissues ◽

Itraq Analysis

Background. To find the potential intersections between the differentially expressed proteins and abnormally expressed genes in gastric cancer (GC) patients. Methods. Gastric cancer tissue and adjacent normal mucosa tissue were used for iTRAQ analysis. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction (PPI) analysis were used to evaluate gene function. Western blotting and immunohistochemistry (IHC) were applied to verify the protein expression. Results. A total of 2770 proteins were identified, of which 147 proteins were upregulated and 159 proteins were downregulated. GO analysis revealed that the differentially expressed genes were mainly enriched for the terms “cellular process,” “binding,” and “cell.” The results of the KEGG analysis showed that the most abundantly enriched proteins were involved in the “focal adhesion” pathway. The results of the PPI analysis showed that VCAM1 was located at the center of the PPI network. Western blotting and IHC analysis demonstrated that VCAM1, FLNA, VASP, CAV1, PICK1, and COL4A2 were differentially expressed in GC and adjacent normal tissues, which was consistent with the results of the iTRAQ analysis. Conclusion. In conclusion, 6 highly differentially expressed proteins were identified as novel differentially expressed proteins in human GC. This exploratory research may provide useful information for the treatment of gastric cancer in the clinic.

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Tissue-Specific Down-Regulation of the Long Non-Coding RNAs PCAT18 and LINC01133 in Gastric Cancer Development

International Journal of Molecular Sciences ◽

10.3390/ijms19123881 ◽

2018 ◽

Vol 19 (12) ◽

pp. 3881 ◽

Cited By ~ 6

Author(s):

Kobra Foroughi ◽

Mohammad Amini ◽

Amir Atashi ◽

Habibollah Mahmoodzadeh ◽

Ute Hamann ◽

...

Keyword(s):

Gastric Cancer ◽

Network Analysis ◽

Gastrointestinal Disease ◽

Gastric Carcinogenesis ◽

Gene Expression Omnibus ◽

Cancer Development ◽

Down Regulation ◽

Tissue Specific ◽

Normal Tissues ◽

Non Coding Rnas

Gastric cancer (GC) is the fifth most common cancer and the third most frequent cause of cancer deaths worldwide. The high death rate associated with GC, and lack of appropriate biomarkers for diagnosis, prognosis, and treatment emphasize the need for identification of novel molecules. Given the emerging roles for long non-coding RNAs (lncRNAs) in cancer development, we studied novel lncRNA candidates involved in gastric carcinogenesis. LncRNA candidate discovery was performed using analyses of available datasets and literature. Validation was done using an internal sample set of GC/normal tissues, and external independent datasets. Network analysis and functional annotation of co-expressed protein coding genes were performed using the weighted gene correlation network analysis (WGCNA) and ingenuity pathway analysis. Two novel lncRNAs, PCAT18 and LINC01133, associated with GC development were identified by analysis of the discovery Gene Expression Omnibus (GEO) datasets. The down-regulation of these genes in GC tissues was successfully validated internally and externally. The results showed a tissue-specific down-regulation of PCAT18 and LINC01133 in gastrointestinal tissues. WGCNA and ingenuity pathway analyses revealed that the genes co-expressed with the two lncRNAs were mostly involved in metabolic pathways and networks of gastrointestinal disease and function. Our findings of a tissue-specific down-regulation of PCAT18 and LINC01133 in gastric and other gastrointestinal cancers imply that these lncRNAs may have a tumor suppressive function in the development of these tumor entities. The two lncRNA biomarkers may contribute to a better understanding of the complex mechanisms of gastric carcinogenesis.

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Progressive and Prognostic Performance of an Extracellular Matrix-Receptor Interaction Signature in Gastric Cancer

Disease Markers ◽

10.1155/2020/8816070 ◽

2020 ◽

Vol 2020 ◽

pp. 1-23

Author(s):

Xiangchou Yang ◽

Liping Chen ◽

Yuting Mao ◽

Zijing Hu ◽

Muqing He

Keyword(s):

Gastric Cancer ◽

Extracellular Matrix ◽

Risk Score ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Receptor Interaction ◽

Clinicopathologic Features ◽

Normal Tissues ◽

Prognostic Application ◽

Score Model

The role of an extracellular matrix- (ECM-) receptor interaction signature has not been fully clarified in gastric cancer. This study performed comprehensive analyses on the differentially expressed ECM-related genes, clinicopathologic features, and prognostic application in gastric cancer. The differentially expressed genes between tumorous and matched normal tissues in The Cancer Genome Atlas (TCGA) and validation cohorts were identified by a paired t -test. Consensus clusters were built to find the correlation between clinicopathologic features and subclusters. Then, the least absolute shrinkage and selection operator (lasso) method was used to construct a risk score model. Correlation analyses were made to reveal the relation between risk score-stratified subgroups and clinicopathologic features or significant signatures. In TCGA (26 pairs) and validation cohort (134 pairs), 25 ECM-related genes were significantly highly expressed and 11 genes were downexpressed in gastric cancer. ECM-based subclusters were slightly related to clinicopathologic features. We constructed a risk score model = 0.081 ∗ log 2 CD 36 + 0.043 ∗ log 2 COL 5 A 2 + 0.001 ∗ log 2 ITGB 5 + 0.039 ∗ log 2 SDC 2 + 0.135 ∗ log 2 SV 2 B + 0.012 ∗ log 2 THBS 1 + 0.068 ∗ log 2 VTN + 0.023 ∗ log 2 VWF . The risk score model could well predict the outcome of patients with gastric cancer in both training ( n = 351 , HR: 1.807, 95% CI: 1.292-2.528, P = 0.00046 ) and validation ( n = 300 , HR: 1.866, 95% CI: 1.347-2.584, P = 0.00014 ) cohorts. Besides, risk score-based subgroups were associated with angiogenesis, cell adhesion molecules, complement and coagulation cascades, TGF-beta signaling, and mismatch repair-relevant signatures ( P < 0.0001 ). By univariate (1.845, 95% CI: 1.382-2.462, P < 0.001 ) and multivariate (1.756, 95% CI: 1.284-2.402, P < 0.001 ) analyses, we regarded the risk score as an independent risk factor in gastric cancer. Our findings revealed that ECM compositions became accomplices in the tumorigenesis, progression, and poor survival of gastric cancer.

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MicroRNA-99a promotes cell proliferation, migration and invasion in gastric cancer by modulating c-Src

10.21203/rs.2.16998/v1 ◽

2019 ◽

Author(s):

Yue Pan ◽

Weixing Chen ◽

Xin Yuan ◽

Hongpeng Lu ◽

Lei Xu ◽

...

Keyword(s):

Gastric Cancer ◽

Cell Cycle ◽

Cell Proliferation ◽

Cancer Cells ◽

Migration And Invasion ◽

Epithelial Cell Line ◽

Cancer Tissue ◽

Gastric Cancer Cells ◽

Normal Tissues ◽

Qrt Pcr

Abstract Background: Recent studies have shown that microRNA-99a(miR-99a)plays a key role in the development of virious malignancies; however, its relationship with gastric cancer remains unclear. In this study, we investigated the functions and potential mechanisms of miR-99a in gastric cancer. Methods: Real-time qRT-PCR was used to assess the expression levels of miR-99a in gastric cancer tissue samples and cell lines compared to their matched adjacent normal tissues and a normal gastric mucosa epithelial cell line, respectively. SGC-7901 cells were transfected with miR-99a mimics and negative controls to determine the effects of miR-99a overexpression on cell proliferation, cell cycle transition, migration and invasion of gastric cancer cells in vitro . The role of miR-99a in endogenous c-Src expression in gastric cancer cells was also investigated by qRT-PCR and Western blotting. Results: Our results showed a significant increase in miR-99a expression in both gastric cancer tissues and cells compared to normal tissues and cells. Overexpression of miR-99a significantly promoted the cell proliferation, migration and invasion of gastric cancer cells compared to normal cells, with a concurrent increase in the S+G2 phases of the cell cycle. Further investigations found that miR-99a overexpression led to significant upregulation of endogenous c-Src. Conclusion: Taken together, our findings suggest that miR-99a may act as a tumour promoter in the pathogenesis of gastric cancer by indirectly modulating c-Src expression.

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Comparison of iodine contents in gastric cancer and surrounding normal tissues

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm.2005.101 ◽

2005 ◽

Vol 43 (6) ◽

Cited By ~ 7

Author(s):

Mine Gulaboglu ◽

Leyla Yildiz ◽

Fehmi Celebi ◽

Mustafa Gul ◽

Kemal Peker

Keyword(s):

Gastric Cancer ◽

Iodine Deficiency ◽

Normal Tissue ◽

Gastric Cancer Tissue ◽

Cancer Tissue ◽

Cancer Prevalence ◽

Normal Tissues ◽

The North ◽

Significant Difference ◽

North Eastern

AbstractIt has been suggested that iodine plays an important role in gastric cancer. Gastric cancer ranks first among the cancers in the north-eastern Anatolia region, Turkey, where iodine deficiency is common. In this study, iodine levels were determined in gastric cancer and surrounding normal tissues in 19 patients with gastric cancer. Tissue iodine levels were determined by the Foss method based on the Sandell-Kolt-hoff reaction. Tissue iodine levels were lower in gastric cancer tissue (17.8±3.4ngI/mg protein, mean±SEM) compared with surrounding normal tissue (41.7±8.0ngI/mg protein) (p<0.001). There was positive correlation between the iodine levels in gastric cancer tissue and surrounding normal tissue (r=0.845, p<0.001). There was no significant difference in iodine levels in cancer and surrounding normal tissue between male and female subjects. The iodine deficiency in our region may be one of the factors for increased gastric cancer prevalence. Our results support the hypothesis that iodine plays an important role in gastric cancer development.

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Combining multi-dimensional data to identify key genes and pathways in gastric cancer

PeerJ ◽

10.7717/peerj.3385 ◽

2017 ◽

Vol 5 ◽

pp. e3385 ◽

Cited By ~ 3

Author(s):

Wu Ren ◽

Wei Li ◽

Daguang Wang ◽

Shuofeng Hu ◽

Jian Suo ◽

...

Keyword(s):

Gastric Cancer ◽

Candidate Genes ◽

Copy Number ◽

Interaction Networks ◽

Differentially Expressed ◽

Cancer Data ◽

Normal Tissues ◽

P53 Signaling ◽

Key Genes ◽

Pathway Analyses

Gastric cancer is an aggressive cancer that is often diagnosed late. Early detection and treatment require a better understanding of the molecular pathology of the disease. The present study combined data on gene expression and regulatory levels (microRNA, methylation, copy number) with the aim of identifying key genes and pathways for gastric cancer. Data used in this study was retrieved from The Cancer Genomic Atlas. Differential analyses between gastric cancer and normal tissues were carried out using Limma. Copy number alterations were identified for tumor samples. Bimodal filtering of differentially expressed genes (DEGs) based on regulatory changes was performed to identify candidate genes. Protein–protein interaction networks for candidate genes were generated by Cytoscape software. Gene ontology and pathway analyses were performed, and disease-associated network was constructed using the Agilent literature search plugin on Cytoscape. In total, we identified 3602 DEGs, 251 differentially expressed microRNAs, 604 differential methylation-sites, and 52 copy number altered regions. Three groups of candidate genes controlled by different regulatory mechanisms were screened out. Interaction networks for candidate genes were constructed consisting of 415, 228, and 233 genes, respectively, all of which were enriched in cell cycle, P53 signaling, DNA replication, viral carcinogenesis, HTLV-1 infection, and progesterone mediated oocyte maturation pathways. Nine hub genes (SRC, KAT2B, NR3C1, CDK6, MCM2, PRKDC, BLM, CCNE1, PARK2) were identified that were presumed to be key regulators of the networks; seven of these were shown to be implicated in gastric cancer through disease-associated network construction. The genes and pathways identified in our study may play pivotal roles in gastric carcinogenesis and have clinical significance.

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Dissecting the Single-Cell Transcriptome Network in Superficial/Deep Tumor Tissues of Diffuse Gastric Cancer

10.21203/rs.3.rs-1130074/v1 ◽

2021 ◽

Author(s):

Yili Ren ◽

Beibei Zhang ◽

Chenkai Xu ◽

Lei Zhang

Keyword(s):

Gastric Cancer ◽

Survival Analysis ◽

Single Cell ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Differentially Expressed ◽

Cell Subpopulation ◽

Diffuse Gastric Cancer ◽

Normal Tissues ◽

Tumor Tissues

Abstract Background and purpose: Gastric cancer is a type of highly heterogeneous malignant tumor and the prognosis of gastric cancer is hard to be improved due to limited knowledge on the molecular mechanism of heterogeneity. Single-cell sequencing technology is recently widely used for the investigation of both inter-tumoral heterogeneity and intra-tumoral heterogeneity. The present study aims to explore the potential oncogene by analyzing the single-cell data in the GSE167297 dataset.Methods: The GSE167297 dataset was downloaded from the GEO database, followed by quality control to remove data with lower quality. The division on cell subtypes was determined by the characteristic marker expressed in each cell subpopulation. Wilcoxon rank-sum test was used to screen out differentially expressed genes. Survival analysis was performed to evaluate the prognostic value of G-protein subunit g 11 (GNG11) gene which was significantly overexpressed in deep tumor tissues of diffuse gastric cancer.Results: In both normal tissues and tumor tissues, subtypes of immune cells and stromal cells were identified, with a higher proportion of infiltrated macrophages observed in deep tumor tissues. EPCAM was found significantly highly expressed in a cell subpopulation from gastric tumor tissues. 515 differentially expressed genes (| log2FC | > 2 and FDR < 1e-5) were screened out between normal tissues and tumor tissues. 86 differentially expressed genes (| log2FC | > 1 and FDR < 0.01) were screened out between superficial and deep tumor tissues, in which GNG11 was most highly expressed in deep tumor tissues (mean expression value: 0.1247, FC value: 52.2109). Disease-specific survival analysis on GNG11 results showed that the HR [95%CI] in the constructed univariate Cox proportional risk model was 4.419 [1.399-13.96] and the P-value in the log-rank test was 0.0056.Conclusion: Differentially expression profiles were provided both extratumorally and intratumorally, indicating a higher infiltration of macrophages in deep tumor tissues. Additionally,GNG11 was screened out to be a significant risk factor in STAD patients.

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Identification of Potential Biomarkers and Therapy Targets involved in Gastric Cancer Using Bioinformatics Analysis

10.21203/rs.3.rs-837643/v1 ◽

2021 ◽

Author(s):

YangYang Teng ◽

Na Shan ◽

GuangRong Lu ◽

LeYi Ni ◽

ZeJun Gao ◽

...

Keyword(s):

Gastric Cancer ◽

Bioinformatics Analysis ◽

Risk Model ◽

Malignant Tumors ◽

Differentially Expressed ◽

Hub Genes ◽

Normal Tissues ◽

Therapy Targets ◽

Selection Operator ◽

Cancer Tissues

Abstract Gastric cancer remains one of the five major malignant tumors in the world, posing a great threat to public life and health. As gene sequencing technology develops, it is urgent to find out specific molecular markers for cancer therapy. In this study, datasets of GSE13911, GSE30727, GSE63089 and GSE118916 were investigated by bioinformatics analysis, and differentially expressed genes (DEGs) between GC tissues and normal tissues were screened for potential cancer therapeutic targets. Furthermore, the GSE63089 dataset was analyzed by Weighted Gene Co-expression Network Analysis (WGCNA), and the highly related genes were clustered. Then, the hub genes were searched using co-expression network and Molecular Complex Detection (MCODE) plug-in from Cytoscape software. Finally, ASPM, COL11A1 and CDC20 were obtained by intersection of hub genes and DEGs. The expressions of ASPM, COL11A1 and CDC20 gene in gastric cancer tissues and normal tissues from TCGA database were detected. For these genes, the least absolute shrink and selection operator (LASSO) Cox expression analysis was used to establish the prognostic risk model. COL11A1 and CDC20 genes were identified as candidate prognostic risk markers for GC. Analysis using qRT-PCR has shown that COL11A1 and CDC20 were significant differentially expressed between gastric cancer tissues and normal gastric tissues (P < 0.01). In conclusion, our study identifies specific DEGs involved in ECM process and metabolism by cytochrome P450 process, and these DEGs may be potential targets for GC therapy. The model constructed by COL11A1 and CDC20 genes can predict the prognosis risk of GC patients. Taken together, these findings provide reference for further analyses of key alterations during GC progression.

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The Construction and Analysis of ceRNA Network in H pylori infection atrophic gastritis

10.21203/rs.3.rs-1047498/v1 ◽

2021 ◽

Author(s):

Wen-jun BAI ◽

Jun-wei LIANG ◽

Xiao-yan WANG

Keyword(s):

Gastric Cancer ◽

Atrophic Gastritis ◽

Signaling Pathway ◽

Regulatory Network ◽

Interaction Analysis ◽

Mapk Signaling ◽

Functional Enrichment ◽

Differentially Expressed ◽

Signal Pathways ◽

H Pylori

Abstract Background：Chronic atrophic gastritis (CAG) is an established pre-cancerous lesion of intestinal type gastric cancer(GC),H pylori infection is the main pathogenic cause,this study intends to study the pathogenesis of atrophic gastritis(Hp+) from the lncRNA-miRNA-mRNA ceRNA regulatory network, in order to provide the oretical basis and data support for the treatment of atrophic gastritis.Results:GSE111762 downloaded from GEO database was used to analyze the differentially expressed lncRNAs and mRNAs(DEGs).A total of 395 differentially expressed lncRNA (225 upregulated,170 downregulated) and 1093 DEGs ( 674 upregulated, 419 downregulated) are obtained. Through the cross-mapping of miRcode, starBase, Sponescan,miRTarBase and miRBase databases,16 miRNAs were predicted,and the lncRNA-miRNA-mRNA ceRNA regulatory network consisting of 71 IncRNAs,16 miRNAs and 597 mRNAs was constructed.597 DEGs were analyzed by David database for functional enrichment. A total of 250 GO enrichment items were obtained, including 160 BP entries, 48 CC entries and 42 MF entries,29 signal pathways were obtained by enrichment analysis of KEGG pathways, mainly p53 signaling pathway, PI3K-Akt signaling pathway and MAPK signaling pathway. Using Cytoscape plug-in CytoHubba to filter 597 DEGs with "MCC, MNC, Degree" top20 as screening conditions, Eleven key hub targets are obtained from the intersection of jvenn.Protein interaction analysis of key hub targets through Cytoscape plug-in GeneMania, it was found that 87.65% displayed similar co-expression characteristics.Construct ceRNA regulatory network of the key hub targets,11 mRNAs(such as BRCA1, RAD54L),12 miRNAs(such as hsa-miR-340-5p,hsa-miR-182-5p) and 58 lncRNAs(such as PCGEM1,FTX) were predicted. Conclusions:Clarify the complex reticular regulation of atrophicgastritis with multi-targets, multi-pathways and multi-pathways.Which provides a new idea for the study of the mechanism of action of atrophicgastritis (Hp+) and a potential target for its treatment,thus to further early diagnosis and reversal of gastric cancer.

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