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

Background This 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.

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Bioinformatics Analysis Reveals Biomarkers With Prognostic Benefits in Diffuse Type Gastric Cancer

10.21203/rs.3.rs-36710/v1 ◽

2020 ◽

Author(s):

Sheng Li ◽

Chao Yu ◽

Yuanguang Cheng ◽

Fangchao Du ◽

Gang Wen

Keyword(s):

Gastric Cancer ◽

Pcr Analysis ◽

Diffuse Type ◽

Hub Genes ◽

Screening Criteria ◽

Clinical Prognosis ◽

Qrt Pcr ◽

Ppi Networks ◽

Immunohistochemistry Analysis ◽

Kaplan Meier

Abstract BackgroundGastric cancer (GC) is one of the most common malignancies in digestive system, among which the differentiation of diffuse type GC is relatively poor, the probability of distant metastasis and lymph node metastasis is relatively high, and the clinical prognosis is relatively poor. The purpose of this study is to explore potential signaling pathways and key biomarkers that drive the development of diffuse type GC. Methods Using the “limma” package in R to screen Differentially expressed genes. Screening hub genes by PPI analysis. Immunohistochemistry analysis and qRT-PCR analysis was carried out to detect genes expression. Using Kaplan-Meier Plotter database analyzed the prognostic roles of hub genes.ResultsA total of 355 DEGs consisting of 293 diffuse type DEGs and 62 intestinal type DEGs were selected according to screening criteria, 3 hub genes were chosen from diffuse type DEGs according to the degree of connectivity by using protein-protein interaction (PPI) networks and Cytoscape software including AGT, CXCL12 and ADRB2. Immunohistochemistry analysis and qRT-PCR results showed that the expression of three genes was related to the different GC lauren types. The Kaplan Meier analysis showed that the expression values of these three genes were related to prognosis of diffuse type GC. ConclusionsAGT, CXCL12 and ADRB2 might contribute to the progression of diffuse type GC, which could have potential as biomarkers or therapeutic targets for diffuse type GC.

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Bioinformatics Analysis to Identify Key Genes and Pathways Associated with Sex Differences in Rheumatoid Arthritis

10.21203/rs.3.rs-687988/v1 ◽

2021 ◽

Author(s):

Siwei Su ◽

Wenjun Jiang ◽

Xiaoying Wang ◽

Sen Du ◽

Lu Zhou ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Hub Genes ◽

Protein Protein Interaction ◽

Kegg Pathways ◽

Ppi Networks ◽

Males And Females ◽

Key Genes

Abstract ObjectiveThis study aims to explore the key genes and investigated the different signaling pathways of rheumatoid arthritis (RA) between males and females.Data and MethodsThe gene expression data of GSE55457, GSE55584, and GSE12021 were obtained from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using R software. Then, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were conducted via Database for Annotation, Visualization, and Integrated Discovery (DAVID). The protein-protein interaction (PPI) networks of DEGs were constructed by Cytoscape 3.6.0. ResultsA total of 416 upregulated DEGs and 336 downregulated DEGs were identified in males, and 744 upregulated DEGs and 309 downregulated DEGs were identified in females.IL6, MYC, EGFR, FOS and JUN were considered as hub genes in RA pathogenesis in males, while IL6, ALB, PTPRC, CXCL8 and CCR5 were considered as hub genes in RA pathogenesis in females. ConclusionIdentified DEG may be involved in the different mechanisms of RA disease progression between males and females, and they are treated as prognostic markers or therapeutic targets for males and females. The pathogenesis mechanism of RA is sex-dependent.

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Human Gastric Cancer Stem Cell (GCSC) Markers Are Prognostic Factors Correlated With Immune Infiltration of Gastric Cancer

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.626966 ◽

2021 ◽

Vol 8 ◽

Author(s):

Tong Lin ◽

Wenya Peng ◽

Peipei Mai ◽

E. Zhang ◽

Lisheng Peng

Keyword(s):

Gastric Cancer ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Clinicopathological Parameters ◽

Human Gastric Cancer ◽

Nf Kappa B ◽

Immune Infiltration ◽

Kaplan Meier ◽

Cancer Aggressiveness ◽

Human Protein Atlas

The prognosis of patients with gastric cancer (GC) is still unsatisfying. Numerous markers of gastric cancer stem cells (GCSCs) have been identified and were thought to be related to cancer aggressiveness. However, the roles of GCSC markers in GC patients’ prognosis and immune infiltration remain unknown. Expression of GCSC markers was analyzed using Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA). Their associations with clinicopathological parameters were analyzed using UALCAN and LinkedOmics. Alternations and protein expression of GCSC markers were analyzed by cBioPortal and the Human Protein Atlas databases, respectively. The prognostic significance of GCSC markers was evaluated using Kaplan-Meier plotter. Correlations between the expression of GCSC markers and immune infiltration along with biomarkers of tumor-infiltrating immune cells (TIICs) were assessed combined Tumor Immune Estimation Resource and GEPIA. GeneMANIA was used to discover the interactive genes of GCSC markers, and enrichment analysis was performed using Database for Annotation, Visualization, and Integrated Discovery server. We identified six GCSC markers significantly up-expressed in GC, compared with normal stomach tissues. Among them, the overexpression of ICAM1, THY1, and CXCR4 significantly indicated adverse, while EPCAM indicated beneficial clinicopathological features of GC patients. The up-regulation of CXCR4 showed unfavorable prognostic significance, whereas EPCAM and TFRC showed the opposite. The six GCSC markers were all correlated with the infiltration and activation of distinct TIICs. Especially, ICAM1, THY1, and CXCR4 showed strongly positive correlations with tumor-associated macrophages. Besides, chemokine, Toll-like receptor, NF-kappa B, and HIF-1 signaling pathways might be involved in the regulation of GCSC markers on cancer development. This study proposed that GCSC markers might be promising targets of GC treatment to weaken cancer stem-like properties and strengthen anticancer immunity.

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Amplification and expression of c-MET correlate with poor prognosis of patients with gastric cancer and upregulate the expression of PDL1

Acta Biochimica et Biophysica Sinica ◽

10.1093/abbs/gmab026 ◽

2021 ◽

Vol 53 (5) ◽

pp. 547-557

Author(s):

Ya’nan Yang ◽

Chenchen Wang ◽

Congqi Dai ◽

Xinyang Liu ◽

Wenhua Li ◽

...

Keyword(s):

Gastric Cancer ◽

Prognostic Significance ◽

Growth Factor Receptor ◽

Disease Free Survival ◽

Positive Association ◽

Her2 Positive ◽

Kaplan Meier ◽

Met Amplification ◽

Amplification Rate ◽

Cox Proportional Hazard Regression

Abstract The prognostic significance of c-MET in gastric cancer (GC) remains uncertain. In the present study, we examined the amplification, expression, and the prognostic value of c-MET, human epidermal growth factor receptor 2 (HER2), and programmed cell death 1 ligand 1 (PDL1), together with the correlations among them in a large cohort of Chinese samples. A total of 444 patients were included. The immunohistochemistry (IHC) and the dual-color silver in situ hybridization (SISH) were performed to examine their expression and amplification. Univariate and multivariate analyses were performed by the Cox proportional hazard regression model, and survival curves were estimated by the Kaplan–Meier method. The positivity determined by IHC of c-MET was 24.8%, and the MET amplification rate was 2.3%. The positivity rates of HER2 and PDL1 were 8% and 34.7%, respectively. PDL1 expression had a significantly positive association with c-MET expression. c-MET positivity played a significant prognostic role in disease-free survival (DFS) (P = 0.032). Patients with mesenchymal-epithelial transition (MET) amplification had significantly poorer prognosis on both DFS and overall survival (OS). Subgroup analysis showed that in HER2-negative patients, but not in HER2-positive patients, MET-positive patients had significantly worse DFS (P = 0.000) and OS (P = 0.006). c-MET regulated the expression of PDL1 through an AKT-dependent pathway. c-MET inhibitor enhanced the T-cell killing ability and increased the efficacy of PD1 antibody. c-MET was found to be an independent prognostic factor for DFS of GC patients. A combination of c-MET inhibitors and PD1 antibodies could enhance the killing capacity of T cells, providing a preliminary basis for the clinical research on the same combination in GC treatment.

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Differential Expression of mRNAs in Peripheral Blood Related to Prodrome and Progression of Alzheimer’s Disease

BioMed Research International ◽

10.1155/2020/4505720 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Weishuang Xue ◽

Jinwei Li ◽

Kailei Fu ◽

Weiyu Teng

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Peripheral Blood ◽

Bioinformatics Analysis ◽

Gene Expression Omnibus ◽

Venn Diagram ◽

Ppi Network ◽

Hub Genes ◽

Protein Protein Interaction ◽

Ppi Networks

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.

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High expression of DNA damage-inducible transcript 4 (DDIT4) is associated with advanced pathological features in the patients with colorectal cancer

Scientific Reports ◽

10.1038/s41598-021-92720-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Fahimeh Fattahi ◽

Leili Saeednejad Zanjani ◽

Zohreh Habibi Shams ◽

Jafar Kiani ◽

Mitra Mehrazma ◽

...

Keyword(s):

Colorectal Cancer ◽

Dna Damage ◽

Prognostic Significance ◽

Tissue Microarrays ◽

Survival Outcomes ◽

Hub Genes ◽

Kegg Pathways ◽

Normal Tissues ◽

Nuclear Expression ◽

Pathways Analysis

AbstractDNA damage-inducible transcript 4 (DDIT4) is induced in various cellular stress conditions. This study was conducted to investigate expression and prognostic significance of DDIT4 protein as a biomarker in the patients with colorectal cancer (CRC). PPI network and KEGG pathway analysis were applied to identify hub genes among obtained differentially expressed genes in CRC tissues from three GEO Series. In clinical, expression of DDIT4 as one of hub genes in three subcellular locations was evaluated in 198 CRC tissues using immunohistochemistry method on tissue microarrays. The association between DDIT4 expression and clinicopathological features as well as survival outcomes were analyzed. Results of bioinformatics analysis indicated 14 hub genes enriched in significant pathways according to KEGG pathways analysis among which DDIT4 was selected to evaluate CRC tissues. Overexpression of nuclear DDIT4 protein was found in CRC tissues compared to adjacent normal tissues (P = 0.003). Furthermore, higher nuclear expression of DDIT4 was found to be significantly associated with the reduced tumor differentiation and advanced TNM stages (all, P = 0.009). No significant association was observed between survival outcomes and nuclear expression of DDIT4 in CRC cases. Our findings indicated higher nuclear expression of DDIT4 was significantly associated with more aggressive tumor behavior and more advanced stage of disease in the patients with CRC.

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Title: Weighted Gene Co-Expression Network Analysis Identifies Five Hub Genes Associated with Metastasis in Synovial Sarcoma

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207324666210628112429 ◽

2021 ◽

Vol 24 ◽

Author(s):

Hongzeng Wu ◽

Benzheng Zhang ◽

Jiazheng Zhao ◽

Yi Zhao ◽

Xiaowei Ma ◽

...

Keyword(s):

Synovial Sarcoma ◽

Tumor Metastasis ◽

Gene Expression Omnibus ◽

Survival Ratio ◽

Hub Genes ◽

Protein Protein Interaction ◽

Metastatic Lesions ◽

Ppi Networks ◽

Malignant Soft Tissue ◽

Geo Database

Background: Synovial sarcoma (SS) refers to a malignant soft tissue sarcoma (STS) which often occurs in children and adults and has a poor prognosis in elderly patients. Patients with local lesions can be treated with extensive surgical resection combined with adjuvant or radiotherapy, whereas about half of the cases have recurrent diseases and metastatic lesions, and five-year survival ratio is assessed within the range of 27% - 55% only. Method: We downloaded a set of expression profile data (GSE40021) related to SS metastasis based on the Gene Expression Omnibus (GEO) database, and selected distinctly represented genes (DEGs) related to tumor metastasis. WGCNA was used to emphasize the DEGs related to tumor metastasis and obtain co-expression modules. Then, the module most related to SS metastasis was screened out. The genes enriched in this module were analyzed by Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway improvement analysis. Cytoscape software was used for constructing protein-protein interaction (PPI) networks, and hub genes were screened in Oncomine analysis. Result: We selected 514 DEGs, consisting of 210 up-regulated genes and 304 down-regulated genes. Through WGCAN, we got seven co-expression modules and the module most related to SS metastasis was the turquoise module, which contained 66 genes. Finally, we screened out five hub genes (HJURP, NCAPG, TPX2, CENPA, NDC80) through CytoHubba and Oncomine analysis. Conclusion: In this study, we screened five hub genes that may help in clinical diagnosis and serve as the latent purpose of SS treatment.

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Expression and Clinical Significance of Serum Exosomal miR-375 in Patients with Gastric Cancer

Tobacco Regulatory Science ◽

10.18001/trs.7.5.1.162 ◽

2021 ◽

Vol 7 (5) ◽

pp. 3896-3904

Author(s):

Daoting Deng ◽

Hong Zhang ◽

Junxi Liu ◽

Lina Ma ◽

Xinrui Lei ◽

...

Keyword(s):

Gastric Cancer ◽

Cancer Patients ◽

Cox Regression ◽

Prognostic Significance ◽

Cox Regression Analysis ◽

Healthy Group ◽

Cancer Group ◽

Kaplan Meier ◽

Gastric Cancer Patients ◽

Gastric Cancer Group

To explore exosomal miR-375 expression in gastric cancer patients and its relationship with patient prognosis. A total of 53 patients diagnosed with gastric cancer in our hospital from May 2014 to May 2016 were included as the gastric cancer group, and 46 healthy women who came to our hospital for physical examination during the same period were enrolled as the healthy group. Exosomal miR-375 expression level was detected using qRT-PCR, and the diagnostic performance and prognostic significance of exosomal miR-375 in gastric cancer were explored. The gastric cancer group showed increased exosomal miR-375 expression than the healthy group (P< 0.05); Kaplan-Meier survival analysis exhibited that serum exosomal miR-375 has an AUC of 0.778, sensitivity of 69.57%, and specificity of 75.47%, whereas Cox regression analysis showed that the miR-375 expression in exosomes was an independent risk factor affecting the prognosis of gastric cancer patients (P< 0.05). Patient with gastric cancer showed upregulated miR-375 expression in serum exosomes. Serum exosomal miR-375 was found to has positive sensitivity and specificity in the diagnosis of gastric cancer, which may be associated with poor prognosis of gastric cancer patients.

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HER-2 Expression in Immunohistochemistry Has No Prognostic Significance in Gastric Cancer Patients

The Scientific World JOURNAL ◽

10.1100/2012/941259 ◽

2012 ◽

Vol 2012 ◽

pp. 1-6 ◽

Cited By ~ 23

Author(s):

Agnieszka Halon ◽

Piotr Donizy ◽

Przemyslaw Biecek ◽

Julia Rudno-Rudzinska ◽

Wojciech Kielan ◽

...

Keyword(s):

Gastric Cancer ◽

Test Score ◽

Prognostic Significance ◽

Clinicopathological Parameters ◽

Prognostic Impact ◽

Curative Surgery ◽

Regional Lymph Nodes ◽

Poorly Differentiated ◽

Her 2 ◽

Gastric Cancer Patients

The role of HER-2 expression as a prognostic factor in gastric cancer (GC) is still controversial. The aim of the study was to asses HER-2 status, its correlations with clinicopathological parameters, and prognostic impact in GC patients. Tumor samples were collected from 78 patients who had undergone curative surgery. In order to evaluate the intensity of immunohistochemical (IHC) reactions two scales were applied: the immunoreactive score according to Remmele modified by the authors and standardised Hercep test score modified for GC by Hofmann et al. The HER-2 overexpression was detected by IHC in 23 (29.5%) tumors in Hercep test (score 2+/3+) and in 24 (30.7%) in IRS scale (IRS 4–12). The overexpression of HER-2 was associated with poorly differentiated tumors, but this correlation was not significant (P=0.064). No relationship was found between HER-2 expression and primary tumor size and degree of spread to regional lymph nodes. Both univariate and multivariate analyses revealed that TNM stage and patient’s age were the crucial negative prognostic factors. No correlation was observed between patient survival and expression of HER-2 estimated using both scales. This research did not confirm HER-2 expression (evaluated with immunohistochemistry) value as a prognostic tool in GC.

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Identification and Classification of Hubs in microRNA Target Gene Networks in Human Neural Stem/Progenitor Cells following Japanese Encephalitis Virus Infection

mSphere ◽

10.1128/msphere.00588-19 ◽

2019 ◽

Vol 4 (5) ◽

Author(s):

Sriparna Mukherjee ◽

Irshad Akbar ◽

Reshma Bhagat ◽

Bibhabasu Hazra ◽

Arindam Bhattacharyya ◽

...

Keyword(s):

Progenitor Cells ◽

Gene Networks ◽

Mirna Target ◽

Target Gene ◽

Target Genes ◽

Hub Genes ◽

Protein Protein Interaction ◽

Ppi Networks ◽

Neural Stem Progenitor Cells

ABSTRACT RNA viruses are known to modulate host microRNA (miRNA) machinery for their own benefit. Japanese encephalitis virus (JEV), a neurotropic RNA virus, has been reported to manipulate several miRNAs in neurons or microglia. However, no report indicates a complete sketch of the miRNA profile of neural stem/progenitor cells (NSPCs), hence the focus of our current study. We used an miRNA array of 84 miRNAs in uninfected and JEV-infected human neuronal progenitor cells and primary neural precursor cells isolated from aborted fetuses. Severalfold downregulation of hsa-miR-9-5p, hsa-miR-22-3p, hsa-miR-124-3p, and hsa-miR-132-3p was found postinfection in both of the cell types compared to the uninfected cells. Subsequently, we screened for the target genes of these miRNAs and looked for the biological pathways that were significantly regulated by the genes. The target genes involved in two or more pathways were sorted out. Protein-protein interaction (PPI) networks of the miRNA target genes were formed based on their interaction patterns. A binary adjacency matrix for each gene network was prepared. Different modules or communities were identified in those networks by community detection algorithms. Mathematically, we identified the hub genes by analyzing their degree centrality and participation coefficient in the network. The hub genes were classified as either provincial (P < 0.4) or connector (P > 0.4) hubs. We validated the expression of hub genes in both cell line and primary cells through qRT-PCR after JEV infection and respective miR mimic transfection. Taken together, our findings highlight the importance of specific target gene networks of miRNAs affected by JEV infection in NSPCs. IMPORTANCE JEV damages the neural stem/progenitor cell population of the mammalian brain. However, JEV-induced alteration in the miRNA expression pattern of the cell population remains an open question, hence warranting our present study. In this study, we specifically address the downregulation of four miRNAs, and we prepared a protein-protein interaction network of miRNA target genes. We identified two types of hub genes in the PPI network, namely, connector hubs and provincial hubs. These two types of miRNA target hub genes critically influence the participation strength in the networks and thereby significantly impact up- and downregulation in several key biological pathways. Computational analysis of the PPI networks identifies key protein interactions and hubs in those modules, which opens up the possibility of precise identification and classification of host factors for viral infection in NSPCs.

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