Identifying multiple collagen gene family members as potential gastric cancer biomarkers using integrated bioinformatics analysis

Li, Zhaoxing; Liu, Zhao; Shao, Zhiting; Li, Chuang; Li, Yong; Li, Renjie; Zhang, Yifei; Tan, Bibo; Liu, Yu

doi:10.7717/peerj.9123

Cited by 23 publications

(22 citation statements)

References 41 publications

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“…There were several literatures using the same dataset in this study ( Chen et al, 2020 ; Chi et al, 2020 ; Li Z. et al, 2020 ; Tian et al, 2020 ; Wang F. et al, 2020 ; Wu et al, 2020 ). However, most of them selected multiple genes for GC by some routine methods and did not concentrate on one gene/biomarker.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Cyclin-Dependent Kinase 1 as an Independent Prognostic Factor for Gastric Cancer Based on Statistical Methods

Zhang

Zou

et al. 2020

Front. Cell Dev. Biol.

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ObjectiveThe aim of this study was to investigate the expression of cyclin-dependent kinase 1 (CDK1) in gastric cancer (GC), evaluate its relationship with the clinicopathological features and prognosis of GC, and analyze the advantage of CDK1 as a potential independent prognostic factor for GC.MethodsThe Cancer Genome Atlas (TCGA) data and corresponding clinical features of GC were collected. First, the aim gene was selected by combining five topological analysis methods, where the gene expression in paracancerous and GC tissues was analyzed by Limma package and Wilcox test. Second, the correlation between gene expression and clinical features was analyzed by logistic regression. Finally, the survival analysis was carried out by using the Kaplan–Meier. The gene prognostic value was evaluated by univariate and multivariate Cox analyses, and the gene potential biological function was explored by gene set enrichment analysis (GSEA).ResultsCDK1 was selected as one of the most important genes associated with GC. The expression level of CDK1 in GC tissues was significantly higher than that in paracancerous tissues, which was significantly correlated with pathological stage and grade. The survival rate of the CDK1 high expression group was significantly lower than that of the low expression group. CDK1 expression was significantly correlated with overall survival (OS). CDK1 expression was mainly involved in prostate cancer, small cell lung cancer, and GC and was enriched in the WNT signaling pathway and T cell receptor signaling pathway.ConclusionCDK1 may serve as an independent prognostic factor for GC. It is also expected to be a new target for molecular targeted therapy of GC.

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Section: Discussionmentioning

confidence: 99%

Analysis of Cyclin-Dependent Kinase 1 as an Independent Prognostic Factor for Gastric Cancer Based on Statistical Methods

Zhang

Zou

et al. 2020

Front. Cell Dev. Biol.

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“…SGC cell proliferation is coupled with remarkable fibrosis when the cancer cells enter into the submucosa composed of stromal cells. Coincidentally, the fibrosis is induced by the excessive deposition of collagen (COL), including COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, COL5A1, and COL5A2 in GC (11). The unique feature of SGC, compared to the other GC types, is high expression of type IV collagen in the stroma of undifferentiated GC with desmoplastic reaction (40.4% vs 9.0%) (12).…”

Section: A B D Cmentioning

confidence: 99%

Crosstalk Between Cancer Associated Fibroblasts and Cancer Cells in Scirrhous Type Gastric Cancer

et al. 2020

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Gastric cancer (GC) is the third leading cause among all cancer deaths globally. Although the treatment outcome of GC has improved, the survival of patients with GC at stages III and IV remains unsatisfactory. Among several types of GC, scirrhous type GC (SGC) shows highly aggressive growth and invasive activity, leading to frequent peritoneal metastasis. SGC is well known to accompany abundant stromal cells that compose the tumor microenvironment (TME) along with the produced extracellular matrix (ECM) and secreted factors. One of the main stromal components is cancer associated fibroblast (CAF). In the SGC microenvironment, CAFs are a source of various secreted factors, including fibroblast growth factors (FGFs), which mediate prominent tumor-stimulating activity. In turn, cancer cells also secrete numerous factors, which can activate and educate CAFs. Current findings suggest that cancer cells and stromal cells communicate interactively via the soluble factors, the ECM, and likely also by exosomes. In this review, we focus on the soluble factors mediating communication between cancer cells and CAFs in SGC, and consider how they are related to the modulation of TME and the high rate of peritoneal metastasis. At last, we discuss the perspectives on targeting these communication pathways for improved future treatment.

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“…COL1A1, COL5A2, COL12A1 belong to the collagen-forming gene family [49], and each collagen is composed of 3 polypeptide chains numbered with Arabic numerals [50]. The collagen-forming gene family is involved in the formation of collagen in extracellular matrix proteins [51] and overexpressed in a variety of cancers [52].…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics analysis of aberrantly methylated- differentially expressed genes in gastric cancer

Siyuan

Shu

2021

Preprint

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Background: This study was carried out to identify the aberrantly methylated-differentially expressed genes in gastric cancer (GC). Methods: We downloaded data of gene expression microarrays GSE118916 and gene methylation microarrays GSE25869 from the Gene Expression Omnibus (GEO) database. The DEGs and DMGs were analyzed by the limma software package and Venn diagram. The PPI network was mapped and the enrichment analysis was conducted by the DAVID database. GEPIA online tool, Oncomine database, HPA, and cBioPortal tool were used to verify hub genes. Result: We obtained 110 Hypo-HGs, 9 high-regulation hypomethylation oncogenes, 23 Hyper-LGs, and 2 low-regulation hypermethylation tumor suppressor genes. Hypo-HGs biological process mainly involves cell adhesion and extracellular matrix organization, Hyper-LGs biological process mainly involves response to nicotine and xenobiotic metabolic process. KEGG analysis showed that Hypo-HGs significantly enriched in Focal adhesion, PI3K-Akt signaling pathway, and ECM-receptor interaction. Hyper-LGs significantly enriched in Drug metabolism-cytochrome P450, Chemical carcinogenesis, and Metabolism of xenobiotics by cytochrome P450. The database identified the hub genes were COL1A1, THBS1, COL5A2, COL12A1, and CXCR. Conclusion: COL1A1, THBS1, COL5A2, COL12A1, and CXCR4 can be used as a target for precise diagnosis and treatment of GC. Focal adhesion, PI3K-Akt signaling pathway, and ECM-receptor interaction are important mechanisms of GC.

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Identifying multiple collagen gene family members as potential gastric cancer biomarkers using integrated bioinformatics analysis

Cited by 23 publications

References 41 publications

Analysis of Cyclin-Dependent Kinase 1 as an Independent Prognostic Factor for Gastric Cancer Based on Statistical Methods

Analysis of Cyclin-Dependent Kinase 1 as an Independent Prognostic Factor for Gastric Cancer Based on Statistical Methods

Crosstalk Between Cancer Associated Fibroblasts and Cancer Cells in Scirrhous Type Gastric Cancer

Bioinformatics analysis of aberrantly methylated- differentially expressed genes in gastric cancer

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