Genetic profiling of somatic alterations by Oncomine Focus Assay in Korean patients with advanced gastric cancer

Park, Joonhong; Lee, Sang Il; Shin, Soyoung; Hong, Jang Hee; Yoo, Han Mo; Kim, Jeong Goo

doi:10.3892/ol.2020.11990

Cited by 6 publications

(4 citation statements)

References 36 publications

(60 reference statements)

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“…The plug-in biological network ontology tool (Bingo) (version 3.0.3) in Cytoscape was used to analyze the hub gene and visualize its biological processes ( 25 ). Using the National Center for Biotechnology Information (NCBI) genomics browser ( https://www.ncbi.nlm.nih.gov/ ), a functional clustering of central genes was constructed ( 26 ). Kaplan-Meier plotter was used to analyze overall survival and disease-free survival associated with the expression of central genes.…”

Section: Methodsmentioning

confidence: 99%

“…Using the National Center for Biotechnology Information (NCBI) genomics browser (https://www.ncbi. nlm.nih.gov/), a functional clustering of central genes was constructed (26). Kaplan-Meier plotter was used to analyze overall survival and disease-free survival associated with the expression of central genes.…”

Section: Construction Of the Ppi Network And Analysis Of Modulesmentioning

confidence: 99%

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Bioinformatics analysis of key biomarkers for bladder cancer

Bai

et al. 2022

Biomed Rep

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Bladder cancer (BC) is one of the most prevalent genitourinary cancers. Despite the growing research interest in BC, the molecular mechanisms underlying its carcinogenesis remain poorly understood. The microarray datasets GSE38264 and GSE61615 obtained from the Gene Expression Omnibus (GEO) database were analyzed and differentially expressed genes (DEGs) were identified, which were then verified using a dataset from The Cancer Genome Atlas (TCGA). By taking the intersection of the two microarray datasets, the common DEGs were identified and these were selected as candidate genes associated with BC. The DEGs were further subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and the protein-protein interaction network was constructed. Further module analysis was performed using STRING and Cytoscape. A total of 362 DEGs were identified, including 13 hub genes, and the GO analysis revealed that these genes were mainly enriched in extracellular matrix organization, positive regulation of cell proliferation, angiogenesis and peptidyl-tyrosine phosphorylation. The expression changes of PTPRC, PDGFRA, CASQ2, TGFBI, KLRD1 and MT1X in the different datasets indicated that these genes were involved in the development of BC. Next, the differential expression of these genes was verified in the TCGA dataset, and ultimately, these 13 genes were determined to be related to the occurrence and development of BC. Finally, the cancer tissues and adjacent tissues of patients with BC were collected and subjected to reverse transcription-quantitative PCR, the results of which were consistent with the bioinformatics prediction. The present findings provide several vital genes for the clinical diagnosis and treatment of BC.

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Section: Methodsmentioning

confidence: 99%

Section: Construction Of the Ppi Network And Analysis Of Modulesmentioning

confidence: 99%

Bioinformatics analysis of key biomarkers for bladder cancer

Bai

et al. 2022

Biomed Rep

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“…Sequencing Binary Alignment Map (BAM) files were analyzed with the Ion Reportt Software (Version 5.16, Thermo Fisher Scientific, Texas, USA) and have been uploaded to the Ion Reportert Server cloud system under institutional license (https://ionreporter.ther mofisher.com). Variant calling and data analysis were performed as described by Park et al 32 We used Oncomine Focus -520 -w3.1 -DNA and Fusions -Single Sample workflow, and analysis was performed using Oncomine Variant Annotator v3.1 in Ion Reporter.…”

Section: Bioinformatic Analysismentioning

confidence: 99%

Identification of prognostic factors in classic Hodgkin lymphoma by integrating whole slide imaging and next generation sequencing

et al. 2022

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“…GC is a complex disease, the pathogenesis of which involves multiple genes and is highly related to variations in exon or intron groups. In the last two decades, after the introduction of next-generation sequencing (NGS), many driver genes involved in GC pathogenesis and several important signaling pathways have been identified, thus improving the understanding of the molecular mechanism of GC ( Park et al., 2020 ; Businello et al., 2021 ; Gu et al., 2021 ; Sundar et al., 2021 ). For example, Wang et al.…”

Section: Introductionmentioning

confidence: 99%

Serological and Molecular Characterization of Hepatitis B Virus Infection in Gastric Cancer

Luo

et al. 2022

Front. Cell. Infect. Microbiol.

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Hepatitis B virus (HBV) infection has been reported to be associated with gastric cancer (GC). Nonetheless, no study has revealed the role of HBV infection in the survival of patients with GC, and the mutation profiles of HBV-infected patients with GC have never been documented. Here, we performed an updated meta-analysis and found a significantly increased risk of GC in HBV-infected individuals (sOR, 1.29; 95% CI, 1.22-1.37). Furthermore, we observed that in the Anhui area, the rate of serum HBsAg positivity (OR, 1.62; 95% CI, 1.03-2.55) was significantly higher in GC patients than in controls. Moreover, our results showed that HBV-positive patients had significantly worse disease-free survival (HR, 1.98; 95% CI, 1.39-2.82) and overall survival (HR, 1.84; 95% CI, 1.19-2.85) than HBV-negative patients. The results of Cox proportional hazards regression proved that HBV infection was an independent adverse prognostic factor in GC. Furthermore, by performing targeted-NGS, we found unique mutation profiles in HBV-infected GC samples, including five frequently mutated protein-coding genes (KMT2B, KMT2D, SOX1, FGF12, and TUBB2B). Expression and survival analyses of these genes identified three novel candidate genes that may have potential roles in GC development. Gene Ontology enrichment analysis showed that the recurrent mutations in HBV-positive GC samples were related to cell proliferation, cell migration, and transcription. Taking together, our study proved that HBV infection is an independent prognostic factor in GC patients. The unique mutation profiles of HBV-infected patients with GC open a new research direction toward the underling mechanism between HBV infection and GC.

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Genetic profiling of somatic alterations by Oncomine Focus Assay in Korean patients with advanced gastric cancer

Cited by 6 publications

References 36 publications

Bioinformatics analysis of key biomarkers for bladder cancer

Bioinformatics analysis of key biomarkers for bladder cancer

Identification of prognostic factors in classic Hodgkin lymphoma by integrating whole slide imaging and next generation sequencing

Serological and Molecular Characterization of Hepatitis B Virus Infection in Gastric Cancer

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